We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
I love being able to quickly bring out the program that is already running in my head without having to worry about the grind of typing it into a format that the compiler understands. Dealing with API names. Syntax. Language quirks. Library gotchas. A sizeable portion of my successful career as a software engineer was spent on the tiresome process of interacting with a text editor/IDE to get a program to do what I wanted.
I was there when people were still coding assembly. A slow torture where the simplest things took forever to get right.
Once I've mentally solved the problem, the fun is mostly over for me. Pure vibe coding is dull and unsustainable with current technology for all but the simplest systems; AI-assisted coding, on the other hand, rekindled my passion for computers.
I like your constructive outlook and I want to believe that we can now focus on the bigger picture, but I'm not really seeing it around me. Most everyone I know that's "AI-pilled" has spent the newfound capacity on throughput instead of altitude.
Is anyone actually seeing a shift towards improved structure rather than more code, faster? We seem to be living in the Gatling-gun version of the picture John Carmack drew when modernity also ushered into precision marksmanship...
The people who are using AI to improve what they were already doing anyway, aren't going around expounding "I made this with AI!"
Like one of my personal projects is a sort of "middleware" for Godot, and it needs to be lean, precise and match certain rules, because it's meant to be used by many games, so I can't blindly trust AI to generate code for it, it'd be too sloppy,
BUT Codex reviews have been a great help in finding bugs that would have taken me ages to even notice on my own. Some of those AI findings helped me overhaul entire subsystems, still manually coded.
I feel like using LLMs as a sort of deep search to find bugs and security issues is going to end up relatively uncontroversial all around, if the externalities of LLM use are ever taken care of.
I use vibecoding to capture UX. It's the best way of capturing requirements I've seen so far. Then once it's all captured and dies down towards requirements that are all in the "could have" category of MoSCoW, then I use AI-assisted coding (and the fun task of reading tens of thousands of source code lines) to refactor or create an entirely new application that is more technically sound.
Are those people working on products or platforms? Platforms still have to be rock solid and deliver performance guarantees to the products built on top of them.
>> Is anyone actually seeing a shift towards improved structure rather than more code, faster?
Yes. At work we recently finished a complete rewrite of the platform. The old codebase got abandoned and two new codebases got stood up. Previous stack was Phoenix LiveView and the new one is Phoenix API + Vue /w TypeScript. Zero code shared between the two. We took the opportunity to re-architect a lot of the core functionality and get rid of the tech debt that had been hounding us and killing our velocity for the past six years.
We finished the rewrite in two months. A little over 700k LoC total. 95% of it was planned, orchestrated and written by AI. We could have gotten it done faster, but we were well aware of the potential for slop and thus paid an absurd amount of attention to (and tokens for) code quality. For example, there is a 100% test coverage requirement in both server and client, combined with AI-driven review rules that say all tests must be non-vacuous, plus a ton of invariants enforced via deterministic checks. Everything from standard linting and formatting rules to AI-necessitated stuff like "comments cannot be more than five lines each" is in there. At the end of each week, we get together for ~30 minutes to review each bug that was fixed that week (there haven't been that many) and try to figure out if more deterministic checks can be added (or new ones extended) to prevent that class of bug from re-appearing. We actually have an Architecture epic with a dedicated Fable agent orchestrating all the initiatives and tickets in it and keeping track of improvements (and the occasional regression). So things like accessibility, usage of shared helpers, enforcement of common patterns, etc. are all kept track of.
The difference between the old codebase and the two new ones has been night and day. The new codebases, combined, are ~35% larger than what we had before, and yet there are way fewer bugs (we actually got suspicious at first and had to check to make sure our logging instrumentation was configured correctly). Performance is also stellar, features have been a lot easier to add and extend, and everything is a lot easier to find. When someone asks a question or has an issue we have a pretty good idea of what part of the codebase to look in and we're usually right.
It wasn't all unicorns and rainbows. Not everyone on the team was proficient with AI-driven development, so they had to be brought up to speed quickly and taught the tools and also what works and doesn't. Code reviews were also difficult and time-consuming. We had to deal with our anxieties about working in two new codebases none of us had authored much code in ourselves. What made all of it worse was that we were racing towards a deadline imposed by external factors so we all ended up working a lot of hours. It was essentially between getting it done this summer or waiting until next summer and we bit the bullet and did it. It absolutely would not have been possible without AI.
That is interesting, but... is it actually improving structure?
We're mid-way through a similar process at work. Rewriting a legacy app in a new language, with new architecture and new features.
And it's a mess.
We're at 10x loc (admittedly, the new programming language is more verbose than the old one), comments make no sense. Yes, we have ~100% coverage, but most of the tests are meaningless. The agent keeps removing our tests to replace them with tests that are easier to pass, breaking code invariants, removing all the engineered data structures and replacing them with stringly-typed code, etc.
And of course, given the number of LoC (and the fact that the agent rewrites so much code all the time), it's physically impossible that all of them were reviewed by a human being.
AI made it possible, insofar as upper management would never have greenlit the project without AI, but I can't escape the feeling that we're building on quicksands.
In my experience, when you attempt something like this it grows like a crystal. If you start badly, with poor tests and poor architecture, that is the code that has the attention of the model going forward. More than any rules you give it, what matters to the model is all the code that’s already there. I’ve found myself in such a situation from going to fast and expecting new hyped models to “just take care of it”. The solution was to stop and take stock. I ended up deleting most of the dead-end and using the models to refactor the rest. From that point on, new code from the models was at the standard I needed, following rules already expressed in the code base.
If your code base is script-kiddy garbage, your models are only going to keep writing more garbage. You should throw it all away. I expect that isn’t an option. Try instead instructing the model that the code you have is legacy garbage written in a hurry that needs siginificant refactoring, but that right now I need one new feature written to these new standards instead. Take it one small piece at a time. Don’t let context go beyond 100k. Good luck!
10x loc? wow. That makes me wonder how it will perform. And how you will review that, since if it is physically impossible for a human then who will take responsibility for what you release?
>> That is interesting, but... is it actually improving structure?
Can you be more specific? "Improve structure" can mean different things to different people.
We've ensured that agents strictly adhere to code architecture rules, using both agentic review rules and deterministic CI gates. Everything from file naming, location and namespacing to the "shape" of each file that shares the same role are consistent. We can trace functions of the same role across the same set of modules, with abstractions and code reuse where they make sense. Once someone learns the code in one part of the codebase, their understanding of that "spine" translates to other areas - the only differences relate to the specific business rules governing those areas.
>> And of course, given the number of LoC (and the fact that the agent rewrites so much code all the time), it's physically impossible that all of them were reviewed by a human being.
Code review was difficult at the start due to the volume of code. One insight we gained midway through though is that the value humans bring to code review is judgment and business context. So we created a code-atlas skill that creates an artifact for PR reviewers. That artifact highlights the most important parts of the code. For example, if a PR author has made the choice to use soft-deletes when the product uses hard-deletes for everything else, that is flagged by the code atlas, and a human reviewer can use that to ask questions about it. Meanwhile, things like boilerplate are de-emphasized; any problems associated with them are reliably found and flagged by AI reviewers anyway. The refreshing part about this is that this has almost completely eliminated bike-shedding: people no longer argue about module naming or whether a comment is worded properly.
> Code review was difficult at the start due to the volume of code. One insight we gained midway through though is that the value humans bring to code review is judgment and business context. So we created a code-atlas skill that creates an artifact for PR reviewers. That artifact highlights the most important parts of the code.
Yeah, we did that, too.
But every time I end up, for some reason, digging up deep in the code, I realize that it's not nearly sufficient in our case.
Assuming the LLM never got anything wrong or otherwise had to be re-prompted, that means your devs were reviewing 130 SLOC per hour, on what was described as moderately greenfield (examining new implementations rather than comparing to old historical accidents).
How?
I don't want to sound flippant, but if the point is to add human thought to the mix, that's a high review rate even when examining small tweaks to an existing, working product, even with substantial AI help to pre-filter major gotchas before you bother spending a lot of human effort on the review. That's only 20-30wpm, but a review isn't just scanning or reading code, especially if you're trying to figure out how a new system which doesn't run yet will fit together.
The fatigue aspect matters too, but another important point I was trying to get across is that not all reviews are created equally. In a working, well tested, properly factored system, with a high quality PR, I can do a cursory, local analysis of the new code and be very confident that it works. AI code I've seen is ... not that. I wouldn't be comfortable in that review without manually checking preconditions and postconditions, defining invariants, examining lifetimes, and a host of other activities. Moreover, for a greenfield replacement of lots of SLOC, I'd expect that most of the code for the early PRs can't even meaningfully run or do anything important, making any sort of broader architectural analysis impossible.
I could see a world potentially where they came up with a magic prompt allowing each proposed PR to be cohesive, shippable, well factored, and everything else you need to be able to actually review it at a higher level and be comfortable with the results, but I'm skeptical. That's a major innovation if they managed to do so even as a one-off, and that wasn't the thing they highlighted when talking about the project.
Is that actually a high review rate? Especially if you know the language and domain. Sure, initially there's a learning curve for a new codebase structure, but lots of lines will also be trivial and many changes might also be similar to each other.
For small separate changes in isolation then maybe it's ok? But not for whole days 8 hours each.
But then you need to watch for bugs coming from interaction with previous changes and in 700k loc that might be nontrivial. How do you know which states are reachable and which are not? That takes time.
It only takes a botched condition here (forgot a "not"? swapped "and"/"or"?), a swapped variable name there, code that looks ok, but isn't.
Could you share more about how you guys set up the rewrite? I am interested in the shape of the software as well as how you achieved (or aimed to achieve) high quality.
> We could have gotten it done faster, but we were well aware of the potential for slop and thus paid an absurd amount of attention to (and tokens for) code quality. For example, there is a 100% test coverage requirement in both server and client, combined with AI-driven review rules that say all tests must be non-vacuous, plus a ton of invariants enforced via deterministic checks.
This is why my current view in terms of LLM productivity gains are:
- debugging and triaging 5x
- refactoring when you have tests in place 3x
- greenfield where you have zero tests is about 1.5x
> For example, there is a 100% test coverage requirement in both server and client, combined with AI-driven review rules that say all tests must be non-vacuous,
look, your application works, right? so it doesn't really matter what you or i think, and this is why AI matters. but this, your "100% test coverage" - that is pure slop. just 20 years ago, all the most popular software shipped with NO tests. are you getting it?
> just 20 years ago, all the most popular software shipped with NO tests
not sure what you're point is here. It sounds similar to "we use to use blood letting and leeches and doctors didn't clean their hands and everything was fine so what are you getting at?"
Good tests have real benefits. The fact that people shipped without them in the past in no way suggests they aren't needed or have no point.
Also, 20 years ago SW was tested by QA department and approved before shipping. Don't want to go back to that, but there were testing, just differently.
IMHO getting rid of proper QA done by teams of QA specialists is the main reason for the current software quality crisis (and that already started 15 years ago or so). We should go back to QA teams and proper QA procedures! Automated tests are no replacement, especially when they are set up by the same people designing and building the product.
> just 20 years ago, all the most popular software shipped with NO tests
Are you getting older? A lot of people anchor their intuition of time and history to a certain year. There are probably still lots of people who think the 1990s is not that long ago even though it’s now over a quarter century since it ended. Maybe you mentally default to 2012 or so, when it might be true that most popular software shipped without automated tests (although manual QA was a lot more extensive in 1992).
But 20 years ago is now 2006, and unit tests were well established as a best practice. Perl had extensive automated tests in the late 1990s that everyone who ever compiled Perl would have noticed, since they were run by default and produced obvious output. Kent Beck’s “Test Driven Development: By Example” was released in 2002, and popularized both the name and practice.
But 20 years ago is now 2006, and unit tests were well established as a best practice.
I agree with the spirit of what you wrote, but my recollection of the timeline is different. The first decade of the 2000s was peak Crazy Agile Advocacy, but IIRC it wasn’t until the 2010s that unit testing really became almost universal practice. Much before that and it was still tangled up with XP, TDD and lots of other things that certainly weren’t universally accepted as good practices (notwithstanding the strident advocacy of a certain group of consultants/authors/speakers/bloggers and their fans).
I remember, back in the mid-2000s, when we had some consultants brought in to talk about different aspects of quality and testing. There were several working groups, each led by one of those external consultants, and one of them was about unit testing. This was in a relatively large software development organisation for the time, a few thousand people, and while some parts of the organisation had some form of automated testing operating by then, it definitely was not the case that the well-known products produced by the organisation all had a unit test suite. Other practices we’d consider routine today, such as peer code reviews, were also in their infancy during that period: some were doing them, many were not, and generally we had much less experience of how to do them effectively than we have today.
As an industry, I don’t think we really matured in how even the most ardent fans of unit testing were writing test suites until the 2010s either. In the 2000s, we still had lots of people mocking the entire universe and then writing unit tests that were 99% testing those mocks because of 100% test coverage requirements, and similar dogmatic nonsense.
By the 2020s, I think there was much more awareness of that automated testing is generally a good idea, but there are different kinds/levels of automated testing and finding a mix that suits each project’s specific needs is important. One of the great benefits from the more recent AI tools, particularly the agentic ones over the past year or so, has been that it has clearly demonstrated both the value of a good automated test strategy and how much of a waste of time vacuous tests are.
>> but this, your "100% test coverage" - that is pure slop.
Not really, but I can see why some people think that.
We treat 100% test coverage as "required, but by itself not sufficient". It doesn't give us false confidence that everything will be perfect or anything like that. But it provides us with the discipline to make sure no corners are cut, and the bugs that are fixed don't come back.
One refreshing aspect was that during PR reviews we stopped debating whether something needed test coverage. Instead we focused on what was being tested and how.
> One refreshing aspect was that during PR reviews we stopped debating whether something needed test coverage.
I’d be curious to know what percentage of the time spent implementing tests would have otherwise gone to discussions about whether to implement them or not. ;)
> just 20 years ago, all the most popular software shipped with NO tests. are you getting it?
Not really?
About 20 years ago, I was working on Firefox and we had millions of tests on CI. I was working on a host of other open source apps and they all had tests (most of them had no CI, of course).
If only the careless drivers were those crippled or killed by their poor driving, it'd be a self-resolving issue as you imply, and nobody should care.
However, what actually happens is that careless drivers often cripple or kill innocent bystanders in other vehicles as a result of their poor driving. That's why seatbelt laws and improved vehicle safety features are a good thing.
I'm exactly the opposite. I like knowing how the code works, what the data structures are, what APIs are being used, and yes even typing the code into the editor. When I'm working with LLMs there's less thinking. I'm bored. My brain is not fully engaged in the task. There's less sense of accomplishment in the finished product.
I also prefer to drive cars with manual transmissions.
> I like knowing how the code works, what the data structures are, what APIs are being used, and yes even typing the code into the editor.
I'd say it probably depends on the kind of work you do - if the low level details are exciting then that's totally understandable. But if you're dealing with more rote CRUD work or soul sucking enterprise bullshit, then probably less so and the low level details are obstacles to getting things done, alongside sometimes unreasonable workloads.
> Every programmer starts out writing some perfect little snowflake like this. Then they’re told on Friday they need to have six hundred snowflakes written by Tuesday, so they cheat a bit here and there and maybe copy a few snowflakes and try to stick them together or they have to ask a coworker to work on one who melts it and then all the programmers’ snowflakes get dumped together in some inscrutable shape and somebody leans a Picasso on it because nobody wants to see the cat urine soaking into all your broken snowflakes melting in the light of day. Next week, everybody shovels more snow on it to keep the Picasso from falling over.
That said, AI will probably saturate most CRUD work first, which doesn't make for great job prospects.
> I'd say it probably depends on the kind of work you do - if the low level details are exciting then that's totally understandable.
Even those who work with CRUD apps need to know things like computational complexity of standard container types, and how to pick basic data structures or choose which basic algorithms to use. Otherwise you'll end up implementing things that have an unreasonably high computational cost that will rear its head at the wrong time.
> That said, AI will probably saturate most CRUD work first, which doesn't make for great job prospects.
I think so too. Today's AI models excel at makeshift plumbing. The boring CRUD jobs are the first ones to go with a prompt.
Not necessarily a bad thing. Just because Carmack has an optimistic view and has some catchet in the programming world doesn't mean he's any more correct than a raving lunatic. Frankly, he said relatively little of substance and it's only made more irrelevant because he's said it from a priveleged position.
"Just because a man, who has some cachet with mountain climbers for being the first to climb mount everest doesn't mean he's any more correct about how to climb mount everest than a raving lunatic". That's your pitch?
Carmac has shipped massive selling, fun games, using low-level, innovative techniques, back when such crazy shit was necessary. The issue is the difference between what is necessary ("Miyamoto") and what is prescriptive ("Kung Fu").
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
Focusing on data structures, architecture and algorithms is what competency in programming has looked like since forever. Building systems out of smaller pieces gets you there.
If your complaint above is that you were struggling with syntax and reading documentation, one might ask if you failed to progress past beginner levels, and now AI is just your cheat-code?
Some projects have fantastic documentation. Qt comes to mind. The experience of writing Qt is a pleasure because I can always jump to the doc for whatever class I'm dealing with and find what I'm looking for immediately. Also every argument type is well-linked in every signature so it's easy to follow and understand everything you're dealing with.
> Focusing on data structures, architecture and algorithms is what competency in programming has looked like since forever
yes, being able to bang out leetcode hard from head on an interview on paper matters so much... oh wait. it does not.
in the real world, outside of interview questions, it hardly matters. when it comes there, I'll optimizite it, but getting the first system up and running in a way I want is way more fun & challenging. need a lock free ringbuffer? I'll look up what's the latest way to build it. or just ask my AI.
> yes, being able to bang out leetcode hard from head on an interview on paper matters so much... oh wait. it does not.
That's about reciting standard data structures like stack and queues. I think parent is talking more about the design of primitives for the domain of the software. That requires creativity and insight.
I think you are not interpreting GP in the most charitable way. He simply said that not having to manually write all the code lets him spend his energy on bigger things. That is different from "struggling with syntax".
It is the same. I mean many mainstream languages made thinking in datastructures hard. Not a coincidence why functional languages, Haskell, F#, OCAML, Scala, Clojure, LISP, etc. had their enthusiast, as they felt just like what you claim.
The datastructures already did the heavy lifting. The syntax was not something to struggle with, but it was the natural way to stick the bits together.
JavaScript for one never gave me this feeling, and I always felt that either the language, or the libraries, but something was always a struggle to overcome. (Python too... seriously, working with collections is a pain in the "pythonic" way for someone who has experienced LINQ... and for most line of business apps it is all about working with collections.)
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
Why? What makes you think your data structure design, architecture and algorithms are ever going to surpass AI in the near future?
You honestly can't see a (near) future where those 3 elements are done by AI, not by you?
I can and I'd be okay with that too. The world doesn't have carriage makers anymore. Nobody is entitled to doing what they love or what they are good at. I certainly didn't as my job as a software engineer, despite being profitable, was far from what I like in the discipline.
That said, I think AI is still many years or decades away from completely replacing the Software Engineering profession. My kids are entering college right for a CS degree and that's what I tell them. I have skin in the game as I'm ultimately responsible for them.
I could be wrong, but anyone's opinion is at most an educated guess at this point.
I’m the opposite. I don’t believe there is a royal road to understanding anything. For me, the process of programming involves frustration. That is usually when I find my greatest insights.
Syntax isn’t a big deal. Names either. You can look them up. Remember them. Language gotchas are annoying and sometimes problematic.
To me, our job is understanding problems. And for me, understanding the problem involves wrestling with the code. I learn much from modelling problems in code, building theories, testing them.
Once an LLM system has generated some code I haven’t learned anything. Even when I read through the solution. It doesn't require the same activation of my brain. There’s nothing quite like working through the problem yourself.
LLMs definitely feel like they are draining my passion for computers. There were plenty of folks who checked out or were never truly passionate about programming. Now they’re louder than ever. “Nobody cares about code,” and, “optimizing is a waste of time.” Now we don’t even want to understand how it works, or whether it works at all. They repeat the lines their master have told them: get on board or get left behind.
I’m pretty sure I am risking getting, “left behind.” But I’m okay with that. The tech is truly the least interesting thing to me. If I don’t have a career in 10 years… oh well. I’ll still be programming.
The possibility to have an agent implement every little thing that comes up in your mind as you're building doesn't spark the tiniest bit of joy? Previously, "ooh it would be cool if" had to answer to "yeah but it'll take too long". Now, it's more like, "how important is that really?" to stupid ideas that never would have seen the light of day before.
> "ooh it would be cool if" had to answer to "yeah but it'll take too long". Now, it's more like, "how important is that really?" to stupid ideas that never would have seen the light of day before.
My answer was it to "ooh it would be cool if" has always to build a PoC of the thing or a MVP, then I can flesh it out when I need more features. Sometimes a web app can be a single PHP script, and a cli command can be as simple as a single file C program. Or using tkinter with python for GUI.
The answer to "ooh it would be cool if I can travel fast" is not "yeah but it'll take too long to build a car". It's "let's build a kick scooter first".
Not even a little bit to be frank. The joy of things came from their implementation to me. I will write something and then peruse its code on github for hours afterwards just looking, like one would at an art gallery.
If I did not toil on it I wont use it most likely. There's a very very small amount of software I ACTUALLY desperately need in a way that I would not care how it came to exist.
Do not get me wrong, those things exist, i have a plethora of dog shit vibe code websites, clis and tuis and other random stuff on a self hosted forgejo. They did their job now they die. But it brought me no joy, in fact it was rather unpleasant the entire time doing it.
Have you tried live programming (smalltalk, LISP)? Or a proper Edit-Compile-Run cycle with a good editor?
A lot of people are bashing old practices, but from y standpoint, it always seems like a lack of proper (usage of) tooling to streamline the coding phase of building software.
Dear sir, I appreciate the help but, as I mentioned, I've been around since the Assembly days... Been there, done that. I currently have a crazy efficient Edit-Compile-Run setup and a great VSCode personal config, all of which were made a lot more crazy efficient with Codex.
LISP has been around since 1959. To the point: the proclaimed advantage of operating at new levels of "abstraction" is not a novel contribution of LLMs to coding.
Put another way: live coding, meta programming, high level abstraction, all have been possible for some 60 years now. Two generations! We don't need the monstrous amounts of accidental complexity involved in running dozens of GB in RAM for LLMs and all the "harness" apparatus, we have had from the right tooling for almost a century (!) now.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
That would be lovely.
It's sad that we're being forced to vibe code, though, because my day-to-day experience of that is that the agent does not respect the data structures I feed it, nor the architecture, nor the algorithms.
> Pure vibe coding is dull and unsustainable with current technology for all but the simplest systems; AI-assisted coding, on the other hand, rekindled my passion for computers.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
That exact sentence could have been said 20 years as well as 40 years ago. I don't know how you programmed pre-LLM, but line-by-line has long been a thing of the past, if it ever existed. I'm sure the folks creating the Apollo software were thinking a lot about data structures, software architecture and algorithms.
Kinda agree with this. And your point is valid for most of the problems that we solve today as software engineers.
However, you cannot forget that there are problems where - all the knowledge of - AI don't help. Problems where letting AI do the work for you means putting more time and effort than doing yourself.
Problems where you need to be so precise in your prompt/spec that at that point you're coding in English. But English don't compile.
I like the idea of power tools vs hand tools. AI is a power tool, but that are times that the most pragmatic approach is using a hand tool.
>AI-assisted coding, on the other hand, rekindled my passion for computers.
I would be interested to know what you mean by AI-assisted coding.
I've been coding for 50 years (40 professionally) and maintain several largish C++ code bases for commercial apps. There is no way that I am going to let an AI scan (train on), let alone edit, my code. But I do ask MSCoPilot questions, basically using it like turbo-charged StackOverflow. And I do get some value from that, even if it is often wrong. Is that what you mean?
We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
Hadn’t good developers been focussing on those things, and other high-level modelling that relates the software system back to the underlying real world domain, for many years before the LLMs were in the picture?
I’d even say that it’s one of the most reliable markers of a more senior/experienced developer that their code reads like a clear and logical explanation of what the system does and why, with concerns well separated and minor details and technicalities abstracted away so they don’t clutter the rest of the code.
I kinda of agree, but still believe that writing most of the critical(!) code yourself has long term benefits. IME the initial mental model hardly survives contact with reality and all those little micro decisions that come up during implementation are good to do on your own and have in your own head instead of being buried in an LLM managed decision record where no human ever ventures.
It all depends of course where the code sits between "low level mission critical code" and "high level throw-away code". every non-trivial project has code across that entire range.
E.g. the lower level the code, the more I want to get directly involved, and that may mean typing each line manually to get that code directly into my head (IME for that purpose, writing is better than reading - have that manually written code reviewed by LLM instead).
Of course that only works if you don't have a manager breathing down your neck who insists on prioritising implementation speed over quality ;)
Also you should try assembly coding with modern (non-LLM) tooling, it feels incredibly more productive than with the primitive tools on slow machines of the past.
Also:
> software engineers can focus on data structures, software architecture and algorithms.
Come on, this is was already "normal" decades before LLMs, that's why an entire zoo of high level languages was created which allow to describe a solution in a highly abstract (yet still precise) way. Replacing this high level problem specification in a programming language with a "sloppy" human language specification is arguably even a step back.
(also tbf, I'm writing this comment while sitting in a cafe while the LLM at home is busy coding a GL mocking library ;) (which is exactly the boring type of throwaway code which should be automated)
M currently re-writing an app that I wrote years ago. All the issues came from data structures, queries, architecture that didn’t fit what emerged as the use case.
Now I can focus on those things and work far faster, and even ADJUST architecture, theorize about pros and cons of changes as I work … sometimes I find that some adjustments are easier than I thought.
The result is far faster development, and a more optimal result where I can stay focused on improvements / efficiency rather than random minutia.
There will always be people who will like it because they are the ones getting ahead and get some reward. If a person is rewarded for something, it's unlikely that they'll care how the reward comes or be critical of the mechanism. It's just human nature; AI has incredible downsides but those who get ahead won't mind, as long as they get ahead.
I bet thieves feel a rush when they rob a store. Does that also make it right?
a lot of people don't understand that the joy of making something is not coding but actually being able to build anything I want. AI just made it 50x better, as exactly as you said, we don't need to deal with the useless junk (what's the API syntax? what's the library syntax? oh it changed in the last 3 versions, let me look up the new API, this and that...).
> a lot of people don't understand that the joy of making something is not coding but actually being able to build anything I want
I expect "a lot of people" understand perfectly well that that's where the joy comes from for you. Do you not understand that other people have different motivations?
Crafting code in your preferred language in a way that it is easily understood by others or fulfills some other constraints while doing whatever algorithm requires can be as fulfilling as writing poetry.
I can write „you live, you die, get over with it, life is hard, love hurts” - it basically encodes all wisdom of countless poems, books. Yet I have seen many people getting that idea better when the knowledge of this simple truth is in a form of a story.
Conversely, if you write an algorithm using better structure, better data structures it makes a lot of difference.
How can you have proper real understanding of data structures and algorithms without at same time having line-by-line mental model?
Or do you blindly trust what machine tells you at whatever time you are communicating with it?
Architecture I might give not needing line-by-line model. But I really doubt the same with data structures and algorithms. Those are in the end build from lines.
Seems to indicate to me that he had full mental model of everything. Whole thing in his head at once. Clearly having it in mental model sentence by sentence.
> one where software engineers can focus on data structures, software architecture and algorithms.
I see this a lot and I'm not sure why people don't think AI will be able to do this too. The self-play training that got them writing code can be used for this too.
Given enough context for a business problem, sure.
But LLMs are not in a condition to judge how you should pick the technical solution to a business problem with several stakeholders, risks, and so on.
With the speed AI moves, a lot of technical decisions become reversible. And while engineering often makes decisions that could lie elsewhere in the business, outside of engineering, I could imagine those decisions moving elsewhere in a fully AI world.
Do you have examples of things that would be hard to train for? One that could be compensated for with changes elsewhere in the business process?
Yes, if Alex from BizDev is a scheming moron who consistently lies about the priority of features, it’s hard to keep an LLM on the loop about it when transcribing meetings and feature requests. If your boss is gonna be unavailable for a month and that means that a junior devs garbage PRs will be getting merged because the second in command is much laxer then you need to be aware for that and so on.
What I mean is that these things decant into technical decisions and even with all the AI in the world running a DB schema migration does not become any more trivial.
In the long term, I think you're correct. In the medium term, AI still won't know your business-specific workflows and data relationships, and humans are needed to define those things and let the AI build the scaffolding around it.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
I prefer an AI that is good at data structures, architecture and algorithms. Then, finally, no more leetcode.
not that i disagree, but its funny because i just came back from a presentation from a "chief ai officer" where he boldly stated that ai is the next big abstraction for programmers (even had fancy charts and tables to boot)
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
This is what declarative programming gives us, not what LLM-based generation offers.
> I love being able to quickly bring out the program that is already running in my head without having to worry about the grind of typing it into a format that the compiler understands.
Using natural instead of a formal language to get probabilistic results based on token fields is not bypassing arbitrary constraints of the compiler, it is dereliction of the responsibility to know and articulate precisely what you are specifying.
> AI-assisted coding, on the other hand, rekindled my passion for computers.
AI-assisted coding isn't a thing. Why would anyone pay you to code when your competitor spends 1 minute spelling out a problem and doing the same thing for 59 more problems?
As far as I'm concerned coding is dead as a profession, now we are Harness Managers.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
AI is getting good at picking those as well. Frontier models can be fed a vague problem, analyze the code base, and pick out an architectural solution that makes sense.
We're going from a world that needs specialized "software engineers" to speak the language of the machine into one where ordinary people need only sit down and think, "what exactly would solve my problem here?", spell it out in ordinary procedural language, and get a software solution that employs best practices without the intervention of professional computer-touchers.
Tim Bryce was right 20 years ago. Abolish programmers, bring back systems analysts!
Everyone who writes enthusiastically about AI already has the benefit of having worked without AI. They have been schooled in the basics. Enough of us know about data structures, concurrency, networks, language design etc. from the ground up that the knowledge is passed on. I worry about the world that we will be living in when a whole generation has skipped learning the basics the hard way. Given the attendance rates at various educational institutions, I fear that day is already here.
I think that anecdote is from the Anabasis by Xenophon and refers to Assyrian city of Nineveh. Babylon was still occupied during the time of Herodotus and was one of the biggest cities in the world at the time. (the book spends some time discussing Cyrus's conquest of Babylon).
Right, I weirdly feel like we are entering an era where industry doesn’t invest that much in training the next generation - it feels like a rich getting richer scenario in all aspects of society
I think mathematics is feeling that concern with training acutely. The average math department pays its way by teaching in all forms and all levels: they don’t bring in the magnitude of grant money that concretely impacts a university’s budget. But they are already dealing with the consequences of that - that’s why universities that are cutting due to “low student demand” are going after math programs.
I think this has long been the norm without AI. Just look at a lot of politians cheating with their university tests, outsourcing the work that lands them their titles to low earning ghost writers. Why do you think so many incompetent people rise to powerful managerial positions to make terrible decisions without consequences. It's probably going on for much longer than we all think because it's not always easy to find hard evidence and we're all trained to treat circumstantial evidence. How many scandals were there of influential people buying their kids into elite colleges? AI is just accelerating what's been ongoing already.
The tooling for industrial farming is reliable on the scale of millions though, and the same for any other innovation that has replaced older ways of working. AI is in a weird place because it is not 100% reliable, and we do not know if it ever will be, but we also do not know if it will eventually good enough to where we are irrelevant.
If tractors plowed reliably 95% of the time, but unless carefully monitored the other 5% of the time they would blow a big hole in the ground, it would be difficult to abandon your shovel entirely.
>Have you been schooled in farming? Raising livestock? Milking cattle?
You're equating life skills to professional skills. I was not taught to milk a cow, but my milk comes from someone who was. The topic is whether software engineers in a professional context learned certain things about software.
> Have you been schooled in farming? Raising livestock? Milking cattle? Does your ability to cook good food ...
Pushing that analogy, AI is the equivalent of automating everything from tilling, growing, all the way to cooking. It is as if the human is involved at the beginning in specifying what they want, and at the end, in plating up the food and consuming the product. The next generation will have no clue about the entire farm-to-table chain.
It's not there yet, but rapidly making it a reality.
Also, there is no one "tech". Different pieces of technology have different levels of effect on the world, and different timelines in which the world can come to terms with it. AI is the thermonuclear weapon introduced to a musket world ... it came upon us suddenly, and instantly flattened the talent/merit based economy. Now everyone has access to the same exoskeleton; the difference between muscles is not important.
The second huge difference between AI (and ordinary tech) is that a literal handful of people are in control of its economics. That kind of power breeds fascism.
> That's a problem with society, not technology.
Semantics. The tech directly enables the incredible power imbalance, and helps seize the means of consensus and debate and reporting. There is no incentive/mechanism left to fix society. An advanced society like the US is weaponized against vaccines, and social media and AI are to blame.
You do realize that the same powers that have bred fascism and mandatory id requirement are hand in glove with the AI oligarchs, no? They gain with rampant use of AI disproportionately more than the peasant.
The peasantry stands no chance. Unless there is a French Revolution style uprising
You can look up laws all night long. Check out all the laws broken by Potus, ICE (just to name a few) on a daily basis.
The peasantry is not on the side that enforces the law. AI is. AI is a force multiplier. The more force you have, the more multiples of it you en up with. Flock uses AI to do surveillance at scale. Every cloud service has NSA backdoors.
It isn't just AI. I would like a world without the poison of social media, without guns & bombs, without dangerous chemicals. Yes, in many many ways we'd be better off. We are accelerating the destruction of our planet.
I don't have a better plan for humanity. I only have fear.
C'mon, you know better than to invoke a slippery slope.
My best move is to influence the people I care about to reduce dependence on these things and seek happiness in non-tech things (where tech is defined as those controlled by corporations), from community, live life from first principles. You are forcing me to answer a strange binary ... propose a fix for the world at large, or let me continue with all this shit. The world isn't as black and white.
I would like to recommend, to both of you, Sarah Wilson’s I Eat the Stars: How to Live Fully and Beautifully in a Collapsing World. I am heartened that both of you are still trying to find solutions.
-https://www.goodreads.com/book/show/241715900
I mean, if I grow my garden and just provide you with the vegetables,
does that affect your cooking skills in any way?
In fact, if you divide your time between growing your own produce AND honing your cooking, both of those skills may suffer
compared to devoting your time to just focusing on one ability.
Otherwise if you try to do everything you'll never be as good as a full-time farmer or a full-time chef.
or how about another analogy:
Say one day your idea for a dish requires softer or sweeter carrots, etc, but oops you spent the last season only growing crunchier and mellower carrots, what're you gonna do now? With external suppliers you always have a wider choice of ingredients better suited to the end product you want at any given time.
Constraints are a good thing. I'll get creative with what I have, instead of having to rely on a supply chain that makes everything available to everybody all the time. I don't have to have apples grown on the other side of the planet.
Ironically, this post comes off as out of touch. The purpose of the various martial arts isn't just to win in a life-or-death brawl or murder people as efficiently as possible. Similarly, the point of programming isn't just to generate as much code as possible, or only to be more "productive".
Code in most organizations is a means to an end to produce an actual product.
The job of a SWE is to not produce the most sublime readable code with cute language bells and whistles that you can show off to your other programmer friends. Yes its fun to do and interesting, but the main value in writing code is to express your intent so you and other people that are working with you can actually build something of value.
Software has value to the people on your team reading it. The product that you create with your software has a far wider impact than just that. As such, there is for _sure_ optimization pressure on "professional software engineering" to be more productive and actually make the product better to use, faster, with more features users like. The user typically does not care that you used a new C++26 feature, as much as I enjoyed writing it for them.
If I can produce features for users faster and I can iterate on them faster, this is a boon to me. I can program by hand for fun all I want in my spare time, but if I want to produce value for someone else, it is economically infeasible for me to be a luddite, and I will simply be outcompeted. Previously you were outcompeted by smarter teams who out executed you (and who also worked more), and now you can be out executed by basically anyone using an LLM who actually understands that the end goal is making a product that is pleasant to use and actually has utility, not code that is pleasant to read.
You can be an "performative/artisanal programmer" just as you can do "performative/artisanal martial arts." Just know that there will not be a large market for it in the real world.
You're reducing programming to its utility in producing exchange value in the captitalist political economy. That's what "value" means in this context. That's exactly what I'm pointing out. Programming is more than that, if you can think beyond your current economic constraints. Your life's activity ought to be more than just a tool for producing capitalist exchange value.
Does cooking food serve any purpose beyond mass producing food for restaurants to sell?
You're reducing programming to its utility in producing exchange value in the captitalist political economy.
Well, yes? If you want to write code that isn't useful to anyone and just gives you warm fuzzies, go for it. I've done plenty of that. But it's exceptionally selfish to try to forbid technological improvements so that you can get paid to work exactly how you want to.
Does cooking food serve any purpose beyond mass producing food for restaurants to sell?
Should we ban industrial agriculture so that you can feel more proud of your rooftop garden?
It would be nice if I could live my life without concern for producing capitalist exchange value. However, I live under the regime of capital and need to pay rent. So my goal is to pay rent with the least amount of suffering on my part.
But we can agree that writing with such disdain about people doing literally anything else, is perhaps a bit of a bad look.
Especially if it comes from Carmack, a guy who doesn't need to pay rent any more and can in fact live the rest of his life without concern for producing value, etc etc. He is currently doing exactly what he wants, just because he wants it. And that happens to be VR stuff, currently, afaik. And that's his choice. So when he speaks deeply condescending about other people doing exactly what they want ("retro computing is so delightful") it definitely comes from a different place as "hey I just want to pay my rent".
> exchange value in the captitalist political economy.
how can one exist in modern society without being an exchange value in the capitalist political economy?
linux is where it is because it is able to be a critical part of said capitalist political economy. even if you want to be a FOSS contributor all your life, you need someone to figure out the "economy" part of it.
People are used to paying for food. They delight in paying more for highly rated Michelin starred food, even. Software is the opposite. People really really hate paying for software. It should all be free! The fact that making an additional copy of a piece of software is basically free vs creating an additional plate for dinner is very much not, has a lot to do with that. For sure. But it also means that I don't see a future where the "capitalist political economy" truely "values" aka pays seriously good money for a bespoke, handcrafted, no AI slop here, version of Photoshop to be run only once, and then you poop it out later.
When programmers say "pleasant to read", they usually mean something which is of real economical value, i.e. the code is easy to understand and maintain (whether by a programmer or an AI).
Products in most organizations are an end to making profit.
The job value of an SWE is to maximize that profit. It doesn't matter if the product is better to use, faster, with more features users like - that's an early 20th century model of value production.
What matters is how much money the company can extract from its customers, and how little it can pay its employees. Use dark patterns, increase lock-in, and switch to a rental system with recurrent payments. Minimize employee benefits, require broad non-compete agreements, have long vesting periods and lay people off before its reached, or simply fire them and order the others to pick up the slack using AI.
If you want to write software meant to please the user, do that for fun in your spare time -- though remember that your employer still owns your IP, so it's not like you can create a market competitor.
Alas, the above was meant in sarcasm but is all too true.
The Luddites were not opposed to machines. They were opposed to bad labor practices, with machine-breaking as way of applying pressure on employers.
In the sense they were not opposed to all machines as a concept. They were definitely against machines they thought reduced their labor value:
"They wrecked specific types of machinery that posed a threat to the particular industrial interests in each region. In the Midlands, these were the "wide" knitting frames used to make cheap and inferior lace articles.[22] In the North West, weavers sought to eliminate the steam-powered looms threatening wages in the cotton trade. In Yorkshire, workers opposed the use of shearing frames and gig mills to finish woollen cloth.[23]"
Yes, that's what I wrote. "They were opposed to bad labor practices, with machine-breaking as way of applying pressure on employers."
Otherwise it would be like claiming that an industrial union is opposed to people working in factories by pointing to a strike action and concluding they members just want to stand around outside the factory instead of work.
Recall that my comment is in response to "it is economically infeasible for me to be a luddite".
If that means something like "infeasible for me to oppose bad labor practices" then collective action is the typical response to bad labor practices.
If that means something like "infeasible for me to destroy the employer's use of AI" then I think that's mistaking what Luddites did as being the Luddite goal.
You wrote "The Luddites were not opposed to machines." What you wrote makes it sound as if there was no problems with machines, only with labor practices. That's simply misleading to untrue in this chain.
You can say Luddites were not only opposed to machines they thought cost them (which was the main reason they started the trouble they did at that point), but they also (insert labor practices).
Read their writings or contemporary reports. The wiki page has ample references to good material.
"Luddites were not opposed to the use of machines per se (many were skilled operators in the textile industry); they attacked manufacturers who were trying to circumvent standard labour practices of the time".
How is that meaningfully different than what I wrote?
In Musashi's era, meaning the late 1500s, kendo (sword fighting) was absolutely about being as "productive" (read: lethal) as possible.
As it happens, this was also the era when firearms had just been introduced to Japan. In 1575 Oda Nobunaga demolished the Takeda cavalry at the Battle of Nagashino, marking the first time firearms had been used at scale in Japanese combat, and in 1600 Musashi participated in the decisive Battle of Sekigahara where both sides used them extensively.
The end of the Sengoku Jidai was triggered by a warlord (Nobunaga) who equipped his armies with massed ashigaru levies armed with long spears and tanegashima arquebuses. It was absolutely a technological brawl where the valiant highly trained cavalry of warlord's like Takeda Shingen got mowed down by the bullets of musketeers stationed behind well prepared and covered firing positions.
If it was still going on today, the warlords would be adopting drone warfare and vibecoded 3d printed cruise missiles.
Everyone in Sengoku Era Japan had access and knowledge of guns and cannons.
The key for Nobunaga is "Ashigaru". Nobunaga gave the guns to the peasants. That also means that Nobunaga mass produced the guns to a level that no one else was doing.
Yes it was a technological brawl, but inadvertently it was one that worked with and uplifted the Ashigaru into a real combat force.
Japanese martial arts generally come in 2 forms. -do (the way) and -jitsu (the art). -do forms are about self improvement, -jitsu forms are about effectiveness. You can see this with judo and jujitsu. Carmac is clearly aware of this difference as he says:
"We aren’t there yet, but carefully writing code completely by hand is moving from a -jitsu to a -do. "
IIRC Carmac has done judo (I'm not sure to what level).
As someone who did train one of the traditional martial arts for a few years, I appreciate the comparison.
I don't know how much weight your "just" is meant to carry, but I remember a culture of cope and excuses about why "my" flavor wasn't the winner of any MMA event.
But at least I got some exercise, strength, and flexibility out of it.
I think it's an interesting analogy, not to be dismissed so easily.
I don't see him saying the point is volume of code. I see AI generating code, and if I question it, it can justify design choices pretty well. I can give it bug symptoms, and it can find and fix the bug. Usually.
But yes, the analogy breaks down in the fact that I understand what it's saying and understand when it's wrong, because I learned it in the first place.
Or maybe it doesn't break down completely. If an MMA (AI) tells me to move in a way where I know I'll lose my balance, or over extend, I will say no, because of my previously acquired experience.
'Make sure you don't fall behind!!!' is my least favourite type of post about ai. There's resllt nothing to learn about ai. You're just typing and telling it what to do.
This is like saying there's nothing to learn about programming, you're just telling a computer what to do. :)
It's partly true, but where this logic gets stuck is software engineering, for both the cases.
Just telling the AI what to do won't get you to good software, especially when you want to use dozens of agents working in parallel, when you have something correctness sensitive, when you want the AI to try and solve a research problem you have a hunch about but not a concrete solution.
but the solution, ironically, is not learning more about ai, but learning more about good software engineering, so you can tell when the ai is not doing it
No, software engineering is fundamentally changed because of AI. No amount of digging our heads in the sand is going to undo that.
For example, the traditional best practice cycle of "small incremental change, code review, test, commit" is pretty much obsolete now. The way ten collaborating agents can make short work of a complex project is not something that fits in with our existing software engineering wisdom at all.
We are still trying to figure out the new science of software engineering. And the best way to get better now is to just figure out what works and what does not for your use case.
I'm not talking about the transient aspects of producing software; I'm happy to accept that AI will change that, but also I feel that it will change it in ways that really aren't very hard to learn, and truth be told the more time that passes the smaller the gap will get as the agents get more capable.
what I am talking about is principles that govern what good software looks like, what properties it has to satisfy in order to be extensible and maintainable and performant and all that other good stuff, and the AIs are not going to make that knowledge obsolete any time soon.
I think this will change quite a bit too. Code being readable is one of our core tenets. Functions fitting within, approximately, a screen of code used to be ideal.
Modern AI as already past solving that problem. You can give it a million line codebase, ask where something specific is happening, and it'll tell you in less than a minute.
If we can de-emphasize readability, what do we gain?
Custom hand rolled containers and data structures for your use cases are somewhat frowned upon unless really needed. Well, probably not anymore.
What about a manually inlined mega-function with loops unrolled that pre-empts some of the compiler's work? No way that would fly a couple of years ago. Already seeing this in performance sensitive code.
> reducing the skill required to operate AI agents
For accomplishing the same task, yes.
But given these tools straight out of science fiction, why on earth would you be stuck doing the same things? There's no point spending human thought over something an agent has just automated yesterday.
Think bigger, take on more ambitious projects that are perpetually at the limits of what you and AI can accomplish.
>No, software engineering is fundamentally changed because of AI. No amount of digging our heads in the sand is going to undo that.
Yet anyone who claims that fails to procure sufficient evidence or instruction on how exactly training the to-be software engineer in the age of AI should be. Until that happens, people still learn DSA, write code manually, and train their problem solving skills with programming exercises.
And I mean handwriting them, not ordering "one solution for Leetcode 1133 in Rust, please" so we can proclaim that we're writing Rust so fast that I don't have to read a book about it anymore.
> fails to procure sufficient evidence or instruction on how exactly training the to-be software engineer in the age of AI should be.
Of course there's no instruction on how to succeed in a rapidly changing new field.
Do you think someone is more likely to succeed by getting their hands dirty and trying things out or waiting around for 'instruction' to be available?
> people still learn DSA, write code manually, and train their problem solving skills with programming exercises.
Maybe you're confusing computer science with software engineering? I agree that you'd still need to learn about algorithms, just like calculators do not reduce the need of learning algebra and trigonometry.
Yeah I'm hoping AI can bring us back to software engineering of 20 years ago. Where studying the solution to a problem, finding clever solutions, getting everything to work without getting buried in little concerns is really important and "best practices" can just be a line in agents.md and the uninteresting part can just be handed off.
> This is like saying there's nothing to learn about programming, you're just telling a computer what to do. :)
Counterpoint: a friend of mine who's not a developer has vibe coded multiple apps. They work just fine. Granted they're not particularly complex (e.g. domain specific CRUD type apps) - but clearly the skills required to do that are just "ability to talk to the AI" - in other words, everybody can do it.
You could also copy paste large blobs of code from stack overflow 'back in the day'.
The baseline of what you can do without being an expert has jumped significantly. My claim is that the baseline of what you can do being an expert has also jumped significantly.
There's nothing to learn about being an engineering manager. You tell your developers to write code, go on vacation, and come back to a completed product.
Also the thing that is infuriating is, do people obsessed with using AI for everything not realise that, they are surplus to the entire process? They are doing 'prompting' or whatever but the end goal will eventually be that they are obsolete and will not be required. Companies will just endlessly, automatically pump out AI generated stuff without any human intervention at all. The tools they gloat about will be closed up and they will not have access to them any more.
You're not really 'keeping up' with anything, you're just fooling yourself into being part of a process that wants to eradicate your presence.
It's almost like embracing this stuff is giving them an illusion of control they don't have
Don't throw the baby out with the bathwater.
It makes more sense to read his 'public statements' and judge them individually rather than in aggregate. No one is correct all the time.
As for this current post (just a tweet really, public statement sounds overly official), I think he's making sense. If you don't follow industry trends, you'll eventually be out of touch. Whether you're a senior software engineer or engineering manager, keeping current with the evolution of tech will make you better at your job. Today that happens to be related to following AI developments, but it applied equally to learning higher level programming languages in the 90s, or big data engineering practices in the 2010s.
Elon Musk, Paul Graham, Steve Yegge and now, sadly John Carmack. Your average hacker scoffs at the idea of religion or faith, but somehow is comfortable with complete unquestioning fealty to whichever person who did something interesting with technology in the past and made enough money to afford drugs you don’t get arrested for and then they started prophesying.
Before you stone me, remember every prophet was downvoted in their own forum.
The nice thing about religious faith is that most minds can hold only one at a time. I may believe in an oddly resurrected deity who took the shape of a man, but I don't have room for anything crazier.
"We are fools for Christ's sake." 1 Corinthians 4:10
Is that the nice thing about religious faith? Polytheism seems somewhat more tolerant of others. And religious pluralism takes in one step further.
I am sure about few things, but it seems to me that monotheism and religious exclusivism at some times represent the worst aspects and outcomes of religious faith.
Whatever your view of religion, you are not very good at literary analysis. The verse you quote, in full:
"We have given up our wisdom for Christ, but you have insight because of Christ. We are weak, but you are strong. You are honored, but we are dishonored"
Sure, but it is that Christ, Buddha or any of the other incarnations of the same idea? I am right there with you, believe it or not, but don’t John 3:16 the wrong football game.
I think you got downvoted unfairly because I really think you're sincere. My brain heard your comment in the voice of Nightcrawler from X-Men—and as the descendant of German Catholics, he's become one of my favorites.
I see it as those who learn to use AI effectively are seeing massive benefits. Those that haven't seen those benefits are still skeptical.
Someone who's seen the benfits, knows, with proof, the benefits exist. They're like Copernicus who realized the plants go around the sun, not the earth. The others are still like those who look up, see the planets go around the sky, and can't believe the earth is not at the center. They then shout "you're lying, you're crazy, burn the hertic!"
Even if we just look at public markets: manufacturers and hyperscalers stocks are through the roof, while they finance private model providers that are ever pushing their IPO into the future.
Doesn't look very much like growing prosperity as much as vacuuming value into the core of the corporate world system.
The story of the discovery of heliocentricism is a lot more complex than this; the people who didn't immediately accept heliocentric theories (including the ancient Greeks - look up Aristarchus) often had good, scientific reasons for doing so. Or just look up at the sky at night yourself and ask yourself how you, personally, would confirm it if someone told you that what you see in the sky is better explained by the Earth moving around the sun than the sun moving around the Earth.
> Elon Musk, Paul Graham, Steve Yegge and now, sadly John Carmack. Your average hacker scoffs at the idea of religion or faith, but somehow is comfortable with complete unquestioning fealty to whichever person who did something interesting with technology in the past and made enough money to afford drugs you don’t get arrested for and then they started prophesying.
Why do you characterize people you disagree with as having "complete unquestioning fealty" to any of these figures who did something interesting with technology in the past? Seriously, why do you think that accurately characterizes anyone's view? I think this observation that John Carmack made on Twitter has some merit to it - it doesn't mean that I worship John Carmack as my god, or even that I think he's necessarily correct about any other issue. And why would I need to do either of those things to think that the one specific observation of his that we're talking about in this thread has merit to it?
I don't think that John Carmack or any of the other people you mentioned are categorically not worth listening to because in some cases the accomplishments that originally made them famous are decades old. If you think that Carmack is wrong on this specific point, make an argument for why; I for one don't think he's wrong, and I think that putting him into a category of people who "should have ceased broadcasting decades ago" is simply avoiding engaging with what he actually said.
One of the great joys of following guys I admire like Carmack is the little smile I get when I see one of his tweets and go, "yeah, John Carmack was totally wrong about that." For example he argued that UI buttons should act on press rather than waiting for the release, and it's been a UI principle for decades that once a button is pressed you wait for the release on the button, giving the user one last chance to back out of a destructive operation by letting them move the pointer off the button and release. And I was like no, I don't care if you wrote Quake, or the Principia Mathematica, don't fuck with my UI expectations.
Carmack has cheerfully admitted to being wrong in the past, for example admitting that the Saturn port of Doom should have used the Saturn's hardware primitives for a smoother experience rather than a faithful replication of the PC's BSP renderer which made it slow. When brilliant guys like him are wrong, they often are in profound ways.
I would suggest that last line is both wildly indulgent and dangerous. Inventing reasons why someone being completely wrong is actually helpful is a level of freedom no one really deserves.
Someone being wrong almost always offers an opportunity for them or others to learn. If someone extremely smart is wrong, the gaps in their knowledge may point to interesting directions for the curious. Einstein was wrong to doubt the principles of quantum mechanics, but the conflicts with relativity he elaborated helped point the way for future physics work.
Of course, it's important to be right when there are consequences on the line, but being wrong isn't ipso facto something bad.
Really embarrassing to see Carmack fall so low and have such little respect for the art of programming he once advanced. Unlike swords and martial arts in combat, code is still needed. It’s not like there’s some new medium that doesn’t use code at all. It’s just a question of who is writing that code: a human or a statistical model. Guns superseded swords, cars superseded horses, but coding agents haven’t superseded code itself. A better analogy would be if, instead of guns, we ended up using advanced kung-fu fighting robots. Which would actually be sick…
It's interesting to see how over the span of just a few years a lot of people went from:
> Architecture astronauts are out of touch and shouldn't give any advice because they haven't written code in ages. Only the hands on engineers can shape it since the design evolves in step with writing the code.
To
> I focus on the architecture patterns and high level goals and let the LLM take care of the rest.
Similar commentary was shared about anyone not writing the code daily, not just the architects.
No gotchas, I just think it's something which calls for introspection.
I'm one of (if not the) original architecture astronaut, so you may not want to listen to me, but you're sliding from "architecture astronauts are bad" (true) to "architecture doesn't matter" (false).
Arguably, architecture is the only thing that ever mattered. Below the level of architecture you're dealing either with algorithms or API calls. Algorithms can be validated by tests and API calls can be validated by tests and the type system.
But architecture is the one thing that could make or break a project and that you can't test for ahead of time. You either know how to create a good architecture or you don't. In fact, the whole point of the Spolsky's Architecture Astronauts' essay is that bad architecture (and bad architects) are a big problem.
AI works amazingly well below the level of architecture, but (I've found) it's not very good at architecture.
I agree architecture is important. But I think the best way to design a good architecture is to have a high level plan, and then feel it out by coding parts of it (usually near component edges / interfaces) in the actual domain with real use cases.
That exploration helped me see whether general "best practices" are applicable in this frame, and let me justify if not.
That was also prevailing opinion pre LLM:
> Only the hands on engineers can shape it since the design evolves in step with writing the code.
So I'm curious to know where people changed their minds.
I think your argument is you can't create good architecture without writing code. I sort of agree. You can't be a good software architect without knowing how to code, and you can't be a good architect of a specific code base without being familiar with the code.
But I don't think you expect an architect to have written all the code, right? I don't even think you expect an architect to have read all the code.
The whole point of being a good architect is understanding the abstractions so that we can focus on the overall system without necessarily knowing all the details. I don't need to know the FFT math behind JPEG to integrate an image library.
So there's no real change in opinion. Architects were never expected write or even understand every line of code.
I think they are lying to themselves. The patterns change with the hardware and environment, i sure code different and use other data structures when having to account for VRAM now, network security, etc.
Going from the specification to the code is not a one way street. You adapt the whole chain. Saying the only thing that matters is the spec is squinting your eyes and hoping for the best.
You stop learning how things actually end up in memory, compute, storage and network this way. Not sure how you can build a secure and fast spec then.
And even if you do know i never understand why not typing it out. You can use a lib if you don't want to worry about these details or know you are not skilled enough (tls f.e. ...). But having AI do it introduces uncertainty where there can be determinism.
I think it's just laziness and people not liking the pain of learning or needing to show off whatever first. Who knows. Still don't see a reason to use these tools outside of learning or whatever i used a google search for before.
This resonated with me as someone who: has read the book of 5 rings (translated), has done quite a lot of martial arts and has been coding for ~50 years.
I work for myself developing apps and selling online. So I have no employer pushing to use AI. But I feel a bit like a dinosaur watching the incoming comet.
Currently, I just use MSCopilot as enhanced StackOverflow and I find it useful for that. But I have been nowhere near Cursor, Claude, harnesses, agents or 'vibe coding'.
It seems my options are:
1. Keep use AIs as an enhanced StackOverflow (e.g. to answer questions about APIs)
2. Embrace the new AI coding tools
Really not convinced about option 2. I don't trust AIs with code bases that I have built over 20 years. Also, I'm not far off retiring and I'm not sure I can be bothered to completely change how I work (again). Would be interested to hear what conclusions any fellow coding dinosaurs have come to.
My suggestion would be just to try it. Get an openrouter account, add 50$ to it and setup pi agent to use it with a cheap and fast model; I personally use 5.6-Luna.
Run it on a throwaway system, pick a codebase you’ve always wanted to fix something about but didn’t have the time. Like you wanted to do a major refactoring or do a library migration to a better maintained library. Or you want to rewrite part of a program in rust for performance/security improvements.
The hardest part for me is sometimes it is hard to write what I want in a prompt; but you don’t have to put everything into the prompt, you can make a code edit as an example and then say; look at this diff, it is doing X; look for and apply this some transformation across codebase Y
If you have a good codebase, AI will have good patterns to follow and will produce pretty good code; and you can quickly iterate on the results (maybe over new context windows) and get high quality code that looks very close, if not indistinguishable from the pre-existing code.
>Run it on a throwaway system, pick a codebase you’ve always wanted to fix something about but didn’t have the time.
Thanks for the suggestion. But I don't have a throwaway system. All 3 of my codebases are commercial software that I charge money for. Also, I don't trust an AI not to serve substantial parts of my codebase to a competitor. Maybe I will try it if I start a new project. I fancy a go doing some Webassembly graphics at some point.
>Or you want to rewrite part of a program in rust for performance/security improvements.
My code is battle tested and robust through years of use. I don't rewrite stuff unless there is a real need.
I was in the same boat around March. I started with Claude and giving it really specific instructions about what I wanted. That turned in to more interactive planning sessions where after we nailed everything down I said, ok just do it and I reviewed. The more I used it the more I let go of some things and the more I held on others. Now I have adapted my entire approach to use both local and cloud agents. Start small. Find what fits you. Also try out different models. Closed source is very strong, but you may actually prefer a bit less capable model that you give more direction to.
To effectively use AI-as-an-engineer as a seasoned developer, you must change how you work. It won't work otherwise. Your knowledge & experience wouldn't allow you to ship raw AI code, you'll end up being frustrated instead.
An alternative way is using it as a pair programmer, which is one step above enhanced StackOverflow.
There are two ways to do this:
1. Subscribe to ChatGPT Pro (or the 20x version) for just one month and use Codex to generate the system you want—whatever it may be.
2. Purchase a Mac Studio or DGX Spark and use the latest local models to securely audit your code.
that was truly, deeply, unnecessarily condescending of him.
it's so full of self-importance, even if he truly believes that whatever code he's writing is more important than anything else, it's really an unnecessary dig
especially coming from some guy who by many people is mostly known for his accomplishments in an era that many people would call retro computing now
sure I know this guy is almost literally the definition of the 10x programmer and he can choose to work on whatever he wants, so whatever he decided to work on is probably the most important thing to him, and if that's VR, that's ... also a choice.
doesn't mean he should be this condescending about what other people are doing
This post reminded me of the story about Jeet Kun Do [0] after Bruce Lee [1] died.
JKD was supposed to be a martial art that adapted the best techniques from other martial arts. e.g. "have no style" because your style is constantly adapting.
After Lee died, JKD broke into two camps:
1. "We should only teach what Lee taught us and no more. e.g. the techniques he taught us are the core techniques."
2. "Lee taught us to be constantly adapting from other martial arts so there is no list of core techniques."
I've always loved this story as it highlights how humans have essentially two reactions to change: embracing it or fearing it.
This is reductive to the level of the people misusing the Douglas Adams quote, with a sprinkle of false dichotomy. Fear and embrace aren’t the only options, and neither camp is entirely positive or negative.
There is plenty of middle ground which should be exercised. If anything, the reason we’re living in an increasingly shitty shit show shower is that too many people are too eager to selfishly embrace too much, with complete disregard for others or long term outcomes.
"as it highlights how humans have essentially two reactions to change"
I'd wager that the most common reaction to change is actually "wearily accept it as there is no realistic option".
Most change is deleterious to those affected; it requires them to change how they live or work, or pay more, just to maintain the status quo. This sort of change is usually imposed by large organisations against which the individual is helpless.
When people are faced with that sort of change it's little wonder they complain about it, but eventually they have to submit to it or face a degredation in their life or work.
Then those who imposed the change roll their eyes and say "ugh, people are so afraid of change," being insulated from and benefitting from it.
The next time you receive a ToS update from your $FAVORITEVENDOR that negatively affects how you do something, or a new tax filing requirement from $GOV that takes up more of your personal time, do come on here and post about how you embraced the change.
> But don’t be the out of touch Kung Fu master, heir to lifetimes of tradition, that gets mauled by an amateur MMA fighter.
I have an issue with this analogy, since a professional MMA fighter is a highly skilled individual who has honed their body through years of training.
A more apt analogy might be "don't be the kung fu master who believes they can survive an atomic bomb, dropped from far above by a pilot who does not understand how it works, but who has nevertheless been gifted the ability to deploy it."
Some context. Many styles of Kung Fu/Gung Fu do not spar in any meaningful sense. Consequently, they have an overinflated opinion of their own ability and generally do very badly against MMA fighters (who do lots of sparring and pressure testing). There are lots of videos on Youtube of Kung Fu 'masters' getting battered by relatively inexperienced MMA fighters. This was sufficiently embarrassing for Chinese martial arts that they created a sport oriented form called Sanda.
I once saw an early black and white film of 2 Chinese Kung Fu masters fighting in a ring. Some sort of grudge match I think. It was embarrassing. You would see better technique outside a Wetherspoons pub at 2am.
When you look at King Fu master as a software dev who refuses to use AI and MMA fighter as a dev who embraces AI.
Vibe coders who know nothing about software development are untrained rubes who got mechanical arm that thinks for itself, they can maul MMA fighter, they can maul Kung Fu master but at the same time arm might just rip off their own face.
That’s great for martial artists where the new arts are objectively better and more robust against the wider array of attacks one must withstand today.
But software…? He’s declaring victory at virtually every level but the highest. Who honestly thinks JS should be cemented as permanent? X86/RISCV? CMake? It’s cool to abstract away the lower tiers when our tools are this powerful but it seems silly to leave this much performance, readability, and extensibility on the table forever.
John Carmack is a personal hero of mine, so it pains me to say this:
Carmack hasn't produced anything noteworthy since AI was invented, therefore, how productive can it really be?
It could be he is doing incredible work in private... but it could also be that he's lost in the weeds, because AI is so counterproductive while feeling the opposite?
Again I don't get what people on HN are doing? Our client wants something: I mumble in my phone what they want, with some spec docs we had / made by mumbling in our phones: a working system comes out, we test it with our client, we fix. We sign a SLA, get paid 100k, a few weeks have passed. I mean, we should not measure everything in money, but for lack of a better measure for productivity, I cannot see how anyone finds it counterproductive. This was strictly impossible for our small team before recent AI and hiring more people didn't work for the pricing. Our profits jumped, revenue jumped, client count jumped. What are people here doing exactly that they are not riding the gravy train and even reporting all these negative AI experiences?
We do spend all our time either code reviewing or talking with clients but the latter was already the case and the former was just better spaced out over time as this would before take many months.
If it works for you, great! Just keep going. I only have the nagging question that if it’s so easy, why would the clients not do it by themselves? Certainly they understand their problems better than you and they can adapt to rising issues faster if their in-house team does it themselves. And certainly what kind of AI you can access, they can too and perhaps even more. So what will remain your value propositions?
I’m a critical user, not a categorical denier. But there are certain categories where I see the current AI face a wall: fitting new ideas, or existing code into an existing architecture particularly. Or work on the backend when constraints are not strictly enforced (for various historical reasons). Schematic understanding is still an issue.
Sometimes additional chunkings and detailed planning/instructions suffice. But other time, humans are still the best vehicles to code.
> nagging question that if it’s so easy, why would the clients not do it by themselves?
It's easy if you're already an expert at software engineering and know how to leverage AI. For people like that, it's a phenomenal upgrade (this is true for me and several co-workers I chat with, all of whom are chasing cool ideas on side projects). But if you're non-technical, or not use to thinking about requirements, or think that using AI is "give me the prompt", it's a pretty big moat to cross.
> I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
Plenty of reasons, including:
1. They don't (yet) know how to use AI to accomplish what they need.
2. The ROI is still meaningfully positive and they don't want to have to do it themselves.
3. Having a third-party do the work provides protection for decision-makers. If the project fails, the third-party takes the blame and "nobody gets fired for buying IBM".
4. The vendor does bring valuable insight to the table and pairs it with the use of AI to deliver a result that wouldn't have been possible in-house.
This doesn't mean that everyone will be able to get work and maintain their rates in AI world but some people will.
I recently tried to encourage my smart, technical, but not-programmer friend to build an app using LLMs and he was just like, "I still have no idea where to even start."
People talk a lot about how "real programmers" used to have to clean up or actually deploy everyone's half-baked MS Access app, and that sort of thing will probably still be the case for a while.
The whole point of the MS Access reference is that similar situations have been tropes since at least the 1990s. Bad code generated by someone who doesn't know how to program well -- whether that person is supposed to be a professional programmer but is incompetent, or has a different job -- is nothing new, and neither is having competent programmers clean it up. LLMs probably generate more of it, but can also fix a lot of it, or at least patch it up.
A year ago, LLMs were not useful for me as a programmer. Now they are: the models are better, they can use long contexts more effectively, and the harnesses are better at helping the models. Nowadays my job is mostly not programming, but LLMs let me organize and prepare tools in spare time rather than needing days or weeks of attention. I would not trust them on a 200k+ line project -- and Claude Opus 5 has issues even on 50k LOC projects -- but they absolutely can help given good direction and a narrow enough scope.
Then I don't understand at all what point you were trying to make about being miserable in our jobs. Cleaning up after bad code has always been part of the job for decades; so has balancing the creation of new technical debt against resource availability.
> The whole point of the MS Access reference is that similar situations have been tropes since at least the 1990s.
I do actually understand that.
I have done this very put the Access database on the web job myself. (FWIW I was well-paid for it and the firm I worked for earned a fortune, but this was in 1997)
I mean they've boasted[1] about their generated code being so good that they add basically zero value and that they're riding out the rentseeking for as long as possible.
Meanwhile they've apparently played with LLM porting of Postgres (or Postgres features?) and "would not put it in production"[2], so we can also guess the kind and scope of features being discussed here.
They're not "adding no value", the SLA is the value. I have a business problem, and I pay you to solve it and support your solution for me, is a completely different proposition than standing up your own solution as a non-technical org and maintaining it.
> They're not "adding no value", the SLA is the value
The code their Astra+Fable setup, automatically generated from requests customers leave in voicemails, is apparently so good they never correct it. If the stories being woven are true, the SLA is literally just a middleman's 100k cut.
At the very least there might be some particulars here that aren't universally applicable.
The second was just for fun; it is fun. This is very far from the code we roll out at customers though. We build LoB apps which are basically crud apps (they are not but most here would call it that).
We can have fun and make money right? Possibly at the same time but not in that case.
> The second was just for fun; it is fun. This is very far from the code we roll out at customers though.
Which is fine, great even (I do the same thing!), but in trying different things outside your day job, it seems like you do understand why people working on different things than you might be "reporting all these negative AI experiences"?
It's a pretty bad sign when you need to resort to this kind of comment stalking to try to find ammunition for a general argument. This user could be a complete con man, and it still wouldn't invalidate the core thesis of LLMs providing business value.
> you need to resort to this kind of comment stalking to try to find ammunition for a general argument
It's not a general argument, they made specific claims, but vague posted (and implying everyone else must be crazy) to the point that the conversation is derailed by a bunch of people trying to figure out what they meant.
> it still wouldn't invalidate the core thesis of LLMs providing business value.
lol, no, "providing business value" is not what was claimed:
>> What are people here doing exactly that they are not riding the gravy train and even reporting all these negative AI experiences?
> I mean it's weird that we all imagine reasons why we're still relevant when we have set fire to the thing that made us indispensable.
Very few things in this world are all-or-nothing, and not every purchasing decision is based on price alone.
Do you always buy the cheapest meal? Car? When you renovate your house, do you always choose the cheapest contractor?
Tons of developers will lose their jobs, and many more will find it hard to maintain the salaries/rates the industry has been accustomed to. This is already happening. The days where an average graduate from a run-of-the-mill CompSci program or even a coding bootcamp could sleepwalk into a $150,000+/year entry-level job are largely gone. The days where you have job security simply because you're a competent developer with 10 years of experience are in the process of going away.
This does not mean that there is no subset of developers who cannot be successful in this market. There are people who are doing just fine because they know how to articulate their value and sell themselves to employers or clients.
> If it works for you, great! Just keep going. I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
Because it's not (yet) that easy, especially if we're talking a complex and genuinely useful app. Agentic coding is fast, but it's not magic.
> I’m a critical user, not a categorical denier. But there are certain categories where I see the current AI face a wall: fitting new ideas, or existing code into an existing architecture particularly.
Exactly. Which is why Joe Average still will have little to no luck vibe coding anything serious or novel. You still (IME) need a lot of active guidance, still need to push away from dead ends and propose alternative algorithms, and it takes hundreds of prompts to go from concept to what I would consider beta. (But, this is just my own experience, and it's possible I'm doing it wrong?)
I don't think that really matters. I have already seen companies generating their own code and just QA testing it, with no software engineers in sight. Or they ask us to "review" their 10k loc PR in 2 hours.
The spirit of the parent comment is true. People feel like it's productive and even if they make something worse, they are going to use it.
Clients are starting to, that’s exactly why I am not sure why AI doom deniers here think this will think it will go well for them. But it will still take awhile and we are enjoying that time. If we see new markets, we will move into them.
> I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
I mean, that's exactly what's starting to happen, we have more and more clients to whom we propose a quote and their answer is "guess i'll just vibe code it" or come to use with an app that they vibe-coded and does the job, and they're content with it. So far it seems to work out just fine for them.
Ya, AI is very good at generating number, be that code for software, images for ads, or banal prose for company blogs. AI not so good at growing corn, cooking eggs, biulding houses, running fiber, treating disease, changing brake pads, loading a truck... or any of the other millions of physical-world jobs on which the economy is biult.
If you company is all about creating things that go on the internet, sure, AI is your thing. But for most companies the internet is a communications tool rather than a product. Those companies are not seeing the claimed productivity gains.
They sure are though; they have many processes to automate as well: big corn farmers/factories also have admin, erp, crm, departments with processes etc. There are companies doing billions in revenue with departments of people just copy/pasting PDFs who do real life things like you state who have immediate gains. But they won't do it alone yet and luckily need us. They still benefit though vs the large consultant businesses or even their own IT deps though.
Literally everyone I know in a large enough company who talks about AI talks about increasingly panicky mandates to use more Copilot coming from above, like you'll lose your job if you don't use it more. I heard exactly this story from my neighbour just three days ago. Literally a call from head office demanding they use Copilot more — to do a task Copilot can't do.
Everyone in smaller companies describes various efforts to get AI to do more that ultimately end up involving lots of corrections or nurse-maiding ChatGPT to get it to do exactly what they need, when what they need is often so formulaic they should already have a process.
Nobody I talk to describes it in terms of massive productivity gains. Everyone describes it as a puzzle they feel variously compelled to solve.
I can add a data point for you: At my job they have made "amount of AI usage" a criteria for performance reviews, advancement and promotions. Mandate from the top: Use as much AI as you can. They even have a leaderboard (accessible to managers) showing who is using the most and least AI. It feels as though nobody even cares how good or bad a job I do, as long as I do it using AI.
They do and there are certainly some mid-level management jobs at risk, but ask any farmer/electrician/millright about the claimed impact of AI and they will laugh. They have yet to see an AI capable of reliably replacing a fuse let alone doing a solid day's work.
Yes, agree with that, but that's usually not the sort of work we talk about here. But sure, robots are close there. All those admin jobs on the other hands...
> Our client wants something: I mumble in my phone what they want, with some spec docs we had / made by mumbling in our phones: a working system comes out, we test it with our client, we fix. We sign a SLA, get paid 100k, a few weeks have passed.
OK so, it sounds empty and miserable to me, but we can stipulate that this is how it is working out for you.
Given that stipulation: how long do you think this can possibly last, when you are in a race to the bottom with everybody else who is doing this?
Have you made plans about how you will get out of your office lease, downsize, subcontract this button-pushing to even cheaper people overseas, etc.? Are you ready to lay off everyone who works for you, downsize your house to a smaller mortgage? Because you're on a burning platform. If you can do this, so can everyone else.
I mean, I think we all are, possibly, on the same burning platform; I don't think I can fully avoid AI so I am trying to make sense of it.
But I intend to fully avoid being in a race with other phone whisperers if I can.
You're not just in a race to the bottom with everybody else who is doing this. I don't think his anecdote is particularly surprising at all. You can do the same with basically any typical CRUD app, which is already going to be some very large percentage of all business software. But this kind of also leads to the conclusion that so can the people paying you.
I think the years of software development/employment for problem solving, in and of itself, are numbered at this point. When people start to understand how relatively easy this stuff is, they're going to be in-housing everything. Not only for price but also because of increased flexibility/confidentiality/control, and even lower concept-to-live timelines.
What third party stuff continues to exist will see its comp plummet. I imagine now you can already get some really nice quality software contracted out on places like fiverr for nothing simply because the skill involved to produce quality solutions has plummeted.
I think it's a mistake to assume that quality doesn't plummet when cost does, even if the AI is capable of quality work. The quality issue will always resurface.
But yeah — I mean, I am a freelancer who burned out for reasons that are rather more influenced by the SaaS wave. That was hard to compete with. People choose between the solution that meets their needs and changing their processes to meet the ten-times-cheaper solution that doesn't, and that decision is often not at all irrational; by and large you want as many of your problems to be shared problems as possible.
I am trying to return to work so I am looking at what AI can really do for me, but the conclusion I draw is that since I cannot simply burn token money to solve people's problems, and because bugs cost me money, I need a strategy where I remain in full control of actual code, but LLMs help me do things faster. If I can't solve that, I am out.
Perhaps AI will upend the SaaS market before it fucks the freelancer market and the balance may temporarily shift. But it probably won't.
And at that point, as a fiftysomething, even with a bit of financial security, I start thinking about living a rather shorter, happier life, instead of a longer one. Because as much as I might have ideas, I don't think there is much I can switch to where I have appropriately deep skills to survive AI there, and all those alternative jobs will be oversubscribed and less likely to hire me.
I wonder if people in this industry have understood what we are doing to ourselves, to our friends.
A bit of a tangent here, but I'd look into lower cost of living areas if you have the ability to move/remote, even moreso if you'll be drawing social security or have a pension. Money just goes so much further, and with an overall much better quality of life. And there's always stuff like teaching, moreso because it's enjoyable than for the paycheck.
But in these parts of the world, making a few bucks doing whatever in the software world goes so much further. Because of that I think LLMs are bringing in something like a temporary golden age. And these parts of the world will be the last to have the lights go out on software simply because the low cost of living means there's a whole lot more slack to give before things get bad.
I am moving to somewhere cheaper, yes. Though since my passport is no longer strong (British), my choice/range of cheaper is a lot more limited.
Quality of life will not improve, because I will be lonelier (plus I have a great quality of life here in other ways, that many places cannot match) but I am mostly reconciled to that loss. I will have a fair bit more flexibility in use of space, which means I can be a bit more of a portfolio-earner; I do have some fringe skills that could make some money still, and I can have a little workshop or studio.
> But in these parts of the world, making a few bucks doing whatever in the software world goes so much further.
I am (undiagnosed but very obviously) ADHD and I don't tend to find it easy to make a sustainable income off "a few bucks" here and there; the effort expenditure in managing it always ends up subsidising the work. It's part of why I am burned out. I need thicker strands of work and those are fewer and further between.
I have little certainty when things will get bad, but I do think it likely it happens in the next five or six years, and I do know that when things do get bad they favour the young. Which I am not. It is clear to me that I am never getting an ordinary dayjob in the tech industry again.
I don't mean to sound particularly gloomy but I think mine is the generation whose lifespans will dramatically shorten. I think a lot of single middle aged people (men mostly) in the tech industry will choose the time and manner of their departure. Because we are deliberately creating both misery and job insecurity.
I don't think you're being gloomy so much as realistic. It's clear a lot of people either don't realize what's already happened, or are in some sort of denial about it. What you're saying is entirely true and was almost certainly also true during past eras of revolutionary leaps in technology. Fortunately in current times we have far more options than we did in the past, but realizing those options takes a bit of adventurism.
Since you already have that in you, I think you'll be surprised what you'll find - entire communities of interesting English speaking tech-oriented folks, many with more than a few grey hairs, would be just the start. And don't forget the teaching aspect. If you have a degree, smarts, some basic charisma, and can roll with a bit of chaos - you'll find plentiful opportunities to teach any topic imaginable. It's not just English, like many think. It's really quite fun!
I have taught/lectured the odd thing in my past and I can do it; I come from a family of teachers and it is in the blood.
I do not have the psychological constitution to teach kids so I am not going to do that.
But teaching/training adults is an industry that AI will destroy because the baseline income — the stuff nobody else wanted to do but you could earn from — will be eliminated, increasingly by policy directives from above. I have some ideas in that regard but it is difficult to see how I won't end up competing with LLMs when even open weights models are pretty good at coming up with tech tutorials etc.
Broadly I think there is undue optimism about what will be left to move to when the programming jobs dry up.
(Thank you for the discussion, though! I may sound quite negative but actually I am doing better than I have been for years, and it is always useful to provoke one's own thoughts)
Well there's a world of difference between teaching a 7 year old and teaching a 17 year old. I would say in both regards a more engaging style may be necessary than what you're possibly alluding to, so there is that. Depending on your background, teaching in a university is also completely viable. There's also the private lessons possibility. There's many options and I definitely wouldn't just write it off.
I don't think AI will touch education. A good case study there is Khanmigo which was to be Khan Academy's revolutionary AI tutor. There's been a million articles written about the topic. It completely failed, in spite of receiving massive sponsorship and imposition in various educational settings. And I'm kind of surprised that Khan himself didn't understand or predict this. As you probably know, great intrinsically motivated students don't really need teachers. You could give them a book or a sort of LLM tutor, and they'd excel completely independently. But then there are the other 95% of students you have to consider.
And those other 95% tend to fall into camps of either being a bit less gifted in the cognitive domain, or lacking motivation. Depending on exactly where they stand on the balance of two, a good teacher can have a huge impact, whereas 'go learn with the LLM for a few hours' would have them tune out instantly. It's because teaching isn't just about literally teaching, but about forming a rapport and trying to gradually push those 95% into more of the habits and patterns of the 5%, but without them realizing they're being pushed in that direction. An LLM there is almost entirely nonsensical.
Software is easy until it isn’t - the moment you need serious infra you’re in deep trouble and looking for an experienced partner or a saas solution anyway.
The days of b2b saas subscriptions doing one simple thing well for 3 or so users are however numbered.
Try getting something good out of fiverr or upwork. Even now it’s terrible (we get to clean up some the experiments). I agree maybe with the in house after enough years but that will also have a big effect on employees of those companies; a future (5+ years for sure as enterprises don’t move so fast) AI would need few resources to create and optimize and improve. I am not resisting my company won’t exist soon-ish; I am resisting that people see a bright future for devs here on HN. I don’t know where that comes from outside handwaiving ‘loom’ and ‘train’.
I know fiverr will start delivering nice software in 5 years and that’s what I worry about. By that time fiverr is probably just a chatbox though without humans, as what is the point?
The point is that button pushers currently simply don’t seem to be able to do this work, so it’s a little more than pushing some buttons. But no, I don’t think it will last very long, but few years more I guess looking at the competition and lack thereof.
What you describe does not sound all that much more than button pushing, TBH.
And your competition is not non-skilled people using AI to take your jobs. It is _cheaper people_ using AI to take your jobs. All the things that outsourcing teams used to struggle to match are much less of a struggle to match when you are actively depersonalising your own effort by handing it to Claude.
Don't underestimate the power of motivated reasoning. Certain people don't like AI coding for various ideological reasons, and so they will, not coincidentally, consistently fail to find it productive or helpful.
As long as we don't underestimate the power of motivated reasoning for other certain people as well, who like AI coding for various ideological or financial reasons.
I mean sure if long term maintenance and code quality don’t matter then I wholeheartedly agree with you.
It’s spectacular for small projects, limited-scope apps (eg marketing campaigns etc) and for market-testable prototypes.
But if you don’t review and edit the code, things become unmaintainable soup very fast, with subtle logic bugs all over the place. And if you do review and edit the code, when working in large nontrivial codebases, then in my experience AI doesn’t actually go faster even if it feels like that at the start of each task.
Obviously this only holds if you have any sort of code quality standard to begin with (and I agree that with small / short-lived products you don’t need one)
I'm currently working on porting a mid-sized project to a new architecture, new programming language and of course adding new features.
Getting a new feature implemented is quite easy. You spend a few hours brainstorming specs with the agent, then ask it to implement it. This gives you extremely frequent code drops that add a new brick, add a new feature, etc. All of this with 100% code coverage (we also have mutation testing, strongly-typed code, standard and custom linters, etc.)
Then you look at the code. Code that has passed review, generally. You realize that the database schema has been broken silently, and that the agent has rewritten the tests or the golden fixtures to match. You realize that it has made assumptions that contradict the specifications and the product is going to break once it's in the hand of users. You realize that the 100% code coverage is essentially a convenient lie, because the code and tests have been written to make passing easy. You realize that none of the security golden rules have been followed, and that has managed to happen because the agent has somehow deactivated linting.
Why did it pass reviews? Well, because of deadlines. And because there is simply so much code (and so much unparsable/misleading documentation) that it's simply impossible to review all of this. And because things move so fast that nobody understands the CI pipeline anymore, and the explanations of the agent are convincing enough that surely, it knows better than you?
On the upside, bugfixing becomes so fast! Just add a new test, wait a few dozen minutes, and a new Merge Request appears. With equally convincing/misleading explanations, and something else broken.
After ~4 months, we had a bare bones deliverable, which we're now steadily expanding. If we had had to write the product manually, I suspect that it would have taken us at least one year, possibly two. So, that's the productivity increase. The productivity decrease is that what we have is not a product but a glorified demo, something that will work very nicely on the happy path, but on any other path, all bets are off.
Thankyou for putting the last three months of my life into words <3
> and the explanations of the agent are convincing enough that surely, it knows better than you.
I feel this in my bones. I also get to watch the misalignment feedback loop close itself when the next agent sees that security rules aren't followed because of a hallucinated 20 line justification in a code comment, and then it decides that the project _is_ a demo and then confidently writes even more security holes into the codebase.
Then when you catch the issue, the agent pushes back against the fix because it would need a schema change and production DB migration.
> Then you look at the code. Code that has passed review, generally. You realize that the database schema has been broken silently, and that the agent has rewritten the tests or the golden fixtures to match.
I find that the code review leg of this is critical to invest a lot of energy into hardening.
First is don't trust the code review from your local harness, even if it uses sub-agents; externalize it into another system.
Second is to get your most critical human code reviewers to encode their heuristics in markdown files and feed those to the code review agents.
Third, if possible, is to bring the code review "into the loop" so that it's not only running in the PR, but also running in the coding loop so the coding agent has immediate, external feedback. Final PR code review is a backstop.
This pattern [0] works well because it solves for some team level problems where folks are using different harnesses or different models (consistency issues) and it means that code reviews don't just sit at the end of the loop; it actively alters the code production cycle.
In my experience, they are fairly good at catching stuff in human-written code, but they tend to gloss over agent-written code, just as human beings being lulled to complacency by superficially-looking competent code.
> "Why did it pass reviews? Well, because of deadlines. And because there is simply so much code (and so much unparsable/misleading documentation) that it's simply impossible to review all of this. And because things move so fast that nobody understands the CI pipeline anymore, and the explanations of the agent are convincing enough that surely, it knows better than you?"
I have come to realize that AI is so "successful" because the system in which it is being deployed was designed to push product as fast and cheaply as possible from the start.
Humans are usually overworked and stretched to their breaking point, which I originally saw as the source of our broken software woes, which, like our streets in the US, just get a new layer of asphalt to cover up the crumbling bits each year instead of rebuilding the infrastructure with reliability and longevity in mind.
My former employer was using both Claude and Codex for firmware that was driving an over-burdened power circuit that itself was partially designed with ChatGPT. All of the individuals involved approach LLMs with god-fearing reverance because they do not understand _how_ the LLM works, just that it _does_ in a "good enough" way and they can offload their thinking, which is something we all wish we could do because thinking is hard, time-consuming and costly. I get it.
But like you mentioned, tests were being passed, not because the code was sound, but because the tests were altered to match the results. This is not necessarily the fault of the agent, either; it's just interpretting the prompt(s) - written by a flawed human, btw - with stochastic mechinations that seem to make a great deal of sense on the surface, but remain unable to be followed or repeated by the brains of (most of) its users.
As a rresult, I had to deal with product that work great in the field...at least at first, before it start literally catching fire, ruining its own powertrain because everything the agents touched became too complex with too many subtle cracks in the veneer to review properly. The system (read; capitalism) demanded viable product quickly to please investors, and the burnt-out humans who decided to try this AI thing ended up trusting it nearly completely, so any ideas of repeatable and complete testing, diagnostics and root cause failure analysis morphed into a sloppy "it works on the bench" checklist before being sold to a customer who had come to trust that their deceptively simple product would just work as advertised.
I'm going to die on the hill that AI as a replacement for our brains is precisely how we will make ourselves go extict, but I am old enough to already be regarded as a crufty dinosaur who is stuck in his ways, and I'm made peace with all of that. What I can't get my head around is watching people use this awesome tool (and it is, admittedly, awesome) to literally just speed up all the mistakes they were already making. Perhaps it is because I am aging, but slowing down and having a think seems more valuable to me now than it ever has, especially when creating something new. AI is powerful and, like any good tool, could be useful in the right hands, but more often than not I see it being used as an accelerant for all the worst parts of product development to appease a market that has suddenly been told they can now pick all three points on the Iron Triangle instead of just two. This makes about as much sense to me as taking a laxitive when you already are suffering diarrhea.
AI amplifies existing process. For people without sufficient clarity I imagine it amplifies that lack of clarity, which is where it is factually unproductive while it still ‘seems’ to be productive (producing slop).
Yeah, that gives me the scary feeling that especially here people are overvalueing themselves by a lot. They find AI counterproductive because they simply never were good at what they do before AI. This is always always my read of people who value talking, meetings and office time as important: I have never met people who have that and who are not sales or just plain suck at their job; AI amplifies that. Also with salespeople who now send me presentations that just have a bucket loads of hallucinations in them: turns out they never read them but had interns write most of them: now they still cannot read and AI generated stuff looks plausible. I only have anecdotal experiences but this sure seems to resonate for the AI negativity around here. I could be wrong but it's so far removed from our experiences.
You don’t value “talk”? I understand. I have a lot of those around me and they are super productive, all day, alone, in their little cubicles. Oblivious to everything around them.
I don’t know what to say to those types anymore. Live and let live I guess.. or in this case, not live I suppose.
It usually is more like; I send an email or so which contains enough details to understand whatever we are doing. A person in that list sends it to 20 people. The next email is a zoom invite with 30 people of 1.5 hours to ‘go over the email together’. If these people have no influence, good or bad over the outcome, why would I waste this time while it usually just says they were too lazy or incompetent to read the email?
Useful talk and meetings all day is fine, but these are just to write busy/billable hours for all these useless folk with no value for the project. And socially I like listening and talking, just not for this.
> For people without sufficient clarity I imagine it amplifies that lack of clarity, which is where it is factually unproductive while it still ‘seem’ to be productive
Convenient way of saying "you're holding it wrong".
I get flamed here whenever I say it's a skill issue, but it absolutely is. Not everyone has what it takes to be a successful CTO but that's the role you play if have 20 agents working on something you designed. I see you got downvoted too.
It would be a skill issue if someone would show they’re able to use it to produce good software while showcasing that it’s due to their mastery. Till this day, I don’t think there’s any such demonstration. Any defects of the technology is always blamed on skill issue.
There's a ton of people out there in various unknown companies grinding away and managing a reasonable number of well-prompted, parallel agents with decent CI and deployment strategy making judicious use of human review.
But that's boring and you can't build a YouTube audience around it.
What had he produced in the years prior to AI getting good enough for coding? All I know is he was on Zuckerberg's sinking metaverse boat for years, and then nothing else.
Maybe it's him, maybe it's his employer. I don't know. I am skeptical of AI's impact on work myself but I just don't think AI is the only thing to blame here.
Oculus was pretty fun and a really nice piece of hardware. What was painful was all the meta things on top of it, which I doubt was something he personally added.
> Carmack hasn't produced anything noteworthy since AI was invented, therefore, how productive can it really be?
He's been spinning his wheels for a while. Carmack is a great example of how important working on the right stuff is. He's undoubtedly a brilliant programmer. Through him we get to see that a brilliant programmer working on non-programming tasks, can produce nothing.
Carmack hasn't produced anything genuinely noteworthy after leaving id software, if we are being frank.
His work at Armadillo aerospace was more akin to hobby, not really leading anywhere, a VR stint at facebook, again, is difficult to gauge at how large his personal contribution was, and this new AI thing is likely end with him leaving the company, again.
Carmack is an amazing engineer, a genius even, but either the age of the individual contributor creating the entire thing from the ground up is over, and he's bored of it, trying to find a niche where this still works, or he is exploring the areas in which to apply his curiosity.
What I'm saying is that his current productivity or lack of thereof isn't a marker of how AI is productive (or not) in general
Its very different living in the late 80s to early 90s coming up with cool ideas that push affordable hardware to their limits just like John Carmack did with games like Keen, Wolf3d, Doom and Quake.
It was at an era where someone good at their craft can get the recognition they deserve. However, while some things he managed to figure out himself.. other things were ideas from others. He simply tried it and reviewed the results!
Looking in the games industry today - an 'individual' is not going to get the same recognition like John Carmack back in the day (or Ken Silverman, etc)
This industry is LARGE. Any god-like programmer trying things within a large corporation is not likely to get noticed today as they hide away in the background pushing an in-house games engine forward. I am sure there are a fair number of John Carmacks out there. Invisible... nameless legends pushing things, etc.
As for indie companies - why risk trying to be a 2026 version of John Carmack when Godot, Unreal, etc, exists. Its a different world today!
Same thing for AI. I bet there have been some legendary programmers working on AI in the last 10 years. Again, nameless individuals behind the brand.
If any names are mentioned... its likely CEO's or other higher ups... not the talent underneath. I guess thats good business strategy and works [for the business].
Focusing on John Carmack - I am not taking anything away from him. He is a legend. I am sure he contributed towards VR before and after Meta purchase. With AI.. I guess we will see.
At the end of the day the guy could walk away and focus on hobbies. Still has a lot of batteries left. More power to him.
Actually, I'd expect someone like Carmack to be the least productive with AI. Carmack focused his career on high-performance 3d graphics tricks. Those are free now. What isn't free is knowing how to use them. In other words, the game engine is free, the game maps/zones/levels are costly. The "John Romero" part of the equation. Let's see what the idea people are making, not the code gurus.
That AI still hasn't made my effort and thinking and directing and checking and ideas completely redundant and thus out of job?
It's like you people see everything in black and white and miss that most of the real world is a gradient of shades of grey and quite never full black or white.
> It's like you people see everything in black and white and miss that most of the real world is a gradient of shades of grey and quite never full black or white.
I’d go even further. Shades of grey implies two extremes on a linear scale, but the world has colour, meaning wildly different interpretations that go in novel directions.
However, ironically, your comment reads to me as extremely black and white—full of certainty, rigidity, possibly some bad faith interpretation and straw manning—while the one you’re criticising has (some) nuance and doubt and seems open to the idea of being wrong.
What complain? OP asked a question. Carmack created Doom, Quake in 2, 3 years. What has he created in 4 years of AI? Should be exceptional if one of the most productive programmers ever says it makes him more productive.
That reminds me of something on my last job. Before AI, we had not so good communication, but if we had a question, the person on the other end will try to give you a passable answer. After AI, everyone seems to be a proxy for the LLM tools they're using and any misleading statement you point out is answered by "Why don't you use $llm_tool to check it out?".
You're comparing the challenge of building game engines in the 90's with the more open-ended AGI research. It's different enough that I don't think it's valid to conclude he's less productive now based on impact over time.
I'm a practical optimist. I see us as being in the age of engineering for AI -- like the early days of the steam engine. We're going to get a ton of things wrong and impractically implemented. But we don't anticipate the train conductor to build the steam engine on their train -- we just expect it to work as targeted.
(Note I'm not being pollyannish here -- a lot of codegen downright sucks).
Sure, among all these other people doing 'incredible work' for 30+ years publicly, well into their 50s, John Carmack sure is a disappointment by comparison.
I sense sarcasm. But I think you misinterpreted the parent’s point. I read it as: yes, Carmack has made huge contributions but, has not publicly released anything noteworthy since the advent of AI coding. Of course that doesn’t mean he won’t, just that so far nothing he released has backed up his statement.
Can you imagine a football fan going up to Ronaldo and saying hey, I saw an interview you did last week - I think you may be lost in the weeds there with your training regimen and outlook. I want to let you know - I remain a skeptic.
I mean, when you start scoring goals like you did 5 years ago Ronaldo, but until then, I remain a skeptic about that training regimen.
As for misinterpreting - maybe you're misinterpreting. Or maybe it's unproductive and dare I say presumptuous to reply to people you know nothing about with 'you're probably wrong and I'm probably right'. Do you do that in real life? Working out great, I can only assume given you've adopted a similar approach here, or?
Do you believe a 50 year old software engineer is mentally no longer able to work?
Should they be forced to sit back and tell stories of the good old days because their knees are blown out?
Do you believe that one of the greatest living programmers is so washed up at 50 that _even with the greatest LLM tools_ cannot ship something publicly in four years to back up his claims?
I would rather listen to someone with current merits than someone who has not produced anything notable in years. Especially if the topic is current trends in software development.
I mean his post boils down to "Get on the bandwagon because you might otherwise miss out. All the cool kids do AI now."
There are valid concerns there (and you should probably be playing around with LLMs), but he voiced none of them. He just led with a metaphor about obsolescence and then continued spreading FOMO with an authoritative voice.
Perhaps he is actually lamenting being the out of touch kung fu master, but his pride won't allow him to articulate the ways in which he identifies with that?
Edit: Had to re-read a bunch of stuff about Musashi, and to Carmack's credit, seems to have been a relatively pragmatic guy when it comes to the choice of weapons in a battle, talking both about the benefits and drawbacks of firearms (although they were slightly different ones than we have today)
In particular regarding free as in freedom, so about access and control. Just like I never enjoyed working with proprietary coding platforms, OS, or IDEs, I’m not particularly excited about proprietary models.
Check out DeepSeek v4.1 Flash, just released, and I am enjoying it more than Claude.
No one can run it locally.. Yet.. But give it a few years and I wouldn't be surprised if models of that capability were standard for programming laptops.
We don't know the training set so it's still not very transparent - and means giving away some control. Then again, it does look better than closed weights
Fighting is competitive and single-minded in a way that programming very much is not. The purpose of fighting is to defeat, often kill, an enemy who wants to do the same thing to you. In that world, there’s no room for anything but the most advanced techniques and technology.
Most jobs, programming included, aren’t like that at all. There’s an element of competition, but you don’t get killed by somebody who does it better. Maybe they get paid more, but you can still have a job too.
I read this advice like: in a world of backhoes, don’t be a guy with a shovel. Except a guy with a shovel is still very useful in the modern world. Backhoes are great but can’t do everything. And even for jobs they can, the shovel might be good enough.
It does say something about our culture, doesn't it? That something as mundane and non-violent as computer programming gets compared with violent combat.
I suppose it comes down to how hyper-competitive some people are, particularly the "greats", that working on software is in the same category as fisticuffs.
Because someone profits from it. If your man had truly embraced Zen after, y’know, becoming wealthy enough to never need anything, it feels like freedom from want would have come pretty easy. Instead we have to find our examples in poor people after they die.
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It's funny, but to relax I was reading Tim Berners-Lee's FAQ for kids. He has a section about "I'm interested in Math -- what exciting stuff is there we don't do at school?". He quickly sketches out what ideas might get us to Maxwell's Equation, ironically enough. But, what a joy it is to see a person who believes in the public domain, and who we have everything to thank for right now, saying "The main thing is, to have fun."
There is a purely strategic reason for keeping some hand code skills exercised. If you outsource the coding away completely you become dependent on entities that can pull the plug on you. Not arguing it's the right choice to rein in the agentic coding just that there is some rationale for doing so
> The introduction chronicled the evolution of swordsmanship and martial arts in general from pragmatic battlefield necessities to sports, historical curiosities, and hobbies.
Eh? Martial arts has always been a mix of utility and cultural artifact.
Greco-Roman wrestling flourished in a/alongside of military utility. Greeks and Romans had swords, shields, spears, bows and arrows. Boxing also traces its history all the way back to the Greeks.
Japanese, Korean, and Chinese arts developed in a society with, also, swords, shields, spears, bows and arrows. Notably these cultures often included weapons training ("kobudo" in Japanese) in their curriculum but that did not phase out the empty-handed aspect of the art.
Catch wrestling developed among sailors who would not be strangers to guns and rifles.
BJJ developed, well, today.
There has always been a component of sportsmanship and self-improvement in martial arts. Carmack misreads this introduction, methinks.
I don't think with the models we have, you shouldn't need to even write a single line of code. What you need is to prompt it right, check for over engineering, check for edge cases, test it very thoroughly. That means don't accept it writing 10,000 lines of code that you cannot review or test properly. Make modules small enough that can be reviewed/tested properly.
I like ai, with IT i can Program again, after being Out of Touch with it for some years. I can Focus in the Thing i actually want to do instead of setting Up 5 different ENVs only to find out that the Framework only works with an Intel processor
Shut up and show us the code, Carmack! Now that you take AI money, you are a hollow influencer.
BTW, for you it would have been pretty bad if coding had been solved in the Quake-3 era. Quake-3 was technically sound but had excruciatingly boring and bland gameplay.
Is there a name for this pervasive psychological phenomenon where someone reads an ancient text and becomes convinced of its profound relevance to their own field? Seems to be especially common amongst the influencers of the tech sphere.
Yep. Having to type the code is a form of accidental complexity, and with it gone, you can focus more on the problem to solve, getting it down faster.
Of course it's possible for it to go off the rails. Consider that a wildly swung sword can do damage you can't do with your bare hands. To prevent this, constrain your model to the solution shape you want by grounding it; give it contact with reality; ways to run the code it's generating and refine it to meet your goals; granular tests; etc.
The new job is in how you wield the tools and it is at least as complex as the old.
I guess in ten years we'll see which is the out of touch Kung Fu master.
I do see a whole set of people doing mystical passes in the air, sometimes with wires holding 'em up, in a set of ritual beliefs propped up by vast accumulations of power, money and pride, not to be questioned.
Didn't expect Carmack to be among those waving his hands about.
If it's so amazing, let's see the amazing thing he does. Go ahead. I'm sure Doom needs a really on-point web page with Inter.
Why is Carmack still someone we look up to in the present? I'm aware of what he did in the past but compared to the likes of Torvalds and Bellard he doesn't seem to still be doing anything noteworthy other than yet another AI company.
My problem with AI is not that they aren't useful, John. Like everything else in life the question is what we shape ourselves to be as a culture, as a community, what is the path we want to take. It's not on the same scale than ditching assembly instruction for a C compiler.
I get why most people get with the flow of what competition taught us: if you can't fight them join them. Yet I think it's demoralising we're forced to live the life forced upon us by a few techbros without real collective intelligence about the use of our resources and goals for the future. Again, it always has been a bit like that but never at this scale.
It would seem that the AI craze has shown a flaw in stereotypical "software engineers": an obsession over quantity and speed over everything else. A desire to belong to the group, a desire to exhibit the fact that they are not being left behind. While FOMO is a thing for all peoples, those in tech are particularly susceptible, given the nature of the field.
I have yet to see evidence that AI produces code that is higher in quality than human-written code. I have yet to see anyone show that burning through tokens is economically smarter than paying human engineers. All that is being revealed is how companies and software engineers truly feel about the work they do.
This technology is impressive, and we cannot doubt this. However, it seems that those within Silicon Valley are desperate to showcase the innovative spirit which has been absent for two decades.
I agree with you wholeheartedly; I was just talking with one of my friends yesterday about this. I don't think AI is causing most of the problems we are discussing, it is simply exacerbating them to such a degree that they are hard to ignore.
yes, regardless how one feels about "ai", its obvious to me its basically gasoline being dumped on this "faster and more" culture we are all suffering from...
If so… Very poor choice of metaphor. Nothing resembles AI coding quite so much as the mystical master waving his hands in karate-style movements, seeing dozens of his opponents helplessly bowl themselves over, and eventually coming to believe he truly has the power to defeat any enemy.
If I still edited videos I would have “make no mistakes” fly out of his hands, and the students would have little “you’re absolutely right” and “that’s on me” captions on them as they flip themselves over.
The author of the work that John Carmack is referencing is named Musashi, which is also the (coincidental?) name of a WW2 Japanese Yamato class battleship, which is quite fitting. Musashi the battleship having met its end at the hand of carrier launched aircraft, which remain a dominant technology to this day.
Aircraft carriers are to a small extent superseded in their own right by strategic bombers and ballistic missiles. We may see nuclear aircraft carriers eventually superseded to some extent by missile/drone swarms and missile/drone deployment platforms, or some other threat.
If the new dominant technology, military in the sense of being used to dominate your adversaries in any arena, relies on data centers, is that infrastructure considered pretty robust? Will that data center infrastructure fully supersede the nuclear powered aircraft carriers, as has been done to battleships? Do hardened data centers and the software they run represent the main locus of national front line capability? Are AI researchers more like WW2 pilots, or are they more akin to the people who worked on the Manhattan project?
This post makes me think harder about physical computer infrastructure. Continuing the metaphor, silicon fabs, computer manufacturing supply chains and their related infrastructure are certainly the WW2 drydocks of our modern conflict, the WW2 drydocks having been critical for the Americans to churn out aircraft carriers. And the drydocks were only one piece, but might have been considered one of the most brittle.
Some seemingly brittle pieces of AI/data center infrastructure today are the fabs and the communication links. As far as I know, the fiber optic cables connecting continents are so exposed it's almost ridiculous, the cables lay directly on the ocean floor. If severing these links favors one or another global actor, my main question is why hasn't this already been done? You can ask the same questions about severing oil pipelines and the various global shipping chokepoints. I do wonder if fiber optic cables are defensible at all in the final analysis. And what life would/will be like without fiber optic connection between continents.
I'm not sure how much more durable satellite links are, due to the cascading debris effects of Kessler syndrome.
A key idea is that if the transoceanic communication links between the Americas and Eurasia were to be cut, either powers based in Eurasia or a power based in the Americas would gain an advantage.
Semiconductor fabs... Well, if I were a military strategist in charge of national security, I definitely wouldn't publish the location of every fab. And a a self respecting superpower wouldn't leave its EUV machine production external, or would it?
Fabless semiconductor companies and AI researchers are critical to current national security capabilities in the way that people who developed radar were critical to WWII. In the long enough term some people think that eventually data centers and the software running inside will supersede and encompass these functions. The question being increasingly not if, but when. Some people think that if it can be done by a computer, it eventually will be.
It really is all about timing, the Japanese thought the Pacific conflict with the USA would be short.
John, if the introduction of the translation of Book of Five Rings is so good, could you please share the identifying information including the translator or the person who wrote the introduction?
It's a good analogy that's probably occurred independently to a lot of us. Here's my version from a private email a few weeks ago:
> [...] I don't like the "great equalizer" effect. [...] Like a kung-fu expert who wandered into a wild-west saloon of drunks all packing six-shooters. (I'm still working on this metaphor.)
Might as well share the entire off-the-cuff email, replying to a great software engineer friend who recently went academic, when they asked what I thought about AI development.
> "You're absolutely right," as the chatbots say.
> I think Claude Code (which I think is currently regarded as the best brand for software development) is for banging out *something* when you don't care so much about the quality. Like most applications of generative AI (homework cheating, customer service, usual corporate ticket-closing).
> And I'm definitely not thinking through the problem very well. The first time I noticed this was on UI design, where Claude would emit a generic *something*, and then the mode is to make incremental tweaks, rather than going through the mental exercises and holistic thinking.
> So sometimes I'm thinking like a non-technical manager, giving initial spec, and then iterating on things I notice -- not thinking like a designer, architect, or engineer.
> Or, like a senior engineer who has to mentor a hyperactive intern who bullshits and plagiarizes like crazy, and makes empty apologies like a sociopath when caught, but is the CEO's nephew, so you can't just fire and blacklist them. You just have to get *something* out of them.
> I can do much better design and better implementation myself, but it's good enough. And it's better than at least half the industry software engineers, so a lot of people who never cared much nor got very good, are in trouble. And management is often a poor judge of skill, if they even care.
> Besides the questions of its performance and utility, and all the ethics questions, I don't like the "great equalizer" effect. Now a lot more people can do (or seem to do) many of things I can do. And I'm having a lot of trouble job-hunting, and companies mostly want people to be using or building AI. Hence learning the robo-plagiarism tools. Like a kung-fu expert who wandered into a wild-west saloon of drunks all packing six-shooters. (I'm still working on this metaphor.)
That conversation might've started when I showed friend my new gen-AI portfolio site, so the context would be realist assessment and handling it, spoken to someone who already knows I'm an enthusiastic hardcore engineer.
I mean, there is still a place in the world for a Kung Fu master… it’s just not as someone trying to win in an anything goes combat competition.
If you think there are going to be as many jobs in the future for people writing all their code by hand, I hate to break it to you. However, there will still be some jobs, and fewer people who want to do it. It will still be a path for some people.
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HN is loaded with out of touch Kung Fu masters. They were the loudest skeptics against AI. Still a lot here.
It's human nature. If your identity is defined by your kung fu and a technology is about to obsolesce your kung fu, then all logic goes out the window as you go all out in protecting your identity. It's mostly for themselves. They have to lie to themselves and tell themselves that they still "matter".
I've been doing martial arts for more than 20 years, some in TMA, some in modern boxing/kickboxing. I have yet to meet an "out of touch Kung Fu master" in person. Nobody thinks they can clear the bar or win in a ruleset they haven't trained for. I mean I don't deny Frank Dux, George Dilman, and the DUST guy exist, nor do I support their claims. It's just that they are larger-than-life personalities to start with and I haven't met them in person.
Similarly, most of the programmers skeptical about AI---me included---don't really do so out of a threat to a domain we've mastered. The problem is, models, to this day, need supervision so they understand requirements, so they know where to properly look for prior art, so that they "understand" the existing architecture. That includes you, Claude. Our kung fu has been six months away from obsolescence since roundabouts 2022 and in 2026 they even rehired a bunch of out-of-touch kung fu masters.
>It's just that they are larger-than-life personalities
That is a very generous assessment of Frank Dux and George Dillman.
Dillman at least started off as the real deal. Dux was a total fantasist. I still find it hard to believe any bought into his 'blood sport' story, let alone made a film about it.
People who are out of touch don’t know they are out of touch. Thats why you haven’t met one. Because they all declare themselves as relevant. And this is also why you can’t recognize yourself as out of touch.
How do you recognize someone who isn’t lying to themselves? It’s hard. There’s no definitive answer but lies people tell themselves tend to be rosy and comforting. When someone tells you their own identity has been eviscrerated by AI that’s not a comforting lie. It’s more than likely a practical analysis.
It's funny that we almost agree except you have it 100% backwards.
The out of touch kung fu masters are all retired or close to it. They continue to shout about their big bet on AI as loudly as possible to protect their egos and, as a last ditch effort, whatever money they threw in.
After all, everyone who is mid-career and younger cannot possibly be a master of anything. Of course they're using AI at work, but that is an extremely far cry from the AI actually helping. They use it because it's shoved down their throats and they don't want to rock the boat. Working extra hours from home is the perfect way for everyone to save face.
In other words, the older generation is delusional. Nobody is surprised except the older generation.
I never commented on age. So we are actually in perfect agreement. Yes, older people tend to have their identities and expertises ingrained. They have more to lose in terms of identity.
I honestly feel personally attacked by this and I don't consider myself to be an out of touch kung fu master or technologist at all. It is just very odd to read such an inflammatory comment on HN and then have people pretend this is correct and perfectly socially acceptable to say.
Like put your shoes into the person you are arguing against, with some empathy, would you want to be treated this way?
You feel attacked? I’m only referring people who are out of touch and lying to themselves. If you’re not doing that then it’s not you.
Unless if you feel it’s referring to you then you’re saying what I said is true. If what I said is true, then it’s not an attack is it? I’m just spitting facts. So don’t get offended, don’t think of it as an attack.
We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
I love being able to quickly bring out the program that is already running in my head without having to worry about the grind of typing it into a format that the compiler understands. Dealing with API names. Syntax. Language quirks. Library gotchas. A sizeable portion of my successful career as a software engineer was spent on the tiresome process of interacting with a text editor/IDE to get a program to do what I wanted.
I was there when people were still coding assembly. A slow torture where the simplest things took forever to get right.
Once I've mentally solved the problem, the fun is mostly over for me. Pure vibe coding is dull and unsustainable with current technology for all but the simplest systems; AI-assisted coding, on the other hand, rekindled my passion for computers.
I like your constructive outlook and I want to believe that we can now focus on the bigger picture, but I'm not really seeing it around me. Most everyone I know that's "AI-pilled" has spent the newfound capacity on throughput instead of altitude.
Is anyone actually seeing a shift towards improved structure rather than more code, faster? We seem to be living in the Gatling-gun version of the picture John Carmack drew when modernity also ushered into precision marksmanship...
The people who are using AI to improve what they were already doing anyway, aren't going around expounding "I made this with AI!"
Like one of my personal projects is a sort of "middleware" for Godot, and it needs to be lean, precise and match certain rules, because it's meant to be used by many games, so I can't blindly trust AI to generate code for it, it'd be too sloppy,
BUT Codex reviews have been a great help in finding bugs that would have taken me ages to even notice on my own. Some of those AI findings helped me overhaul entire subsystems, still manually coded.
I feel like using LLMs as a sort of deep search to find bugs and security issues is going to end up relatively uncontroversial all around, if the externalities of LLM use are ever taken care of.
I use vibecoding to capture UX. It's the best way of capturing requirements I've seen so far. Then once it's all captured and dies down towards requirements that are all in the "could have" category of MoSCoW, then I use AI-assisted coding (and the fun task of reading tens of thousands of source code lines) to refactor or create an entirely new application that is more technically sound.
I'm making full-stack applications at the moment.
Miyamoto having an assault rifle doesn’t exclude 19 year old cannon fodder also having assault rifles and spraying them liberally to little effect.
Are those people working on products or platforms? Platforms still have to be rock solid and deliver performance guarantees to the products built on top of them.
>> Is anyone actually seeing a shift towards improved structure rather than more code, faster?
Yes. At work we recently finished a complete rewrite of the platform. The old codebase got abandoned and two new codebases got stood up. Previous stack was Phoenix LiveView and the new one is Phoenix API + Vue /w TypeScript. Zero code shared between the two. We took the opportunity to re-architect a lot of the core functionality and get rid of the tech debt that had been hounding us and killing our velocity for the past six years.
We finished the rewrite in two months. A little over 700k LoC total. 95% of it was planned, orchestrated and written by AI. We could have gotten it done faster, but we were well aware of the potential for slop and thus paid an absurd amount of attention to (and tokens for) code quality. For example, there is a 100% test coverage requirement in both server and client, combined with AI-driven review rules that say all tests must be non-vacuous, plus a ton of invariants enforced via deterministic checks. Everything from standard linting and formatting rules to AI-necessitated stuff like "comments cannot be more than five lines each" is in there. At the end of each week, we get together for ~30 minutes to review each bug that was fixed that week (there haven't been that many) and try to figure out if more deterministic checks can be added (or new ones extended) to prevent that class of bug from re-appearing. We actually have an Architecture epic with a dedicated Fable agent orchestrating all the initiatives and tickets in it and keeping track of improvements (and the occasional regression). So things like accessibility, usage of shared helpers, enforcement of common patterns, etc. are all kept track of.
The difference between the old codebase and the two new ones has been night and day. The new codebases, combined, are ~35% larger than what we had before, and yet there are way fewer bugs (we actually got suspicious at first and had to check to make sure our logging instrumentation was configured correctly). Performance is also stellar, features have been a lot easier to add and extend, and everything is a lot easier to find. When someone asks a question or has an issue we have a pretty good idea of what part of the codebase to look in and we're usually right.
It wasn't all unicorns and rainbows. Not everyone on the team was proficient with AI-driven development, so they had to be brought up to speed quickly and taught the tools and also what works and doesn't. Code reviews were also difficult and time-consuming. We had to deal with our anxieties about working in two new codebases none of us had authored much code in ourselves. What made all of it worse was that we were racing towards a deadline imposed by external factors so we all ended up working a lot of hours. It was essentially between getting it done this summer or waiting until next summer and we bit the bullet and did it. It absolutely would not have been possible without AI.
That is interesting, but... is it actually improving structure?
We're mid-way through a similar process at work. Rewriting a legacy app in a new language, with new architecture and new features.
And it's a mess.
We're at 10x loc (admittedly, the new programming language is more verbose than the old one), comments make no sense. Yes, we have ~100% coverage, but most of the tests are meaningless. The agent keeps removing our tests to replace them with tests that are easier to pass, breaking code invariants, removing all the engineered data structures and replacing them with stringly-typed code, etc.
And of course, given the number of LoC (and the fact that the agent rewrites so much code all the time), it's physically impossible that all of them were reviewed by a human being.
AI made it possible, insofar as upper management would never have greenlit the project without AI, but I can't escape the feeling that we're building on quicksands.
In my experience, when you attempt something like this it grows like a crystal. If you start badly, with poor tests and poor architecture, that is the code that has the attention of the model going forward. More than any rules you give it, what matters to the model is all the code that’s already there. I’ve found myself in such a situation from going to fast and expecting new hyped models to “just take care of it”. The solution was to stop and take stock. I ended up deleting most of the dead-end and using the models to refactor the rest. From that point on, new code from the models was at the standard I needed, following rules already expressed in the code base.
If your code base is script-kiddy garbage, your models are only going to keep writing more garbage. You should throw it all away. I expect that isn’t an option. Try instead instructing the model that the code you have is legacy garbage written in a hurry that needs siginificant refactoring, but that right now I need one new feature written to these new standards instead. Take it one small piece at a time. Don’t let context go beyond 100k. Good luck!
I thought stringly-typed was a typo. Apparently not.
https://www.hanselman.com/blog/stringly-typed-vs-strongly-ty...
10x loc? wow. That makes me wonder how it will perform. And how you will review that, since if it is physically impossible for a human then who will take responsibility for what you release?
Benchmarks look good.
Reviews? They were the first casualty.
>> That is interesting, but... is it actually improving structure?
Can you be more specific? "Improve structure" can mean different things to different people.
We've ensured that agents strictly adhere to code architecture rules, using both agentic review rules and deterministic CI gates. Everything from file naming, location and namespacing to the "shape" of each file that shares the same role are consistent. We can trace functions of the same role across the same set of modules, with abstractions and code reuse where they make sense. Once someone learns the code in one part of the codebase, their understanding of that "spine" translates to other areas - the only differences relate to the specific business rules governing those areas.
>> And of course, given the number of LoC (and the fact that the agent rewrites so much code all the time), it's physically impossible that all of them were reviewed by a human being.
Code review was difficult at the start due to the volume of code. One insight we gained midway through though is that the value humans bring to code review is judgment and business context. So we created a code-atlas skill that creates an artifact for PR reviewers. That artifact highlights the most important parts of the code. For example, if a PR author has made the choice to use soft-deletes when the product uses hard-deletes for everything else, that is flagged by the code atlas, and a human reviewer can use that to ask questions about it. Meanwhile, things like boilerplate are de-emphasized; any problems associated with them are reliably found and flagged by AI reviewers anyway. The refreshing part about this is that this has almost completely eliminated bike-shedding: people no longer argue about module naming or whether a comment is worded properly.
> Code review was difficult at the start due to the volume of code. One insight we gained midway through though is that the value humans bring to code review is judgment and business context. So we created a code-atlas skill that creates an artifact for PR reviewers. That artifact highlights the most important parts of the code.
Yeah, we did that, too.
But every time I end up, for some reason, digging up deep in the code, I realize that it's not nearly sufficient in our case.
LLMs are a game-changer. You work more for less money.
Need to get the budget for those tokens somewhere.
Awesome. Any further writeups? Would love to read.
Also what kind of problems did you have with LiveView?
> We finished the rewrite in two months. > racing towards a deadline imposed by external factors so we all ended up working a lot of hours.
2 months of 80 hour weeks is 4 months of regular weeks. Can you clarify how many hours your team was putting in? And how large was your team?
Probably averaging 70. 9 devs and 1 QA engineer.
Assuming the LLM never got anything wrong or otherwise had to be re-prompted, that means your devs were reviewing 130 SLOC per hour, on what was described as moderately greenfield (examining new implementations rather than comparing to old historical accidents).
How?
I don't want to sound flippant, but if the point is to add human thought to the mix, that's a high review rate even when examining small tweaks to an existing, working product, even with substantial AI help to pre-filter major gotchas before you bother spending a lot of human effort on the review. That's only 20-30wpm, but a review isn't just scanning or reading code, especially if you're trying to figure out how a new system which doesn't run yet will fit together.
> Assuming the LLM never got anything wrong or otherwise had to be re-prompted, that means your devs were reviewing 130 SLOC per hour,
It's possible, I think, but humans cannot do repetitive mental work (like reviewing code) constantly without atrophy.
Can I review 130 SLoC/hour? Sure. Can I do it 80 hours a week? No. Not even a single 8-hour workday.
The fatigue aspect matters too, but another important point I was trying to get across is that not all reviews are created equally. In a working, well tested, properly factored system, with a high quality PR, I can do a cursory, local analysis of the new code and be very confident that it works. AI code I've seen is ... not that. I wouldn't be comfortable in that review without manually checking preconditions and postconditions, defining invariants, examining lifetimes, and a host of other activities. Moreover, for a greenfield replacement of lots of SLOC, I'd expect that most of the code for the early PRs can't even meaningfully run or do anything important, making any sort of broader architectural analysis impossible.
I could see a world potentially where they came up with a magic prompt allowing each proposed PR to be cohesive, shippable, well factored, and everything else you need to be able to actually review it at a higher level and be comfortable with the results, but I'm skeptical. That's a major innovation if they managed to do so even as a one-off, and that wasn't the thing they highlighted when talking about the project.
Is that actually a high review rate? Especially if you know the language and domain. Sure, initially there's a learning curve for a new codebase structure, but lots of lines will also be trivial and many changes might also be similar to each other.
For small separate changes in isolation then maybe it's ok? But not for whole days 8 hours each.
But then you need to watch for bugs coming from interaction with previous changes and in 700k loc that might be nontrivial. How do you know which states are reachable and which are not? That takes time.
It only takes a botched condition here (forgot a "not"? swapped "and"/"or"?), a swapped variable name there, code that looks ok, but isn't.
No don’t worry they said it’s not slop because there’s tests lol
Could you share more about how you guys set up the rewrite? I am interested in the shape of the software as well as how you achieved (or aimed to achieve) high quality.
> We could have gotten it done faster, but we were well aware of the potential for slop and thus paid an absurd amount of attention to (and tokens for) code quality. For example, there is a 100% test coverage requirement in both server and client, combined with AI-driven review rules that say all tests must be non-vacuous, plus a ton of invariants enforced via deterministic checks.
This is why my current view in terms of LLM productivity gains are:
- debugging and triaging 5x
- refactoring when you have tests in place 3x
- greenfield where you have zero tests is about 1.5x
> For example, there is a 100% test coverage requirement in both server and client, combined with AI-driven review rules that say all tests must be non-vacuous,
look, your application works, right? so it doesn't really matter what you or i think, and this is why AI matters. but this, your "100% test coverage" - that is pure slop. just 20 years ago, all the most popular software shipped with NO tests. are you getting it?
> just 20 years ago, all the most popular software shipped with NO tests
not sure what you're point is here. It sounds similar to "we use to use blood letting and leeches and doctors didn't clean their hands and everything was fine so what are you getting at?"
Good tests have real benefits. The fact that people shipped without them in the past in no way suggests they aren't needed or have no point.
Also, 20 years ago SW was tested by QA department and approved before shipping. Don't want to go back to that, but there were testing, just differently.
IMHO getting rid of proper QA done by teams of QA specialists is the main reason for the current software quality crisis (and that already started 15 years ago or so). We should go back to QA teams and proper QA procedures! Automated tests are no replacement, especially when they are set up by the same people designing and building the product.
Well. First they came for the testers. Then they came for the developers.
> just 20 years ago, all the most popular software shipped with NO tests
Are you getting older? A lot of people anchor their intuition of time and history to a certain year. There are probably still lots of people who think the 1990s is not that long ago even though it’s now over a quarter century since it ended. Maybe you mentally default to 2012 or so, when it might be true that most popular software shipped without automated tests (although manual QA was a lot more extensive in 1992).
But 20 years ago is now 2006, and unit tests were well established as a best practice. Perl had extensive automated tests in the late 1990s that everyone who ever compiled Perl would have noticed, since they were run by default and produced obvious output. Kent Beck’s “Test Driven Development: By Example” was released in 2002, and popularized both the name and practice.
But 20 years ago is now 2006, and unit tests were well established as a best practice.
I agree with the spirit of what you wrote, but my recollection of the timeline is different. The first decade of the 2000s was peak Crazy Agile Advocacy, but IIRC it wasn’t until the 2010s that unit testing really became almost universal practice. Much before that and it was still tangled up with XP, TDD and lots of other things that certainly weren’t universally accepted as good practices (notwithstanding the strident advocacy of a certain group of consultants/authors/speakers/bloggers and their fans).
I remember, back in the mid-2000s, when we had some consultants brought in to talk about different aspects of quality and testing. There were several working groups, each led by one of those external consultants, and one of them was about unit testing. This was in a relatively large software development organisation for the time, a few thousand people, and while some parts of the organisation had some form of automated testing operating by then, it definitely was not the case that the well-known products produced by the organisation all had a unit test suite. Other practices we’d consider routine today, such as peer code reviews, were also in their infancy during that period: some were doing them, many were not, and generally we had much less experience of how to do them effectively than we have today.
As an industry, I don’t think we really matured in how even the most ardent fans of unit testing were writing test suites until the 2010s either. In the 2000s, we still had lots of people mocking the entire universe and then writing unit tests that were 99% testing those mocks because of 100% test coverage requirements, and similar dogmatic nonsense.
By the 2020s, I think there was much more awareness of that automated testing is generally a good idea, but there are different kinds/levels of automated testing and finding a mix that suits each project’s specific needs is important. One of the great benefits from the more recent AI tools, particularly the agentic ones over the past year or so, has been that it has clearly demonstrated both the value of a good automated test strategy and how much of a waste of time vacuous tests are.
What kind of software are you talking about? Test harnesses were commonly used in 2006. JUnit was created in 1997.
>> but this, your "100% test coverage" - that is pure slop.
Not really, but I can see why some people think that.
We treat 100% test coverage as "required, but by itself not sufficient". It doesn't give us false confidence that everything will be perfect or anything like that. But it provides us with the discipline to make sure no corners are cut, and the bugs that are fixed don't come back.
One refreshing aspect was that during PR reviews we stopped debating whether something needed test coverage. Instead we focused on what was being tested and how.
> One refreshing aspect was that during PR reviews we stopped debating whether something needed test coverage.
I’d be curious to know what percentage of the time spent implementing tests would have otherwise gone to discussions about whether to implement them or not. ;)
> just 20 years ago, all the most popular software shipped with NO tests. are you getting it?
Not really?
About 20 years ago, I was working on Firefox and we had millions of tests on CI. I was working on a host of other open source apps and they all had tests (most of them had no CI, of course).
And 80 years ago cars didn't have seatbelts. Your point?
Careless drivers got weeded out.
Cars today are safer than ever. Drivers (in my memory anyway) have never been worse.
If only the careless drivers were those crippled or killed by their poor driving, it'd be a self-resolving issue as you imply, and nobody should care.
However, what actually happens is that careless drivers often cripple or kill innocent bystanders in other vehicles as a result of their poor driving. That's why seatbelt laws and improved vehicle safety features are a good thing.
But surely then you agree they are having an effect. Thus my analogy serves its point - test coverage isn't to be dismissed out of hand.
I'm exactly the opposite. I like knowing how the code works, what the data structures are, what APIs are being used, and yes even typing the code into the editor. When I'm working with LLMs there's less thinking. I'm bored. My brain is not fully engaged in the task. There's less sense of accomplishment in the finished product.
I also prefer to drive cars with manual transmissions.
> I like knowing how the code works, what the data structures are, what APIs are being used, and yes even typing the code into the editor.
I'd say it probably depends on the kind of work you do - if the low level details are exciting then that's totally understandable. But if you're dealing with more rote CRUD work or soul sucking enterprise bullshit, then probably less so and the low level details are obstacles to getting things done, alongside sometimes unreasonable workloads.
I'm reminded of: https://www.stilldrinking.org/programming-sucks
> Every programmer starts out writing some perfect little snowflake like this. Then they’re told on Friday they need to have six hundred snowflakes written by Tuesday, so they cheat a bit here and there and maybe copy a few snowflakes and try to stick them together or they have to ask a coworker to work on one who melts it and then all the programmers’ snowflakes get dumped together in some inscrutable shape and somebody leans a Picasso on it because nobody wants to see the cat urine soaking into all your broken snowflakes melting in the light of day. Next week, everybody shovels more snow on it to keep the Picasso from falling over.
That said, AI will probably saturate most CRUD work first, which doesn't make for great job prospects.
> I'd say it probably depends on the kind of work you do - if the low level details are exciting then that's totally understandable.
Even those who work with CRUD apps need to know things like computational complexity of standard container types, and how to pick basic data structures or choose which basic algorithms to use. Otherwise you'll end up implementing things that have an unreasonably high computational cost that will rear its head at the wrong time.
> That said, AI will probably saturate most CRUD work first, which doesn't make for great job prospects.
I think so too. Today's AI models excel at makeshift plumbing. The boring CRUD jobs are the first ones to go with a prompt.
What's stopping you from slowing down and doing those things even with AI?
Do you consider yourself to be part of the retro computer scene?
> That’s ok! The retro computing scene is delightful, full of people building and exercising old skills for the love of it.
Yes. You are the Kung Fu master in Carmack’s analogy.
Not necessarily a bad thing. Just because Carmack has an optimistic view and has some catchet in the programming world doesn't mean he's any more correct than a raving lunatic. Frankly, he said relatively little of substance and it's only made more irrelevant because he's said it from a priveleged position.
>Not necessarily a bad thing.
Agree. I made no judgement call.
>Just because Carmack
"Just because a man, who has some cachet with mountain climbers for being the first to climb mount everest doesn't mean he's any more correct about how to climb mount everest than a raving lunatic". That's your pitch?
Carmac has shipped massive selling, fun games, using low-level, innovative techniques, back when such crazy shit was necessary. The issue is the difference between what is necessary ("Miyamoto") and what is prescriptive ("Kung Fu").
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
Focusing on data structures, architecture and algorithms is what competency in programming has looked like since forever. Building systems out of smaller pieces gets you there.
If your complaint above is that you were struggling with syntax and reading documentation, one might ask if you failed to progress past beginner levels, and now AI is just your cheat-code?
Do you remember how bad documentation was? I still have nightmares about Twisted.
Some projects have fantastic documentation. Qt comes to mind. The experience of writing Qt is a pleasure because I can always jump to the doc for whatever class I'm dealing with and find what I'm looking for immediately. Also every argument type is well-linked in every signature so it's easy to follow and understand everything you're dealing with.
And I have wonderful lucid dreams about MSDN.
Also, are you implying that docs became better in the AI era?
> Focusing on data structures, architecture and algorithms is what competency in programming has looked like since forever
yes, being able to bang out leetcode hard from head on an interview on paper matters so much... oh wait. it does not.
in the real world, outside of interview questions, it hardly matters. when it comes there, I'll optimizite it, but getting the first system up and running in a way I want is way more fun & challenging. need a lock free ringbuffer? I'll look up what's the latest way to build it. or just ask my AI.
So which is it now? Do you hate thinking about algorithms and data structures or do you hate writing code? Or both?
> yes, being able to bang out leetcode hard from head on an interview on paper matters so much... oh wait. it does not.
That's about reciting standard data structures like stack and queues. I think parent is talking more about the design of primitives for the domain of the software. That requires creativity and insight.
I think you are not interpreting GP in the most charitable way. He simply said that not having to manually write all the code lets him spend his energy on bigger things. That is different from "struggling with syntax".
Syntax is listed right there in the GP comment. They've given plenty of rope to hang themselves by.
Someone who says that programming is not about working at the level of about data structures and algorithms without LLMs raises red flags.
It is the same. I mean many mainstream languages made thinking in datastructures hard. Not a coincidence why functional languages, Haskell, F#, OCAML, Scala, Clojure, LISP, etc. had their enthusiast, as they felt just like what you claim.
The datastructures already did the heavy lifting. The syntax was not something to struggle with, but it was the natural way to stick the bits together.
JavaScript for one never gave me this feeling, and I always felt that either the language, or the libraries, but something was always a struggle to overcome. (Python too... seriously, working with collections is a pain in the "pythonic" way for someone who has experienced LINQ... and for most line of business apps it is all about working with collections.)
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
Why? What makes you think your data structure design, architecture and algorithms are ever going to surpass AI in the near future?
You honestly can't see a (near) future where those 3 elements are done by AI, not by you?
I can and I'd be okay with that too. The world doesn't have carriage makers anymore. Nobody is entitled to doing what they love or what they are good at. I certainly didn't as my job as a software engineer, despite being profitable, was far from what I like in the discipline.
That said, I think AI is still many years or decades away from completely replacing the Software Engineering profession. My kids are entering college right for a CS degree and that's what I tell them. I have skin in the game as I'm ultimately responsible for them.
I could be wrong, but anyone's opinion is at most an educated guess at this point.
I’m the opposite. I don’t believe there is a royal road to understanding anything. For me, the process of programming involves frustration. That is usually when I find my greatest insights.
Syntax isn’t a big deal. Names either. You can look them up. Remember them. Language gotchas are annoying and sometimes problematic.
To me, our job is understanding problems. And for me, understanding the problem involves wrestling with the code. I learn much from modelling problems in code, building theories, testing them.
Once an LLM system has generated some code I haven’t learned anything. Even when I read through the solution. It doesn't require the same activation of my brain. There’s nothing quite like working through the problem yourself.
LLMs definitely feel like they are draining my passion for computers. There were plenty of folks who checked out or were never truly passionate about programming. Now they’re louder than ever. “Nobody cares about code,” and, “optimizing is a waste of time.” Now we don’t even want to understand how it works, or whether it works at all. They repeat the lines their master have told them: get on board or get left behind.
I’m pretty sure I am risking getting, “left behind.” But I’m okay with that. The tech is truly the least interesting thing to me. If I don’t have a career in 10 years… oh well. I’ll still be programming.
ya i find all LLM output to be incredibly boring and unskillful, I can ship vibe bugs fast with the best of them but it brings me no joy.
I'll never let myself be left behind but the joy professionally of writing quality software is 100% gone.
The possibility to have an agent implement every little thing that comes up in your mind as you're building doesn't spark the tiniest bit of joy? Previously, "ooh it would be cool if" had to answer to "yeah but it'll take too long". Now, it's more like, "how important is that really?" to stupid ideas that never would have seen the light of day before.
> "ooh it would be cool if" had to answer to "yeah but it'll take too long". Now, it's more like, "how important is that really?" to stupid ideas that never would have seen the light of day before.
My answer was it to "ooh it would be cool if" has always to build a PoC of the thing or a MVP, then I can flesh it out when I need more features. Sometimes a web app can be a single PHP script, and a cli command can be as simple as a single file C program. Or using tkinter with python for GUI.
The answer to "ooh it would be cool if I can travel fast" is not "yeah but it'll take too long to build a car". It's "let's build a kick scooter first".
Not even a little bit to be frank. The joy of things came from their implementation to me. I will write something and then peruse its code on github for hours afterwards just looking, like one would at an art gallery.
If I did not toil on it I wont use it most likely. There's a very very small amount of software I ACTUALLY desperately need in a way that I would not care how it came to exist.
Do not get me wrong, those things exist, i have a plethora of dog shit vibe code websites, clis and tuis and other random stuff on a self hosted forgejo. They did their job now they die. But it brought me no joy, in fact it was rather unpleasant the entire time doing it.
That's really sad! I'm sorry for you. If you try reframing it, maybe you can find joy again.
Have you tried live programming (smalltalk, LISP)? Or a proper Edit-Compile-Run cycle with a good editor?
A lot of people are bashing old practices, but from y standpoint, it always seems like a lack of proper (usage of) tooling to streamline the coding phase of building software.
Dear sir, I appreciate the help but, as I mentioned, I've been around since the Assembly days... Been there, done that. I currently have a crazy efficient Edit-Compile-Run setup and a great VSCode personal config, all of which were made a lot more crazy efficient with Codex.
LISP has been around since 1959. To the point: the proclaimed advantage of operating at new levels of "abstraction" is not a novel contribution of LLMs to coding.
Put another way: live coding, meta programming, high level abstraction, all have been possible for some 60 years now. Two generations! We don't need the monstrous amounts of accidental complexity involved in running dozens of GB in RAM for LLMs and all the "harness" apparatus, we have had from the right tooling for almost a century (!) now.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
That would be lovely.
It's sad that we're being forced to vibe code, though, because my day-to-day experience of that is that the agent does not respect the data structures I feed it, nor the architecture, nor the algorithms.
> Pure vibe coding is dull and unsustainable with current technology for all but the simplest systems; AI-assisted coding, on the other hand, rekindled my passion for computers.
Agreed.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
That exact sentence could have been said 20 years as well as 40 years ago. I don't know how you programmed pre-LLM, but line-by-line has long been a thing of the past, if it ever existed. I'm sure the folks creating the Apollo software were thinking a lot about data structures, software architecture and algorithms.
They weren't. A lot of abstraction concepts like ADT, modularization, structured programming had to be developed over the following decades.
> AI-assisted coding, on the other hand, rekindled my passion for computers.
"Walking on stilts made me taller"?
More like, not having to read the docs of a library or a domain with a million gotchas is a bummer and best avoided if possible.
Kinda agree with this. And your point is valid for most of the problems that we solve today as software engineers.
However, you cannot forget that there are problems where - all the knowledge of - AI don't help. Problems where letting AI do the work for you means putting more time and effort than doing yourself.
Problems where you need to be so precise in your prompt/spec that at that point you're coding in English. But English don't compile.
I like the idea of power tools vs hand tools. AI is a power tool, but that are times that the most pragmatic approach is using a hand tool.
>AI-assisted coding, on the other hand, rekindled my passion for computers.
I would be interested to know what you mean by AI-assisted coding.
I've been coding for 50 years (40 professionally) and maintain several largish C++ code bases for commercial apps. There is no way that I am going to let an AI scan (train on), let alone edit, my code. But I do ask MSCoPilot questions, basically using it like turbo-charged StackOverflow. And I do get some value from that, even if it is often wrong. Is that what you mean?
We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
Hadn’t good developers been focussing on those things, and other high-level modelling that relates the software system back to the underlying real world domain, for many years before the LLMs were in the picture?
I’d even say that it’s one of the most reliable markers of a more senior/experienced developer that their code reads like a clear and logical explanation of what the system does and why, with concerns well separated and minor details and technicalities abstracted away so they don’t clutter the rest of the code.
I kinda of agree, but still believe that writing most of the critical(!) code yourself has long term benefits. IME the initial mental model hardly survives contact with reality and all those little micro decisions that come up during implementation are good to do on your own and have in your own head instead of being buried in an LLM managed decision record where no human ever ventures.
It all depends of course where the code sits between "low level mission critical code" and "high level throw-away code". every non-trivial project has code across that entire range.
E.g. the lower level the code, the more I want to get directly involved, and that may mean typing each line manually to get that code directly into my head (IME for that purpose, writing is better than reading - have that manually written code reviewed by LLM instead).
Of course that only works if you don't have a manager breathing down your neck who insists on prioritising implementation speed over quality ;)
Also you should try assembly coding with modern (non-LLM) tooling, it feels incredibly more productive than with the primitive tools on slow machines of the past.
Also:
> software engineers can focus on data structures, software architecture and algorithms.
Come on, this is was already "normal" decades before LLMs, that's why an entire zoo of high level languages was created which allow to describe a solution in a highly abstract (yet still precise) way. Replacing this high level problem specification in a programming language with a "sloppy" human language specification is arguably even a step back.
(also tbf, I'm writing this comment while sitting in a cafe while the LLM at home is busy coding a GL mocking library ;) (which is exactly the boring type of throwaway code which should be automated)
I think I feel similarly to you.
M currently re-writing an app that I wrote years ago. All the issues came from data structures, queries, architecture that didn’t fit what emerged as the use case.
Now I can focus on those things and work far faster, and even ADJUST architecture, theorize about pros and cons of changes as I work … sometimes I find that some adjustments are easier than I thought.
The result is far faster development, and a more optimal result where I can stay focused on improvements / efficiency rather than random minutia.
There will always be people who will like it because they are the ones getting ahead and get some reward. If a person is rewarded for something, it's unlikely that they'll care how the reward comes or be critical of the mechanism. It's just human nature; AI has incredible downsides but those who get ahead won't mind, as long as they get ahead.
I bet thieves feel a rush when they rob a store. Does that also make it right?
a lot of people don't understand that the joy of making something is not coding but actually being able to build anything I want. AI just made it 50x better, as exactly as you said, we don't need to deal with the useless junk (what's the API syntax? what's the library syntax? oh it changed in the last 3 versions, let me look up the new API, this and that...).
it's great.
> a lot of people don't understand that the joy of making something is not coding but actually being able to build anything I want
I expect "a lot of people" understand perfectly well that that's where the joy comes from for you. Do you not understand that other people have different motivations?
Crafting code in your preferred language in a way that it is easily understood by others or fulfills some other constraints while doing whatever algorithm requires can be as fulfilling as writing poetry.
I can write „you live, you die, get over with it, life is hard, love hurts” - it basically encodes all wisdom of countless poems, books. Yet I have seen many people getting that idea better when the knowledge of this simple truth is in a form of a story.
Conversely, if you write an algorithm using better structure, better data structures it makes a lot of difference.
coding for the sake of coding is, well, dumb.
The number of down votes the parent comment has seems to me like a litmus test of people who will use AI and those that are just critical of it.
I have my reservations about AI but so far I’ve found ways to make me faster. So I’ll continue to use it but make sure to review my usage regularly.
The number of downvotes reflects the fact that people don't consider just calling something "dumb" a worthwhile contribution to the discussion.
Is painting for the sake of painting dumb too?
that's a dumb comparison. are you equating writing code to painting like Michaelangelo?
Did Michaelangelo paint his works himself, or did he buy a bunch of slaves and give them some prompting?
Eh, take your fav painter then.
How can you have proper real understanding of data structures and algorithms without at same time having line-by-line mental model?
Or do you blindly trust what machine tells you at whatever time you are communicating with it?
Architecture I might give not needing line-by-line model. But I really doubt the same with data structures and algorithms. Those are in the end build from lines.
Djikstra seemed to manage?
https://en.wikipedia.org/wiki/Edsger_W._Dijkstra#Use_of_tech...
Seems to indicate to me that he had full mental model of everything. Whole thing in his head at once. Clearly having it in mental model sentence by sentence.
AI would here be the word processor.
He still thought in terms of what the actual code would need to be, at that level of precision, and also wrote pseudo-code.
> one where software engineers can focus on data structures, software architecture and algorithms.
I see this a lot and I'm not sure why people don't think AI will be able to do this too. The self-play training that got them writing code can be used for this too.
Given enough context for a business problem, sure. But LLMs are not in a condition to judge how you should pick the technical solution to a business problem with several stakeholders, risks, and so on.
With the speed AI moves, a lot of technical decisions become reversible. And while engineering often makes decisions that could lie elsewhere in the business, outside of engineering, I could imagine those decisions moving elsewhere in a fully AI world.
Do you have examples of things that would be hard to train for? One that could be compensated for with changes elsewhere in the business process?
Yes, if Alex from BizDev is a scheming moron who consistently lies about the priority of features, it’s hard to keep an LLM on the loop about it when transcribing meetings and feature requests. If your boss is gonna be unavailable for a month and that means that a junior devs garbage PRs will be getting merged because the second in command is much laxer then you need to be aware for that and so on.
What I mean is that these things decant into technical decisions and even with all the AI in the world running a DB schema migration does not become any more trivial.
In the long term, I think you're correct. In the medium term, AI still won't know your business-specific workflows and data relationships, and humans are needed to define those things and let the AI build the scaffolding around it.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
I prefer an AI that is good at data structures, architecture and algorithms. Then, finally, no more leetcode.
leetcode and data structures are 2 different things. Just like a marathon and jogging in the park
AI is not an abstraction and is not like moving up from assembly at all.
not that i disagree, but its funny because i just came back from a presentation from a "chief ai officer" where he boldly stated that ai is the next big abstraction for programmers (even had fancy charts and tables to boot)
I find it disturbing how often supposed professionals make this claim.
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
This is what declarative programming gives us, not what LLM-based generation offers.
> I love being able to quickly bring out the program that is already running in my head without having to worry about the grind of typing it into a format that the compiler understands.
Using natural instead of a formal language to get probabilistic results based on token fields is not bypassing arbitrary constraints of the compiler, it is dereliction of the responsibility to know and articulate precisely what you are specifying.
Would you mind elaborating on where exactly the boundary between vibe coding and AI assisted coding lies?
Architecture is the first to be outsourced to AI, because AI shepherds have no idea how to do it.
You're describing software developers, even better, coders, not really engineers.
> AI-assisted coding, on the other hand, rekindled my passion for computers.
AI-assisted coding isn't a thing. Why would anyone pay you to code when your competitor spends 1 minute spelling out a problem and doing the same thing for 59 more problems?
As far as I'm concerned coding is dead as a profession, now we are Harness Managers.
You guys can downvote all you want. If you don't already realize this you'll realize soon enough.
This is where I’m at as well. It is incredibly liberating I feel very empowered
> We are going from the era of manual, line-by-line mental model transcription to one where software engineers can focus on data structures, software architecture and algorithms.
AI is getting good at picking those as well. Frontier models can be fed a vague problem, analyze the code base, and pick out an architectural solution that makes sense.
We're going from a world that needs specialized "software engineers" to speak the language of the machine into one where ordinary people need only sit down and think, "what exactly would solve my problem here?", spell it out in ordinary procedural language, and get a software solution that employs best practices without the intervention of professional computer-touchers.
Tim Bryce was right 20 years ago. Abolish programmers, bring back systems analysts!
Everyone who writes enthusiastically about AI already has the benefit of having worked without AI. They have been schooled in the basics. Enough of us know about data structures, concurrency, networks, language design etc. from the ground up that the knowledge is passed on. I worry about the world that we will be living in when a whole generation has skipped learning the basics the hard way. Given the attendance rates at various educational institutions, I fear that day is already here.
Herodotus wrote about finding people living in the ruins of a great city (Babylon) who had no idea who built it or how they built it.
I think that anecdote is from the Anabasis by Xenophon and refers to Assyrian city of Nineveh. Babylon was still occupied during the time of Herodotus and was one of the biggest cities in the world at the time. (the book spends some time discussing Cyrus's conquest of Babylon).
I thought it was Xenophon. MSCopilot assured me it was Herodotus. The irony! ;0)
(I spent a few minutes checking, but couldn't find the original quote)
Given the context of the thread, what you have done here fits so perfectly.
[dead]
The city of London was abandoned for about 400 years and fell into ruins after the people who built it left.
Right, I weirdly feel like we are entering an era where industry doesn’t invest that much in training the next generation - it feels like a rich getting richer scenario in all aspects of society
I think mathematics is feeling that concern with training acutely. The average math department pays its way by teaching in all forms and all levels: they don’t bring in the magnitude of grant money that concretely impacts a university’s budget. But they are already dealing with the consequences of that - that’s why universities that are cutting due to “low student demand” are going after math programs.
I think this has long been the norm without AI. Just look at a lot of politians cheating with their university tests, outsourcing the work that lands them their titles to low earning ghost writers. Why do you think so many incompetent people rise to powerful managerial positions to make terrible decisions without consequences. It's probably going on for much longer than we all think because it's not always easy to find hard evidence and we're all trained to treat circumstantial evidence. How many scandals were there of influential people buying their kids into elite colleges? AI is just accelerating what's been ongoing already.
We know that use of AI has a negative result for students: https://pivot-to-ai.com/2026/09/08/students-who-dont-use-ai-...
I read your first sentence as:
> Everyone who writes enthusiastically about AI already has the benefit of not having worked with AI
... because if you really do, and you actaully a capable developer, you become much less enthusiastic.
Anyway, definitely agree with your point, and let us also remember that it is our human output and expression which LLMs are trained on.
Tech priests reciting blessings to the Omnisiah. Time to do the blessing of checking how much 5h usage I have left.
> I worry about the world that we will be living in when a whole generation has skipped learning the basics the hard way.
Have you been schooled in farming? Raising livestock? Milking cattle?
Does your ability to cook good food depend upon your ability to till soil and sow seeds?
I don't mean that in ass way but re: what other comments said:
> it feels like a rich getting richer scenario in all aspects of society
That's a problem with society, not technology.
Holding back technology won't fix society.
The tooling for industrial farming is reliable on the scale of millions though, and the same for any other innovation that has replaced older ways of working. AI is in a weird place because it is not 100% reliable, and we do not know if it ever will be, but we also do not know if it will eventually good enough to where we are irrelevant.
If tractors plowed reliably 95% of the time, but unless carefully monitored the other 5% of the time they would blow a big hole in the ground, it would be difficult to abandon your shovel entirely.
>Have you been schooled in farming? Raising livestock? Milking cattle?
You're equating life skills to professional skills. I was not taught to milk a cow, but my milk comes from someone who was. The topic is whether software engineers in a professional context learned certain things about software.
> my milk comes from someone who was.
Your milk likely comes from an automated milker machine..
> Have you been schooled in farming? Raising livestock? Milking cattle? Does your ability to cook good food ...
Pushing that analogy, AI is the equivalent of automating everything from tilling, growing, all the way to cooking. It is as if the human is involved at the beginning in specifying what they want, and at the end, in plating up the food and consuming the product. The next generation will have no clue about the entire farm-to-table chain.
It's not there yet, but rapidly making it a reality.
Also, there is no one "tech". Different pieces of technology have different levels of effect on the world, and different timelines in which the world can come to terms with it. AI is the thermonuclear weapon introduced to a musket world ... it came upon us suddenly, and instantly flattened the talent/merit based economy. Now everyone has access to the same exoskeleton; the difference between muscles is not important.
The second huge difference between AI (and ordinary tech) is that a literal handful of people are in control of its economics. That kind of power breeds fascism.
> That's a problem with society, not technology.
Semantics. The tech directly enables the incredible power imbalance, and helps seize the means of consensus and debate and reporting. There is no incentive/mechanism left to fix society. An advanced society like the US is weaponized against vaccines, and social media and AI are to blame.
> That kind of power breeds fascism.
uhmmm and what have y'all been doing to prevent fascism and wealth inequality up until the point -before- AI became a thing?
What did you do about the mandatory government IDs required to access the internet?
What did you do to reduce police brutality and unaccountability in the USA?
AI is the ONE thing that COULD give the common peasantry a chance.
..maybe that's why so many fires are being stoked against it.. *thinking emoji*
You do realize that the same powers that have bred fascism and mandatory id requirement are hand in glove with the AI oligarchs, no? They gain with rampant use of AI disproportionately more than the peasant.
The peasantry stands no chance. Unless there is a French Revolution style uprising
> Unless there is a French Revolution style uprising
Yeah civilians are not going to win with weapons anymore. The imbalance there has been ridiculously disproportionate for decades.
But the common peon can use AI to look up laws and rights and other information and shit to see what we CAN still do.
USE it before they take that away too.
You can look up laws all night long. Check out all the laws broken by Potus, ICE (just to name a few) on a daily basis.
The peasantry is not on the side that enforces the law. AI is. AI is a force multiplier. The more force you have, the more multiples of it you en up with. Flock uses AI to do surveillance at scale. Every cloud service has NSA backdoors.
So we stop AI, uninvent it,
what then?
We go back to how it was before AI
And everyone will have a better life?
Let's hear your plan
It isn't just AI. I would like a world without the poison of social media, without guns & bombs, without dangerous chemicals. Yes, in many many ways we'd be better off. We are accelerating the destruction of our planet.
I don't have a better plan for humanity. I only have fear.
> a world without the poison of social media
No radio, no newspapers, no town criers, no gossip at the alewife's house?
> I don't have a better plan for humanity. I only have fear.
So your best move is to go around spreading that fear without offering ways to fix shit or inspiring anyone else to do so?
C'mon, you know better than to invoke a slippery slope.
My best move is to influence the people I care about to reduce dependence on these things and seek happiness in non-tech things (where tech is defined as those controlled by corporations), from community, live life from first principles. You are forcing me to answer a strange binary ... propose a fix for the world at large, or let me continue with all this shit. The world isn't as black and white.
Anyway, I'm done with this thread.
I would like to recommend, to both of you, Sarah Wilson’s I Eat the Stars: How to Live Fully and Beautifully in a Collapsing World. I am heartened that both of you are still trying to find solutions. -https://www.goodreads.com/book/show/241715900
I haven't been schooled in farming, but my understanding of food has greatly increased since we started growing our own vegetables.
Yes, but that still has little bearing on actual cooking skills, no?
Knowing how to go from whatever is fresh today in the garden to a meal is a cooking skill, yes. And how to preserve gluts of fruit, also a skill.
I mean, if I grow my garden and just provide you with the vegetables,
does that affect your cooking skills in any way?
In fact, if you divide your time between growing your own produce AND honing your cooking, both of those skills may suffer
compared to devoting your time to just focusing on one ability.
Otherwise if you try to do everything you'll never be as good as a full-time farmer or a full-time chef.
or how about another analogy:
Say one day your idea for a dish requires softer or sweeter carrots, etc, but oops you spent the last season only growing crunchier and mellower carrots, what're you gonna do now? With external suppliers you always have a wider choice of ingredients better suited to the end product you want at any given time.
Constraints are a good thing. I'll get creative with what I have, instead of having to rely on a supply chain that makes everything available to everybody all the time. I don't have to have apples grown on the other side of the planet.
Some people are schooled in farming. Farming is not some kind of lost knowledge people dont practice anymore.
>Have you been schooled in farming? Raising livestock? Milking cattle?
No! And good thing I'm not a farmer!
Ironically, this post comes off as out of touch. The purpose of the various martial arts isn't just to win in a life-or-death brawl or murder people as efficiently as possible. Similarly, the point of programming isn't just to generate as much code as possible, or only to be more "productive".
Code in most organizations is a means to an end to produce an actual product.
The job of a SWE is to not produce the most sublime readable code with cute language bells and whistles that you can show off to your other programmer friends. Yes its fun to do and interesting, but the main value in writing code is to express your intent so you and other people that are working with you can actually build something of value.
Software has value to the people on your team reading it. The product that you create with your software has a far wider impact than just that. As such, there is for _sure_ optimization pressure on "professional software engineering" to be more productive and actually make the product better to use, faster, with more features users like. The user typically does not care that you used a new C++26 feature, as much as I enjoyed writing it for them.
If I can produce features for users faster and I can iterate on them faster, this is a boon to me. I can program by hand for fun all I want in my spare time, but if I want to produce value for someone else, it is economically infeasible for me to be a luddite, and I will simply be outcompeted. Previously you were outcompeted by smarter teams who out executed you (and who also worked more), and now you can be out executed by basically anyone using an LLM who actually understands that the end goal is making a product that is pleasant to use and actually has utility, not code that is pleasant to read.
You can be an "performative/artisanal programmer" just as you can do "performative/artisanal martial arts." Just know that there will not be a large market for it in the real world.
You're reducing programming to its utility in producing exchange value in the captitalist political economy. That's what "value" means in this context. That's exactly what I'm pointing out. Programming is more than that, if you can think beyond your current economic constraints. Your life's activity ought to be more than just a tool for producing capitalist exchange value.
Does cooking food serve any purpose beyond mass producing food for restaurants to sell?
You're reducing programming to its utility in producing exchange value in the captitalist political economy.
Well, yes? If you want to write code that isn't useful to anyone and just gives you warm fuzzies, go for it. I've done plenty of that. But it's exceptionally selfish to try to forbid technological improvements so that you can get paid to work exactly how you want to.
Does cooking food serve any purpose beyond mass producing food for restaurants to sell?
Should we ban industrial agriculture so that you can feel more proud of your rooftop garden?
Rapid, empty, and poorly integrated code that appears to work but no one bothers to understand is much less valuable than everyone seems to believe.
Absolutely correct take. People are so caught up in doing the bidding, they forget what it is all about.
It would be nice if I could live my life without concern for producing capitalist exchange value. However, I live under the regime of capital and need to pay rent. So my goal is to pay rent with the least amount of suffering on my part.
But we can agree that writing with such disdain about people doing literally anything else, is perhaps a bit of a bad look.
Especially if it comes from Carmack, a guy who doesn't need to pay rent any more and can in fact live the rest of his life without concern for producing value, etc etc. He is currently doing exactly what he wants, just because he wants it. And that happens to be VR stuff, currently, afaik. And that's his choice. So when he speaks deeply condescending about other people doing exactly what they want ("retro computing is so delightful") it definitely comes from a different place as "hey I just want to pay my rent".
> exchange value in the captitalist political economy.
how can one exist in modern society without being an exchange value in the capitalist political economy?
linux is where it is because it is able to be a critical part of said capitalist political economy. even if you want to be a FOSS contributor all your life, you need someone to figure out the "economy" part of it.
food is a false equivalence in this case.
People are used to paying for food. They delight in paying more for highly rated Michelin starred food, even. Software is the opposite. People really really hate paying for software. It should all be free! The fact that making an additional copy of a piece of software is basically free vs creating an additional plate for dinner is very much not, has a lot to do with that. For sure. But it also means that I don't see a future where the "capitalist political economy" truely "values" aka pays seriously good money for a bespoke, handcrafted, no AI slop here, version of Photoshop to be run only once, and then you poop it out later.
When programmers say "pleasant to read", they usually mean something which is of real economical value, i.e. the code is easy to understand and maintain (whether by a programmer or an AI).
Products in most organizations are an end to making profit.
The job value of an SWE is to maximize that profit. It doesn't matter if the product is better to use, faster, with more features users like - that's an early 20th century model of value production.
What matters is how much money the company can extract from its customers, and how little it can pay its employees. Use dark patterns, increase lock-in, and switch to a rental system with recurrent payments. Minimize employee benefits, require broad non-compete agreements, have long vesting periods and lay people off before its reached, or simply fire them and order the others to pick up the slack using AI.
If you want to write software meant to please the user, do that for fun in your spare time -- though remember that your employer still owns your IP, so it's not like you can create a market competitor.
Alas, the above was meant in sarcasm but is all too true.
The Luddites were not opposed to machines. They were opposed to bad labor practices, with machine-breaking as way of applying pressure on employers.
> The Luddites were not opposed to machines.
In the sense they were not opposed to all machines as a concept. They were definitely against machines they thought reduced their labor value:
"They wrecked specific types of machinery that posed a threat to the particular industrial interests in each region. In the Midlands, these were the "wide" knitting frames used to make cheap and inferior lace articles.[22] In the North West, weavers sought to eliminate the steam-powered looms threatening wages in the cotton trade. In Yorkshire, workers opposed the use of shearing frames and gig mills to finish woollen cloth.[23]"
Citations in
https://en.wikipedia.org/wiki/Luddites
Yes, that's what I wrote. "They were opposed to bad labor practices, with machine-breaking as way of applying pressure on employers."
Otherwise it would be like claiming that an industrial union is opposed to people working in factories by pointing to a strike action and concluding they members just want to stand around outside the factory instead of work.
Recall that my comment is in response to "it is economically infeasible for me to be a luddite".
If that means something like "infeasible for me to oppose bad labor practices" then collective action is the typical response to bad labor practices.
If that means something like "infeasible for me to destroy the employer's use of AI" then I think that's mistaking what Luddites did as being the Luddite goal.
You wrote "The Luddites were not opposed to machines." What you wrote makes it sound as if there was no problems with machines, only with labor practices. That's simply misleading to untrue in this chain.
You can say Luddites were not only opposed to machines they thought cost them (which was the main reason they started the trouble they did at that point), but they also (insert labor practices).
Read their writings or contemporary reports. The wiki page has ample references to good material.
Quoting the Wikipedia link you gave:
"Luddites were not opposed to the use of machines per se (many were skilled operators in the textile industry); they attacked manufacturers who were trying to circumvent standard labour practices of the time".
How is that meaningfully different than what I wrote?
In Musashi's era, meaning the late 1500s, kendo (sword fighting) was absolutely about being as "productive" (read: lethal) as possible.
As it happens, this was also the era when firearms had just been introduced to Japan. In 1575 Oda Nobunaga demolished the Takeda cavalry at the Battle of Nagashino, marking the first time firearms had been used at scale in Japanese combat, and in 1600 Musashi participated in the decisive Battle of Sekigahara where both sides used them extensively.
The end of the Sengoku Jidai was triggered by a warlord (Nobunaga) who equipped his armies with massed ashigaru levies armed with long spears and tanegashima arquebuses. It was absolutely a technological brawl where the valiant highly trained cavalry of warlord's like Takeda Shingen got mowed down by the bullets of musketeers stationed behind well prepared and covered firing positions.
If it was still going on today, the warlords would be adopting drone warfare and vibecoded 3d printed cruise missiles.
Everyone in Sengoku Era Japan had access and knowledge of guns and cannons.
The key for Nobunaga is "Ashigaru". Nobunaga gave the guns to the peasants. That also means that Nobunaga mass produced the guns to a level that no one else was doing.
Yes it was a technological brawl, but inadvertently it was one that worked with and uplifted the Ashigaru into a real combat force.
I think you are slightly missing the mark of the historical reference.
What you say is true for modernized budō disciplines. They have very different purposes.
But this this is not what Musashi was concerned with. He was practicing kenjutsu (not kendo) / writing about hyōhō.
The primary criterion was absolutely murdering people as efficiently as possible in a life and death situation.
"The true Way of sword fencing is the craft of defeating the enemy in a fight, and nothing other than this"
Japanese martial arts generally come in 2 forms. -do (the way) and -jitsu (the art). -do forms are about self improvement, -jitsu forms are about effectiveness. You can see this with judo and jujitsu. Carmac is clearly aware of this difference as he says:
"We aren’t there yet, but carefully writing code completely by hand is moving from a -jitsu to a -do. "
IIRC Carmac has done judo (I'm not sure to what level).
> The purpose of the various martial arts isn't just to win in a life-or-death brawl or murder people as efficiently as possible
That's a retroactively-applied justification to save the embarrassment for martial arts that don't make the cut for modern CQB.
When photography came out, artists redefined their purpose as not being about realism.
Similar has already happened with martial arts, as OP mentions, and you've grown up with the new definition/focus not the original one.
https://news.ycombinator.com/item?id=49668392
As someone who did train one of the traditional martial arts for a few years, I appreciate the comparison.
I don't know how much weight your "just" is meant to carry, but I remember a culture of cope and excuses about why "my" flavor wasn't the winner of any MMA event.
But at least I got some exercise, strength, and flexibility out of it.
I think it's an interesting analogy, not to be dismissed so easily.
I don't see him saying the point is volume of code. I see AI generating code, and if I question it, it can justify design choices pretty well. I can give it bug symptoms, and it can find and fix the bug. Usually.
But yes, the analogy breaks down in the fact that I understand what it's saying and understand when it's wrong, because I learned it in the first place.
Or maybe it doesn't break down completely. If an MMA (AI) tells me to move in a way where I know I'll lose my balance, or over extend, I will say no, because of my previously acquired experience.
The whole latter part of the post is exactly about that.
'Make sure you don't fall behind!!!' is my least favourite type of post about ai. There's resllt nothing to learn about ai. You're just typing and telling it what to do.
This is like saying there's nothing to learn about programming, you're just telling a computer what to do. :)
It's partly true, but where this logic gets stuck is software engineering, for both the cases.
Just telling the AI what to do won't get you to good software, especially when you want to use dozens of agents working in parallel, when you have something correctness sensitive, when you want the AI to try and solve a research problem you have a hunch about but not a concrete solution.
but the solution, ironically, is not learning more about ai, but learning more about good software engineering, so you can tell when the ai is not doing it
No, software engineering is fundamentally changed because of AI. No amount of digging our heads in the sand is going to undo that.
For example, the traditional best practice cycle of "small incremental change, code review, test, commit" is pretty much obsolete now. The way ten collaborating agents can make short work of a complex project is not something that fits in with our existing software engineering wisdom at all.
We are still trying to figure out the new science of software engineering. And the best way to get better now is to just figure out what works and what does not for your use case.
I'm not talking about the transient aspects of producing software; I'm happy to accept that AI will change that, but also I feel that it will change it in ways that really aren't very hard to learn, and truth be told the more time that passes the smaller the gap will get as the agents get more capable.
what I am talking about is principles that govern what good software looks like, what properties it has to satisfy in order to be extensible and maintainable and performant and all that other good stuff, and the AIs are not going to make that knowledge obsolete any time soon.
> what good software looks like
I think this will change quite a bit too. Code being readable is one of our core tenets. Functions fitting within, approximately, a screen of code used to be ideal.
Modern AI as already past solving that problem. You can give it a million line codebase, ask where something specific is happening, and it'll tell you in less than a minute.
If we can de-emphasize readability, what do we gain?
Custom hand rolled containers and data structures for your use cases are somewhat frowned upon unless really needed. Well, probably not anymore.
What about a manually inlined mega-function with loops unrolled that pre-empts some of the compiler's work? No way that would fly a couple of years ago. Already seeing this in performance sensitive code.
> truth be told the more time that passes the smaller the gap will get as the agents get more capable
Yup. A lot of work is going in to reducing the skill required to operate AI agents.
> reducing the skill required to operate AI agents
For accomplishing the same task, yes.
But given these tools straight out of science fiction, why on earth would you be stuck doing the same things? There's no point spending human thought over something an agent has just automated yesterday.
Think bigger, take on more ambitious projects that are perpetually at the limits of what you and AI can accomplish.
>No, software engineering is fundamentally changed because of AI. No amount of digging our heads in the sand is going to undo that.
Yet anyone who claims that fails to procure sufficient evidence or instruction on how exactly training the to-be software engineer in the age of AI should be. Until that happens, people still learn DSA, write code manually, and train their problem solving skills with programming exercises.
And I mean handwriting them, not ordering "one solution for Leetcode 1133 in Rust, please" so we can proclaim that we're writing Rust so fast that I don't have to read a book about it anymore.
> fails to procure sufficient evidence or instruction on how exactly training the to-be software engineer in the age of AI should be.
Of course there's no instruction on how to succeed in a rapidly changing new field.
Do you think someone is more likely to succeed by getting their hands dirty and trying things out or waiting around for 'instruction' to be available?
> people still learn DSA, write code manually, and train their problem solving skills with programming exercises.
Maybe you're confusing computer science with software engineering? I agree that you'd still need to learn about algorithms, just like calculators do not reduce the need of learning algebra and trigonometry.
Yeah I'm hoping AI can bring us back to software engineering of 20 years ago. Where studying the solution to a problem, finding clever solutions, getting everything to work without getting buried in little concerns is really important and "best practices" can just be a line in agents.md and the uninteresting part can just be handed off.
> This is like saying there's nothing to learn about programming, you're just telling a computer what to do. :)
Counterpoint: a friend of mine who's not a developer has vibe coded multiple apps. They work just fine. Granted they're not particularly complex (e.g. domain specific CRUD type apps) - but clearly the skills required to do that are just "ability to talk to the AI" - in other words, everybody can do it.
You could also copy paste large blobs of code from stack overflow 'back in the day'.
The baseline of what you can do without being an expert has jumped significantly. My claim is that the baseline of what you can do being an expert has also jumped significantly.
There's nothing to learn about being an engineering manager. You tell your developers to write code, go on vacation, and come back to a completed product.
AI is built to adapt to you. ICs aren't.
Also the thing that is infuriating is, do people obsessed with using AI for everything not realise that, they are surplus to the entire process? They are doing 'prompting' or whatever but the end goal will eventually be that they are obsolete and will not be required. Companies will just endlessly, automatically pump out AI generated stuff without any human intervention at all. The tools they gloat about will be closed up and they will not have access to them any more.
You're not really 'keeping up' with anything, you're just fooling yourself into being part of a process that wants to eradicate your presence.
It's almost like embracing this stuff is giving them an illusion of control they don't have
the point of AI hype is to increase shareholder value.
The system that solved Navier-Stokes certainly was not about OpenAI engineers just typing and telling it what to do.
The recent advancement in math with the Riemann Hypothesis by Jared Sumner was basically him saying "you can do it! keep going!", however.
> In 2022, he left Oculus to work on his AGI startup, Keen Technologies
https://en.wikipedia.org/wiki/John_Carmack
oh
Yup. More hype mania from someone with a financial interest in people abdicating their thought to AI.
I understand why people value the code John Carmack has released but I do not understand why people value his public statements.
"eventually id Tech 5 is going to be open source also. This is still the law of the land at id"[0]
"Great! I think Microsoft has been a good parent company for gaming IPs"[1]
By sheer coincidence, John Carmack is peddling machine generated code.[2]
[0] https://web.archive.org/web/20081003111457/http://www.linuxg...
[1] https://x.com/ID_AA_Carmack/status/1308069857913720832
[2] https://80.lv/articles/john-carmack-s-agi-startup-keen-techn...
Don't throw the baby out with the bathwater. It makes more sense to read his 'public statements' and judge them individually rather than in aggregate. No one is correct all the time.
As for this current post (just a tweet really, public statement sounds overly official), I think he's making sense. If you don't follow industry trends, you'll eventually be out of touch. Whether you're a senior software engineer or engineering manager, keeping current with the evolution of tech will make you better at your job. Today that happens to be related to following AI developments, but it applied equally to learning higher level programming languages in the 90s, or big data engineering practices in the 2010s.
1st link is broken
https://web.archive.org/web/20081003111457/http://www.linuxg...
I have a new theory as of this moment.
Elon Musk, Paul Graham, Steve Yegge and now, sadly John Carmack. Your average hacker scoffs at the idea of religion or faith, but somehow is comfortable with complete unquestioning fealty to whichever person who did something interesting with technology in the past and made enough money to afford drugs you don’t get arrested for and then they started prophesying.
Before you stone me, remember every prophet was downvoted in their own forum.
The nice thing about religious faith is that most minds can hold only one at a time. I may believe in an oddly resurrected deity who took the shape of a man, but I don't have room for anything crazier.
"We are fools for Christ's sake." 1 Corinthians 4:10
Is that the nice thing about religious faith? Polytheism seems somewhat more tolerant of others. And religious pluralism takes in one step further.
I am sure about few things, but it seems to me that monotheism and religious exclusivism at some times represent the worst aspects and outcomes of religious faith.
> most minds can hold only one at a time. [...] I don't have room for anything crazier.
I feel you aren't accounting for exactly how much "crazier" churches/sects can be, both currently and historically.
Whatever your view of religion, you are not very good at literary analysis. The verse you quote, in full:
"We have given up our wisdom for Christ, but you have insight because of Christ. We are weak, but you are strong. You are honored, but we are dishonored"
Not quite the same of what you imply is it?
But now I don't know what you think it means. Who do you think "you" and "we" are in this quote?
Go read Corinthians? I'm just pointing out it was quoted halfway through to make it sound like Paul just wrote "we dumb" in a letter.
Right. But you didn't quote it in full either, so I couldn't figure out what you thought it said.
So yeah, there's a base unit of meaning which is well beyond one or two verses (something I wish the church would learn).
Sure, but it is that Christ, Buddha or any of the other incarnations of the same idea? I am right there with you, believe it or not, but don’t John 3:16 the wrong football game.
I think you got downvoted unfairly because I really think you're sincere. My brain heard your comment in the voice of Nightcrawler from X-Men—and as the descendant of German Catholics, he's become one of my favorites.
I love that and want to know what that voice sounds like.
Also I want to add some Claremont era flourish to my response, ja?
Like the animated series version: https://m.youtube.com/watch?v=U7cMZPklcn0
I see it as those who learn to use AI effectively are seeing massive benefits. Those that haven't seen those benefits are still skeptical.
Someone who's seen the benfits, knows, with proof, the benefits exist. They're like Copernicus who realized the plants go around the sun, not the earth. The others are still like those who look up, see the planets go around the sky, and can't believe the earth is not at the center. They then shout "you're lying, you're crazy, burn the hertic!"
> those who learn to use AI effectively are seeing massive benefits
The massive benefits should be visible to outside observers as well, but where are they?
Yes. People see orgs tackling more problems and resolving bugs faster.
Even if we just look at public markets: manufacturers and hyperscalers stocks are through the roof, while they finance private model providers that are ever pushing their IPO into the future.
Doesn't look very much like growing prosperity as much as vacuuming value into the core of the corporate world system.
I don't agree that people do see that, and if they do, it's hardly an overwhelming trend.
I see my org delivering twice as many features and implementing way more tools that actually solve problems.
The issue is that doesn’t necessarily mean that customers will pay more, as most of the features of software are not actually core.
Would that really count as a 'massive benefit' then?
For the customers? Yes. For engineers building tools that increase their quality of life? For sure. For removing legacy cruft? Absolutely.
The story of the discovery of heliocentricism is a lot more complex than this; the people who didn't immediately accept heliocentric theories (including the ancient Greeks - look up Aristarchus) often had good, scientific reasons for doing so. Or just look up at the sky at night yourself and ask yourself how you, personally, would confirm it if someone told you that what you see in the sky is better explained by the Earth moving around the sun than the sun moving around the Earth.
> Elon Musk, Paul Graham, Steve Yegge and now, sadly John Carmack. Your average hacker scoffs at the idea of religion or faith, but somehow is comfortable with complete unquestioning fealty to whichever person who did something interesting with technology in the past and made enough money to afford drugs you don’t get arrested for and then they started prophesying.
Why do you characterize people you disagree with as having "complete unquestioning fealty" to any of these figures who did something interesting with technology in the past? Seriously, why do you think that accurately characterizes anyone's view? I think this observation that John Carmack made on Twitter has some merit to it - it doesn't mean that I worship John Carmack as my god, or even that I think he's necessarily correct about any other issue. And why would I need to do either of those things to think that the one specific observation of his that we're talking about in this thread has merit to it?
I am not lumping everyone in, more observing we are still amplifying the signal from radio stations that should have ceased broadcasting years ago.
I don't think that John Carmack or any of the other people you mentioned are categorically not worth listening to because in some cases the accomplishments that originally made them famous are decades old. If you think that Carmack is wrong on this specific point, make an argument for why; I for one don't think he's wrong, and I think that putting him into a category of people who "should have ceased broadcasting decades ago" is simply avoiding engaging with what he actually said.
One of the great joys of following guys I admire like Carmack is the little smile I get when I see one of his tweets and go, "yeah, John Carmack was totally wrong about that." For example he argued that UI buttons should act on press rather than waiting for the release, and it's been a UI principle for decades that once a button is pressed you wait for the release on the button, giving the user one last chance to back out of a destructive operation by letting them move the pointer off the button and release. And I was like no, I don't care if you wrote Quake, or the Principia Mathematica, don't fuck with my UI expectations.
Carmack has cheerfully admitted to being wrong in the past, for example admitting that the Saturn port of Doom should have used the Saturn's hardware primitives for a smoother experience rather than a faithful replication of the PC's BSP renderer which made it slow. When brilliant guys like him are wrong, they often are in profound ways.
I would suggest that last line is both wildly indulgent and dangerous. Inventing reasons why someone being completely wrong is actually helpful is a level of freedom no one really deserves.
Someone being wrong almost always offers an opportunity for them or others to learn. If someone extremely smart is wrong, the gaps in their knowledge may point to interesting directions for the curious. Einstein was wrong to doubt the principles of quantum mechanics, but the conflicts with relativity he elaborated helped point the way for future physics work.
Of course, it's important to be right when there are consequences on the line, but being wrong isn't ipso facto something bad.
Really embarrassing to see Carmack fall so low and have such little respect for the art of programming he once advanced. Unlike swords and martial arts in combat, code is still needed. It’s not like there’s some new medium that doesn’t use code at all. It’s just a question of who is writing that code: a human or a statistical model. Guns superseded swords, cars superseded horses, but coding agents haven’t superseded code itself. A better analogy would be if, instead of guns, we ended up using advanced kung-fu fighting robots. Which would actually be sick…
Whatever his technical chops may be, Carmack has slid fully and comfortably into the role of “influencer” over the last decade.
how the mighty have fallen. maybe he finally got tired of it with the years but never realized it
It's interesting to see how over the span of just a few years a lot of people went from:
> Architecture astronauts are out of touch and shouldn't give any advice because they haven't written code in ages. Only the hands on engineers can shape it since the design evolves in step with writing the code.
To
> I focus on the architecture patterns and high level goals and let the LLM take care of the rest.
Similar commentary was shared about anyone not writing the code daily, not just the architects.
No gotchas, I just think it's something which calls for introspection.
I'm one of (if not the) original architecture astronaut, so you may not want to listen to me, but you're sliding from "architecture astronauts are bad" (true) to "architecture doesn't matter" (false).
Arguably, architecture is the only thing that ever mattered. Below the level of architecture you're dealing either with algorithms or API calls. Algorithms can be validated by tests and API calls can be validated by tests and the type system.
But architecture is the one thing that could make or break a project and that you can't test for ahead of time. You either know how to create a good architecture or you don't. In fact, the whole point of the Spolsky's Architecture Astronauts' essay is that bad architecture (and bad architects) are a big problem.
AI works amazingly well below the level of architecture, but (I've found) it's not very good at architecture.
I agree architecture is important. But I think the best way to design a good architecture is to have a high level plan, and then feel it out by coding parts of it (usually near component edges / interfaces) in the actual domain with real use cases.
That exploration helped me see whether general "best practices" are applicable in this frame, and let me justify if not.
That was also prevailing opinion pre LLM:
> Only the hands on engineers can shape it since the design evolves in step with writing the code.
So I'm curious to know where people changed their minds.
I think your argument is you can't create good architecture without writing code. I sort of agree. You can't be a good software architect without knowing how to code, and you can't be a good architect of a specific code base without being familiar with the code.
But I don't think you expect an architect to have written all the code, right? I don't even think you expect an architect to have read all the code.
The whole point of being a good architect is understanding the abstractions so that we can focus on the overall system without necessarily knowing all the details. I don't need to know the FFT math behind JPEG to integrate an image library.
So there's no real change in opinion. Architects were never expected write or even understand every line of code.
I think they are lying to themselves. The patterns change with the hardware and environment, i sure code different and use other data structures when having to account for VRAM now, network security, etc.
Going from the specification to the code is not a one way street. You adapt the whole chain. Saying the only thing that matters is the spec is squinting your eyes and hoping for the best.
You stop learning how things actually end up in memory, compute, storage and network this way. Not sure how you can build a secure and fast spec then.
And even if you do know i never understand why not typing it out. You can use a lib if you don't want to worry about these details or know you are not skilled enough (tls f.e. ...). But having AI do it introduces uncertainty where there can be determinism.
I think it's just laziness and people not liking the pain of learning or needing to show off whatever first. Who knows. Still don't see a reason to use these tools outside of learning or whatever i used a google search for before.
This resonated with me as someone who: has read the book of 5 rings (translated), has done quite a lot of martial arts and has been coding for ~50 years.
I work for myself developing apps and selling online. So I have no employer pushing to use AI. But I feel a bit like a dinosaur watching the incoming comet.
Currently, I just use MSCopilot as enhanced StackOverflow and I find it useful for that. But I have been nowhere near Cursor, Claude, harnesses, agents or 'vibe coding'.
It seems my options are:
1. Keep use AIs as an enhanced StackOverflow (e.g. to answer questions about APIs)
2. Embrace the new AI coding tools
Really not convinced about option 2. I don't trust AIs with code bases that I have built over 20 years. Also, I'm not far off retiring and I'm not sure I can be bothered to completely change how I work (again). Would be interested to hear what conclusions any fellow coding dinosaurs have come to.
My suggestion would be just to try it. Get an openrouter account, add 50$ to it and setup pi agent to use it with a cheap and fast model; I personally use 5.6-Luna.
Run it on a throwaway system, pick a codebase you’ve always wanted to fix something about but didn’t have the time. Like you wanted to do a major refactoring or do a library migration to a better maintained library. Or you want to rewrite part of a program in rust for performance/security improvements.
The hardest part for me is sometimes it is hard to write what I want in a prompt; but you don’t have to put everything into the prompt, you can make a code edit as an example and then say; look at this diff, it is doing X; look for and apply this some transformation across codebase Y
If you have a good codebase, AI will have good patterns to follow and will produce pretty good code; and you can quickly iterate on the results (maybe over new context windows) and get high quality code that looks very close, if not indistinguishable from the pre-existing code.
>Run it on a throwaway system, pick a codebase you’ve always wanted to fix something about but didn’t have the time.
Thanks for the suggestion. But I don't have a throwaway system. All 3 of my codebases are commercial software that I charge money for. Also, I don't trust an AI not to serve substantial parts of my codebase to a competitor. Maybe I will try it if I start a new project. I fancy a go doing some Webassembly graphics at some point.
>Or you want to rewrite part of a program in rust for performance/security improvements.
My code is battle tested and robust through years of use. I don't rewrite stuff unless there is a real need.
>use it with a cheap and fast model
Also try it with a frontier model though. With $20 for a one-month sub you can get a decent amount of GPT-6 Astra usage.
I was in the same boat around March. I started with Claude and giving it really specific instructions about what I wanted. That turned in to more interactive planning sessions where after we nailed everything down I said, ok just do it and I reviewed. The more I used it the more I let go of some things and the more I held on others. Now I have adapted my entire approach to use both local and cloud agents. Start small. Find what fits you. Also try out different models. Closed source is very strong, but you may actually prefer a bit less capable model that you give more direction to.
Thanks!
To effectively use AI-as-an-engineer as a seasoned developer, you must change how you work. It won't work otherwise. Your knowledge & experience wouldn't allow you to ship raw AI code, you'll end up being frustrated instead.
An alternative way is using it as a pair programmer, which is one step above enhanced StackOverflow.
There are two ways to do this: 1. Subscribe to ChatGPT Pro (or the 20x version) for just one month and use Codex to generate the system you want—whatever it may be. 2. Purchase a Mac Studio or DGX Spark and use the latest local models to securely audit your code.
> The retro computing scene is delightful
that was truly, deeply, unnecessarily condescending of him.
it's so full of self-importance, even if he truly believes that whatever code he's writing is more important than anything else, it's really an unnecessary dig
especially coming from some guy who by many people is mostly known for his accomplishments in an era that many people would call retro computing now
sure I know this guy is almost literally the definition of the 10x programmer and he can choose to work on whatever he wants, so whatever he decided to work on is probably the most important thing to him, and if that's VR, that's ... also a choice.
doesn't mean he should be this condescending about what other people are doing
You're reading something into that line that I don't see. I read it as sincere.
This post reminded me of the story about Jeet Kun Do [0] after Bruce Lee [1] died.
JKD was supposed to be a martial art that adapted the best techniques from other martial arts. e.g. "have no style" because your style is constantly adapting.
After Lee died, JKD broke into two camps:
1. "We should only teach what Lee taught us and no more. e.g. the techniques he taught us are the core techniques."
2. "Lee taught us to be constantly adapting from other martial arts so there is no list of core techniques."
I've always loved this story as it highlights how humans have essentially two reactions to change: embracing it or fearing it.
0 - https://en.wikipedia.org/wiki/Jeet_Kune_Do
1 - https://en.wikipedia.org/wiki/Bruce_Lee
This is reductive to the level of the people misusing the Douglas Adams quote, with a sprinkle of false dichotomy. Fear and embrace aren’t the only options, and neither camp is entirely positive or negative.
There is plenty of middle ground which should be exercised. If anything, the reason we’re living in an increasingly shitty shit show shower is that too many people are too eager to selfishly embrace too much, with complete disregard for others or long term outcomes.
"as it highlights how humans have essentially two reactions to change"
I'd wager that the most common reaction to change is actually "wearily accept it as there is no realistic option".
Most change is deleterious to those affected; it requires them to change how they live or work, or pay more, just to maintain the status quo. This sort of change is usually imposed by large organisations against which the individual is helpless.
When people are faced with that sort of change it's little wonder they complain about it, but eventually they have to submit to it or face a degredation in their life or work.
Then those who imposed the change roll their eyes and say "ugh, people are so afraid of change," being insulated from and benefitting from it.
The next time you receive a ToS update from your $FAVORITEVENDOR that negatively affects how you do something, or a new tax filing requirement from $GOV that takes up more of your personal time, do come on here and post about how you embraced the change.
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https://xxcancel.com/ID_AA_Carmack/status/209844326221423009...
[dead]
https://xcancel.com/ID_AA_Carmack/status/2098443262214230095 for convenience
"don’t be the out of touch Kung Fu master"
posts on Twitter
> But don’t be the out of touch Kung Fu master, heir to lifetimes of tradition, that gets mauled by an amateur MMA fighter.
I have an issue with this analogy, since a professional MMA fighter is a highly skilled individual who has honed their body through years of training.
A more apt analogy might be "don't be the kung fu master who believes they can survive an atomic bomb, dropped from far above by a pilot who does not understand how it works, but who has nevertheless been gifted the ability to deploy it."
Some context. Many styles of Kung Fu/Gung Fu do not spar in any meaningful sense. Consequently, they have an overinflated opinion of their own ability and generally do very badly against MMA fighters (who do lots of sparring and pressure testing). There are lots of videos on Youtube of Kung Fu 'masters' getting battered by relatively inexperienced MMA fighters. This was sufficiently embarrassing for Chinese martial arts that they created a sport oriented form called Sanda.
I once saw an early black and white film of 2 Chinese Kung Fu masters fighting in a ring. Some sort of grudge match I think. It was embarrassing. You would see better technique outside a Wetherspoons pub at 2am.
I would say analogy is still apt.
When you look at King Fu master as a software dev who refuses to use AI and MMA fighter as a dev who embraces AI.
Vibe coders who know nothing about software development are untrained rubes who got mechanical arm that thinks for itself, they can maul MMA fighter, they can maul Kung Fu master but at the same time arm might just rip off their own face.
But he said amateur.
That’s great for martial artists where the new arts are objectively better and more robust against the wider array of attacks one must withstand today.
But software…? He’s declaring victory at virtually every level but the highest. Who honestly thinks JS should be cemented as permanent? X86/RISCV? CMake? It’s cool to abstract away the lower tiers when our tools are this powerful but it seems silly to leave this much performance, readability, and extensibility on the table forever.
John Carmack is a personal hero of mine, so it pains me to say this:
Carmack hasn't produced anything noteworthy since AI was invented, therefore, how productive can it really be?
It could be he is doing incredible work in private... but it could also be that he's lost in the weeds, because AI is so counterproductive while feeling the opposite?
I remain a skeptic.
> because AI is so counterproductive while feeling the opposite
Wow that resonated by a scary amount.
Again I don't get what people on HN are doing? Our client wants something: I mumble in my phone what they want, with some spec docs we had / made by mumbling in our phones: a working system comes out, we test it with our client, we fix. We sign a SLA, get paid 100k, a few weeks have passed. I mean, we should not measure everything in money, but for lack of a better measure for productivity, I cannot see how anyone finds it counterproductive. This was strictly impossible for our small team before recent AI and hiring more people didn't work for the pricing. Our profits jumped, revenue jumped, client count jumped. What are people here doing exactly that they are not riding the gravy train and even reporting all these negative AI experiences?
We do spend all our time either code reviewing or talking with clients but the latter was already the case and the former was just better spaced out over time as this would before take many months.
If it works for you, great! Just keep going. I only have the nagging question that if it’s so easy, why would the clients not do it by themselves? Certainly they understand their problems better than you and they can adapt to rising issues faster if their in-house team does it themselves. And certainly what kind of AI you can access, they can too and perhaps even more. So what will remain your value propositions?
I’m a critical user, not a categorical denier. But there are certain categories where I see the current AI face a wall: fitting new ideas, or existing code into an existing architecture particularly. Or work on the backend when constraints are not strictly enforced (for various historical reasons). Schematic understanding is still an issue.
Sometimes additional chunkings and detailed planning/instructions suffice. But other time, humans are still the best vehicles to code.
> nagging question that if it’s so easy, why would the clients not do it by themselves?
It's easy if you're already an expert at software engineering and know how to leverage AI. For people like that, it's a phenomenal upgrade (this is true for me and several co-workers I chat with, all of whom are chasing cool ideas on side projects). But if you're non-technical, or not use to thinking about requirements, or think that using AI is "give me the prompt", it's a pretty big moat to cross.
> I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
Plenty of reasons, including:
1. They don't (yet) know how to use AI to accomplish what they need.
2. The ROI is still meaningfully positive and they don't want to have to do it themselves.
3. Having a third-party do the work provides protection for decision-makers. If the project fails, the third-party takes the blame and "nobody gets fired for buying IBM".
4. The vendor does bring valuable insight to the table and pairs it with the use of AI to deliver a result that wouldn't have been possible in-house.
This doesn't mean that everyone will be able to get work and maintain their rates in AI world but some people will.
I recently tried to encourage my smart, technical, but not-programmer friend to build an app using LLMs and he was just like, "I still have no idea where to even start."
People talk a lot about how "real programmers" used to have to clean up or actually deploy everyone's half-baked MS Access app, and that sort of thing will probably still be the case for a while.
> to clean up or actually deploy everyone's half-baked MS Access app
So we are switching to LLMs to be fucking miserable in our jobs?
The whole point of the MS Access reference is that similar situations have been tropes since at least the 1990s. Bad code generated by someone who doesn't know how to program well -- whether that person is supposed to be a professional programmer but is incompetent, or has a different job -- is nothing new, and neither is having competent programmers clean it up. LLMs probably generate more of it, but can also fix a lot of it, or at least patch it up.
A year ago, LLMs were not useful for me as a programmer. Now they are: the models are better, they can use long contexts more effectively, and the harnesses are better at helping the models. Nowadays my job is mostly not programming, but LLMs let me organize and prepare tools in spare time rather than needing days or weeks of attention. I would not trust them on a 200k+ line project -- and Claude Opus 5 has issues even on 50k LOC projects -- but they absolutely can help given good direction and a narrow enough scope.
Then I don't understand at all what point you were trying to make about being miserable in our jobs. Cleaning up after bad code has always been part of the job for decades; so has balancing the creation of new technical debt against resource availability.
> The whole point of the MS Access reference is that similar situations have been tropes since at least the 1990s.
I do actually understand that.
I have done this very put the Access database on the web job myself. (FWIW I was well-paid for it and the firm I worked for earned a fortune, but this was in 1997)
I mean they've boasted[1] about their generated code being so good that they add basically zero value and that they're riding out the rentseeking for as long as possible.
Meanwhile they've apparently played with LLM porting of Postgres (or Postgres features?) and "would not put it in production"[2], so we can also guess the kind and scope of features being discussed here.
[1] https://news.ycombinator.com/item?id=49594498
[2] https://news.ycombinator.com/item?id=48855951
They're not "adding no value", the SLA is the value. I have a business problem, and I pay you to solve it and support your solution for me, is a completely different proposition than standing up your own solution as a non-technical org and maintaining it.
> They're not "adding no value", the SLA is the value
The code their Astra+Fable setup, automatically generated from requests customers leave in voicemails, is apparently so good they never correct it. If the stories being woven are true, the SLA is literally just a middleman's 100k cut.
At the very least there might be some particulars here that aren't universally applicable.
>"the SLA is literally just a middleman's 100k cut"
Indeed, welcome to enterprise software.
The second was just for fun; it is fun. This is very far from the code we roll out at customers though. We build LoB apps which are basically crud apps (they are not but most here would call it that).
We can have fun and make money right? Possibly at the same time but not in that case.
> The second was just for fun; it is fun. This is very far from the code we roll out at customers though.
Which is fine, great even (I do the same thing!), but in trying different things outside your day job, it seems like you do understand why people working on different things than you might be "reporting all these negative AI experiences"?
It's a pretty bad sign when you need to resort to this kind of comment stalking to try to find ammunition for a general argument. This user could be a complete con man, and it still wouldn't invalidate the core thesis of LLMs providing business value.
> you need to resort to this kind of comment stalking to try to find ammunition for a general argument
It's not a general argument, they made specific claims, but vague posted (and implying everyone else must be crazy) to the point that the conversation is derailed by a bunch of people trying to figure out what they meant.
> it still wouldn't invalidate the core thesis of LLMs providing business value.
lol, no, "providing business value" is not what was claimed:
>> What are people here doing exactly that they are not riding the gravy train and even reporting all these negative AI experiences?
Hard disagree. It adds context to what they said.
[dead]
Yes but it's cheaper?
Of course they will do it by themselves.
Because it's cheaper.
I mean it's weird that we all imagine reasons why we're still relevant when we have set fire to the thing that made us indispensable.
It's cheaper.
> I mean it's weird that we all imagine reasons why we're still relevant when we have set fire to the thing that made us indispensable.
Very few things in this world are all-or-nothing, and not every purchasing decision is based on price alone.
Do you always buy the cheapest meal? Car? When you renovate your house, do you always choose the cheapest contractor?
Tons of developers will lose their jobs, and many more will find it hard to maintain the salaries/rates the industry has been accustomed to. This is already happening. The days where an average graduate from a run-of-the-mill CompSci program or even a coding bootcamp could sleepwalk into a $150,000+/year entry-level job are largely gone. The days where you have job security simply because you're a competent developer with 10 years of experience are in the process of going away.
This does not mean that there is no subset of developers who cannot be successful in this market. There are people who are doing just fine because they know how to articulate their value and sell themselves to employers or clients.
> If it works for you, great! Just keep going. I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
Because it's not (yet) that easy, especially if we're talking a complex and genuinely useful app. Agentic coding is fast, but it's not magic.
> I’m a critical user, not a categorical denier. But there are certain categories where I see the current AI face a wall: fitting new ideas, or existing code into an existing architecture particularly.
Exactly. Which is why Joe Average still will have little to no luck vibe coding anything serious or novel. You still (IME) need a lot of active guidance, still need to push away from dead ends and propose alternative algorithms, and it takes hundreds of prompts to go from concept to what I would consider beta. (But, this is just my own experience, and it's possible I'm doing it wrong?)
I don't think that really matters. I have already seen companies generating their own code and just QA testing it, with no software engineers in sight. Or they ask us to "review" their 10k loc PR in 2 hours.
The spirit of the parent comment is true. People feel like it's productive and even if they make something worse, they are going to use it.
Clients are starting to, that’s exactly why I am not sure why AI doom deniers here think this will think it will go well for them. But it will still take awhile and we are enjoying that time. If we see new markets, we will move into them.
> I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
They can do it. What's the issue?
> I only have the nagging question that if it’s so easy, why would the clients not do it by themselves?
I mean, that's exactly what's starting to happen, we have more and more clients to whom we propose a quote and their answer is "guess i'll just vibe code it" or come to use with an app that they vibe-coded and does the job, and they're content with it. So far it seems to work out just fine for them.
Ya, AI is very good at generating number, be that code for software, images for ads, or banal prose for company blogs. AI not so good at growing corn, cooking eggs, biulding houses, running fiber, treating disease, changing brake pads, loading a truck... or any of the other millions of physical-world jobs on which the economy is biult.
If you company is all about creating things that go on the internet, sure, AI is your thing. But for most companies the internet is a communications tool rather than a product. Those companies are not seeing the claimed productivity gains.
They sure are though; they have many processes to automate as well: big corn farmers/factories also have admin, erp, crm, departments with processes etc. There are companies doing billions in revenue with departments of people just copy/pasting PDFs who do real life things like you state who have immediate gains. But they won't do it alone yet and luckily need us. They still benefit though vs the large consultant businesses or even their own IT deps though.
Literally everyone I know in a large enough company who talks about AI talks about increasingly panicky mandates to use more Copilot coming from above, like you'll lose your job if you don't use it more. I heard exactly this story from my neighbour just three days ago. Literally a call from head office demanding they use Copilot more — to do a task Copilot can't do.
Everyone in smaller companies describes various efforts to get AI to do more that ultimately end up involving lots of corrections or nurse-maiding ChatGPT to get it to do exactly what they need, when what they need is often so formulaic they should already have a process.
Nobody I talk to describes it in terms of massive productivity gains. Everyone describes it as a puzzle they feel variously compelled to solve.
I can add a data point for you: At my job they have made "amount of AI usage" a criteria for performance reviews, advancement and promotions. Mandate from the top: Use as much AI as you can. They even have a leaderboard (accessible to managers) showing who is using the most and least AI. It feels as though nobody even cares how good or bad a job I do, as long as I do it using AI.
That sounds completely miserable and Kafkaesque.
They do and there are certainly some mid-level management jobs at risk, but ask any farmer/electrician/millright about the claimed impact of AI and they will laugh. They have yet to see an AI capable of reliably replacing a fuse let alone doing a solid day's work.
Yes, agree with that, but that's usually not the sort of work we talk about here. But sure, robots are close there. All those admin jobs on the other hands...
> Our client wants something: I mumble in my phone what they want, with some spec docs we had / made by mumbling in our phones: a working system comes out, we test it with our client, we fix. We sign a SLA, get paid 100k, a few weeks have passed.
OK so, it sounds empty and miserable to me, but we can stipulate that this is how it is working out for you.
Given that stipulation: how long do you think this can possibly last, when you are in a race to the bottom with everybody else who is doing this?
Have you made plans about how you will get out of your office lease, downsize, subcontract this button-pushing to even cheaper people overseas, etc.? Are you ready to lay off everyone who works for you, downsize your house to a smaller mortgage? Because you're on a burning platform. If you can do this, so can everyone else.
I mean, I think we all are, possibly, on the same burning platform; I don't think I can fully avoid AI so I am trying to make sense of it.
But I intend to fully avoid being in a race with other phone whisperers if I can.
You're not just in a race to the bottom with everybody else who is doing this. I don't think his anecdote is particularly surprising at all. You can do the same with basically any typical CRUD app, which is already going to be some very large percentage of all business software. But this kind of also leads to the conclusion that so can the people paying you.
I think the years of software development/employment for problem solving, in and of itself, are numbered at this point. When people start to understand how relatively easy this stuff is, they're going to be in-housing everything. Not only for price but also because of increased flexibility/confidentiality/control, and even lower concept-to-live timelines.
What third party stuff continues to exist will see its comp plummet. I imagine now you can already get some really nice quality software contracted out on places like fiverr for nothing simply because the skill involved to produce quality solutions has plummeted.
I think it's a mistake to assume that quality doesn't plummet when cost does, even if the AI is capable of quality work. The quality issue will always resurface.
But yeah — I mean, I am a freelancer who burned out for reasons that are rather more influenced by the SaaS wave. That was hard to compete with. People choose between the solution that meets their needs and changing their processes to meet the ten-times-cheaper solution that doesn't, and that decision is often not at all irrational; by and large you want as many of your problems to be shared problems as possible.
I am trying to return to work so I am looking at what AI can really do for me, but the conclusion I draw is that since I cannot simply burn token money to solve people's problems, and because bugs cost me money, I need a strategy where I remain in full control of actual code, but LLMs help me do things faster. If I can't solve that, I am out.
Perhaps AI will upend the SaaS market before it fucks the freelancer market and the balance may temporarily shift. But it probably won't.
And at that point, as a fiftysomething, even with a bit of financial security, I start thinking about living a rather shorter, happier life, instead of a longer one. Because as much as I might have ideas, I don't think there is much I can switch to where I have appropriately deep skills to survive AI there, and all those alternative jobs will be oversubscribed and less likely to hire me.
I wonder if people in this industry have understood what we are doing to ourselves, to our friends.
A bit of a tangent here, but I'd look into lower cost of living areas if you have the ability to move/remote, even moreso if you'll be drawing social security or have a pension. Money just goes so much further, and with an overall much better quality of life. And there's always stuff like teaching, moreso because it's enjoyable than for the paycheck.
But in these parts of the world, making a few bucks doing whatever in the software world goes so much further. Because of that I think LLMs are bringing in something like a temporary golden age. And these parts of the world will be the last to have the lights go out on software simply because the low cost of living means there's a whole lot more slack to give before things get bad.
I am moving to somewhere cheaper, yes. Though since my passport is no longer strong (British), my choice/range of cheaper is a lot more limited.
Quality of life will not improve, because I will be lonelier (plus I have a great quality of life here in other ways, that many places cannot match) but I am mostly reconciled to that loss. I will have a fair bit more flexibility in use of space, which means I can be a bit more of a portfolio-earner; I do have some fringe skills that could make some money still, and I can have a little workshop or studio.
> But in these parts of the world, making a few bucks doing whatever in the software world goes so much further.
I am (undiagnosed but very obviously) ADHD and I don't tend to find it easy to make a sustainable income off "a few bucks" here and there; the effort expenditure in managing it always ends up subsidising the work. It's part of why I am burned out. I need thicker strands of work and those are fewer and further between.
I have little certainty when things will get bad, but I do think it likely it happens in the next five or six years, and I do know that when things do get bad they favour the young. Which I am not. It is clear to me that I am never getting an ordinary dayjob in the tech industry again.
I don't mean to sound particularly gloomy but I think mine is the generation whose lifespans will dramatically shorten. I think a lot of single middle aged people (men mostly) in the tech industry will choose the time and manner of their departure. Because we are deliberately creating both misery and job insecurity.
I don't think you're being gloomy so much as realistic. It's clear a lot of people either don't realize what's already happened, or are in some sort of denial about it. What you're saying is entirely true and was almost certainly also true during past eras of revolutionary leaps in technology. Fortunately in current times we have far more options than we did in the past, but realizing those options takes a bit of adventurism.
Since you already have that in you, I think you'll be surprised what you'll find - entire communities of interesting English speaking tech-oriented folks, many with more than a few grey hairs, would be just the start. And don't forget the teaching aspect. If you have a degree, smarts, some basic charisma, and can roll with a bit of chaos - you'll find plentiful opportunities to teach any topic imaginable. It's not just English, like many think. It's really quite fun!
I have taught/lectured the odd thing in my past and I can do it; I come from a family of teachers and it is in the blood.
I do not have the psychological constitution to teach kids so I am not going to do that.
But teaching/training adults is an industry that AI will destroy because the baseline income — the stuff nobody else wanted to do but you could earn from — will be eliminated, increasingly by policy directives from above. I have some ideas in that regard but it is difficult to see how I won't end up competing with LLMs when even open weights models are pretty good at coming up with tech tutorials etc.
Broadly I think there is undue optimism about what will be left to move to when the programming jobs dry up.
(Thank you for the discussion, though! I may sound quite negative but actually I am doing better than I have been for years, and it is always useful to provoke one's own thoughts)
Well there's a world of difference between teaching a 7 year old and teaching a 17 year old. I would say in both regards a more engaging style may be necessary than what you're possibly alluding to, so there is that. Depending on your background, teaching in a university is also completely viable. There's also the private lessons possibility. There's many options and I definitely wouldn't just write it off.
I don't think AI will touch education. A good case study there is Khanmigo which was to be Khan Academy's revolutionary AI tutor. There's been a million articles written about the topic. It completely failed, in spite of receiving massive sponsorship and imposition in various educational settings. And I'm kind of surprised that Khan himself didn't understand or predict this. As you probably know, great intrinsically motivated students don't really need teachers. You could give them a book or a sort of LLM tutor, and they'd excel completely independently. But then there are the other 95% of students you have to consider.
And those other 95% tend to fall into camps of either being a bit less gifted in the cognitive domain, or lacking motivation. Depending on exactly where they stand on the balance of two, a good teacher can have a huge impact, whereas 'go learn with the LLM for a few hours' would have them tune out instantly. It's because teaching isn't just about literally teaching, but about forming a rapport and trying to gradually push those 95% into more of the habits and patterns of the 5%, but without them realizing they're being pushed in that direction. An LLM there is almost entirely nonsensical.
Software is easy until it isn’t - the moment you need serious infra you’re in deep trouble and looking for an experienced partner or a saas solution anyway.
The days of b2b saas subscriptions doing one simple thing well for 3 or so users are however numbered.
Try getting something good out of fiverr or upwork. Even now it’s terrible (we get to clean up some the experiments). I agree maybe with the in house after enough years but that will also have a big effect on employees of those companies; a future (5+ years for sure as enterprises don’t move so fast) AI would need few resources to create and optimize and improve. I am not resisting my company won’t exist soon-ish; I am resisting that people see a bright future for devs here on HN. I don’t know where that comes from outside handwaiving ‘loom’ and ‘train’.
I know fiverr will start delivering nice software in 5 years and that’s what I worry about. By that time fiverr is probably just a chatbox though without humans, as what is the point?
The point is that button pushers currently simply don’t seem to be able to do this work, so it’s a little more than pushing some buttons. But no, I don’t think it will last very long, but few years more I guess looking at the competition and lack thereof.
What you describe does not sound all that much more than button pushing, TBH.
And your competition is not non-skilled people using AI to take your jobs. It is _cheaper people_ using AI to take your jobs. All the things that outsourcing teams used to struggle to match are much less of a struggle to match when you are actively depersonalising your own effort by handing it to Claude.
Don't underestimate the power of motivated reasoning. Certain people don't like AI coding for various ideological reasons, and so they will, not coincidentally, consistently fail to find it productive or helpful.
As long as we don't underestimate the power of motivated reasoning for other certain people as well, who like AI coding for various ideological or financial reasons.
That's why I don't believe most AI hate I read on HN and I don't believe much AI hype I read on X.
I mean sure if long term maintenance and code quality don’t matter then I wholeheartedly agree with you.
It’s spectacular for small projects, limited-scope apps (eg marketing campaigns etc) and for market-testable prototypes.
But if you don’t review and edit the code, things become unmaintainable soup very fast, with subtle logic bugs all over the place. And if you do review and edit the code, when working in large nontrivial codebases, then in my experience AI doesn’t actually go faster even if it feels like that at the start of each task.
Obviously this only holds if you have any sort of code quality standard to begin with (and I agree that with small / short-lived products you don’t need one)
in that case aren't you a completely useless middleman now?
The technical term is ‘meat proxy’
Can you elaborate on this with real-world examples you've experienced?
Not GP, but I can.
I'm currently working on porting a mid-sized project to a new architecture, new programming language and of course adding new features.
Getting a new feature implemented is quite easy. You spend a few hours brainstorming specs with the agent, then ask it to implement it. This gives you extremely frequent code drops that add a new brick, add a new feature, etc. All of this with 100% code coverage (we also have mutation testing, strongly-typed code, standard and custom linters, etc.)
Then you look at the code. Code that has passed review, generally. You realize that the database schema has been broken silently, and that the agent has rewritten the tests or the golden fixtures to match. You realize that it has made assumptions that contradict the specifications and the product is going to break once it's in the hand of users. You realize that the 100% code coverage is essentially a convenient lie, because the code and tests have been written to make passing easy. You realize that none of the security golden rules have been followed, and that has managed to happen because the agent has somehow deactivated linting.
Why did it pass reviews? Well, because of deadlines. And because there is simply so much code (and so much unparsable/misleading documentation) that it's simply impossible to review all of this. And because things move so fast that nobody understands the CI pipeline anymore, and the explanations of the agent are convincing enough that surely, it knows better than you?
On the upside, bugfixing becomes so fast! Just add a new test, wait a few dozen minutes, and a new Merge Request appears. With equally convincing/misleading explanations, and something else broken.
After ~4 months, we had a bare bones deliverable, which we're now steadily expanding. If we had had to write the product manually, I suspect that it would have taken us at least one year, possibly two. So, that's the productivity increase. The productivity decrease is that what we have is not a product but a glorified demo, something that will work very nicely on the happy path, but on any other path, all bets are off.
Thankyou for putting the last three months of my life into words <3
> and the explanations of the agent are convincing enough that surely, it knows better than you.
I feel this in my bones. I also get to watch the misalignment feedback loop close itself when the next agent sees that security rules aren't followed because of a hallucinated 20 line justification in a code comment, and then it decides that the project _is_ a demo and then confidently writes even more security holes into the codebase.
Then when you catch the issue, the agent pushes back against the fix because it would need a schema change and production DB migration.
First is don't trust the code review from your local harness, even if it uses sub-agents; externalize it into another system.
Second is to get your most critical human code reviewers to encode their heuristics in markdown files and feed those to the code review agents.
Third, if possible, is to bring the code review "into the loop" so that it's not only running in the PR, but also running in the coding loop so the coding agent has immediate, external feedback. Final PR code review is a backstop.
This pattern [0] works well because it solves for some team level problems where folks are using different harnesses or different models (consistency issues) and it means that code reviews don't just sit at the end of the loop; it actively alters the code production cycle.
[0] https://zeeq.ai/docs/key-features/code-review-tool
But why did it pass the reviews of the independent subagents whose sole job it is to check all those things?
They are very good at that.
In my experience, they are fairly good at catching stuff in human-written code, but they tend to gloss over agent-written code, just as human beings being lulled to complacency by superficially-looking competent code.
One thing we've noticed is that if you have model X implement AND review the same change, the reviewer often shares the same blind spots as the implementer. https://blog.brokk.ai/mjolnir-automated-cross-vendor-adversa...
This is the interesting bit
> "Why did it pass reviews? Well, because of deadlines. And because there is simply so much code (and so much unparsable/misleading documentation) that it's simply impossible to review all of this. And because things move so fast that nobody understands the CI pipeline anymore, and the explanations of the agent are convincing enough that surely, it knows better than you?"
I have come to realize that AI is so "successful" because the system in which it is being deployed was designed to push product as fast and cheaply as possible from the start.
Humans are usually overworked and stretched to their breaking point, which I originally saw as the source of our broken software woes, which, like our streets in the US, just get a new layer of asphalt to cover up the crumbling bits each year instead of rebuilding the infrastructure with reliability and longevity in mind.
My former employer was using both Claude and Codex for firmware that was driving an over-burdened power circuit that itself was partially designed with ChatGPT. All of the individuals involved approach LLMs with god-fearing reverance because they do not understand _how_ the LLM works, just that it _does_ in a "good enough" way and they can offload their thinking, which is something we all wish we could do because thinking is hard, time-consuming and costly. I get it.
But like you mentioned, tests were being passed, not because the code was sound, but because the tests were altered to match the results. This is not necessarily the fault of the agent, either; it's just interpretting the prompt(s) - written by a flawed human, btw - with stochastic mechinations that seem to make a great deal of sense on the surface, but remain unable to be followed or repeated by the brains of (most of) its users.
As a rresult, I had to deal with product that work great in the field...at least at first, before it start literally catching fire, ruining its own powertrain because everything the agents touched became too complex with too many subtle cracks in the veneer to review properly. The system (read; capitalism) demanded viable product quickly to please investors, and the burnt-out humans who decided to try this AI thing ended up trusting it nearly completely, so any ideas of repeatable and complete testing, diagnostics and root cause failure analysis morphed into a sloppy "it works on the bench" checklist before being sold to a customer who had come to trust that their deceptively simple product would just work as advertised.
I'm going to die on the hill that AI as a replacement for our brains is precisely how we will make ourselves go extict, but I am old enough to already be regarded as a crufty dinosaur who is stuck in his ways, and I'm made peace with all of that. What I can't get my head around is watching people use this awesome tool (and it is, admittedly, awesome) to literally just speed up all the mistakes they were already making. Perhaps it is because I am aging, but slowing down and having a think seems more valuable to me now than it ever has, especially when creating something new. AI is powerful and, like any good tool, could be useful in the right hands, but more often than not I see it being used as an accelerant for all the worst parts of product development to appease a market that has suddenly been told they can now pick all three points on the Iron Triangle instead of just two. This makes about as much sense to me as taking a laxitive when you already are suffering diarrhea.
AI amplifies existing process. For people without sufficient clarity I imagine it amplifies that lack of clarity, which is where it is factually unproductive while it still ‘seems’ to be productive (producing slop).
At the end of the day, LLMs are still tools.
Yeah, that gives me the scary feeling that especially here people are overvalueing themselves by a lot. They find AI counterproductive because they simply never were good at what they do before AI. This is always always my read of people who value talking, meetings and office time as important: I have never met people who have that and who are not sales or just plain suck at their job; AI amplifies that. Also with salespeople who now send me presentations that just have a bucket loads of hallucinations in them: turns out they never read them but had interns write most of them: now they still cannot read and AI generated stuff looks plausible. I only have anecdotal experiences but this sure seems to resonate for the AI negativity around here. I could be wrong but it's so far removed from our experiences.
LLMs are just tools indeed.
You don’t value “talk”? I understand. I have a lot of those around me and they are super productive, all day, alone, in their little cubicles. Oblivious to everything around them.
I don’t know what to say to those types anymore. Live and let live I guess.. or in this case, not live I suppose.
It usually is more like; I send an email or so which contains enough details to understand whatever we are doing. A person in that list sends it to 20 people. The next email is a zoom invite with 30 people of 1.5 hours to ‘go over the email together’. If these people have no influence, good or bad over the outcome, why would I waste this time while it usually just says they were too lazy or incompetent to read the email?
Useful talk and meetings all day is fine, but these are just to write busy/billable hours for all these useless folk with no value for the project. And socially I like listening and talking, just not for this.
> For people without sufficient clarity I imagine it amplifies that lack of clarity, which is where it is factually unproductive while it still ‘seem’ to be productive
Convenient way of saying "you're holding it wrong".
Yes, that's what I'm saying.
I get flamed here whenever I say it's a skill issue, but it absolutely is. Not everyone has what it takes to be a successful CTO but that's the role you play if have 20 agents working on something you designed. I see you got downvoted too.
It would be a skill issue if someone would show they’re able to use it to produce good software while showcasing that it’s due to their mastery. Till this day, I don’t think there’s any such demonstration. Any defects of the technology is always blamed on skill issue.
People who produce good software don't feel the need to show off how modern and agentic they are.
We don't want them to show off, just make public software we can pay and use. What's yours?
There's a ton of people out there in various unknown companies grinding away and managing a reasonable number of well-prompted, parallel agents with decent CI and deployment strategy making judicious use of human review.
But that's boring and you can't build a YouTube audience around it.
Then when asked for examples of what they built using AI, what they have to show is boring slop worse than "git cloning" a mature project.
People who build good software with AI don't gloat about it being built with AI because it's not the most relevant part of it.
What had he produced in the years prior to AI getting good enough for coding? All I know is he was on Zuckerberg's sinking metaverse boat for years, and then nothing else.
Maybe it's him, maybe it's his employer. I don't know. I am skeptical of AI's impact on work myself but I just don't think AI is the only thing to blame here.
Oculus was pretty fun and a really nice piece of hardware. What was painful was all the meta things on top of it, which I doubt was something he personally added.
But he didn’t build the Oculus did he? Not sure what he worked on, software?
But as he has little to show the last decades we have very little reason to listen to him over some random blogger.
> Carmack hasn't produced anything noteworthy since AI was invented, therefore, how productive can it really be?
He's been spinning his wheels for a while. Carmack is a great example of how important working on the right stuff is. He's undoubtedly a brilliant programmer. Through him we get to see that a brilliant programmer working on non-programming tasks, can produce nothing.
Carmack hasn't produced anything genuinely noteworthy after leaving id software, if we are being frank. His work at Armadillo aerospace was more akin to hobby, not really leading anywhere, a VR stint at facebook, again, is difficult to gauge at how large his personal contribution was, and this new AI thing is likely end with him leaving the company, again.
Carmack is an amazing engineer, a genius even, but either the age of the individual contributor creating the entire thing from the ground up is over, and he's bored of it, trying to find a niche where this still works, or he is exploring the areas in which to apply his curiosity.
What I'm saying is that his current productivity or lack of thereof isn't a marker of how AI is productive (or not) in general
Its very different living in the late 80s to early 90s coming up with cool ideas that push affordable hardware to their limits just like John Carmack did with games like Keen, Wolf3d, Doom and Quake.
It was at an era where someone good at their craft can get the recognition they deserve. However, while some things he managed to figure out himself.. other things were ideas from others. He simply tried it and reviewed the results!
Looking in the games industry today - an 'individual' is not going to get the same recognition like John Carmack back in the day (or Ken Silverman, etc)
This industry is LARGE. Any god-like programmer trying things within a large corporation is not likely to get noticed today as they hide away in the background pushing an in-house games engine forward. I am sure there are a fair number of John Carmacks out there. Invisible... nameless legends pushing things, etc.
As for indie companies - why risk trying to be a 2026 version of John Carmack when Godot, Unreal, etc, exists. Its a different world today!
Same thing for AI. I bet there have been some legendary programmers working on AI in the last 10 years. Again, nameless individuals behind the brand.
If any names are mentioned... its likely CEO's or other higher ups... not the talent underneath. I guess thats good business strategy and works [for the business].
Focusing on John Carmack - I am not taking anything away from him. He is a legend. I am sure he contributed towards VR before and after Meta purchase. With AI.. I guess we will see.
At the end of the day the guy could walk away and focus on hobbies. Still has a lot of batteries left. More power to him.
Actually, I'd expect someone like Carmack to be the least productive with AI. Carmack focused his career on high-performance 3d graphics tricks. Those are free now. What isn't free is knowing how to use them. In other words, the game engine is free, the game maps/zones/levels are costly. The "John Romero" part of the equation. Let's see what the idea people are making, not the code gurus.
I can achieve more with AI than without.
What's the complain exactly?
That AI still hasn't made my effort and thinking and directing and checking and ideas completely redundant and thus out of job?
It's like you people see everything in black and white and miss that most of the real world is a gradient of shades of grey and quite never full black or white.
> It's like you people see everything in black and white and miss that most of the real world is a gradient of shades of grey and quite never full black or white.
I’d go even further. Shades of grey implies two extremes on a linear scale, but the world has colour, meaning wildly different interpretations that go in novel directions.
However, ironically, your comment reads to me as extremely black and white—full of certainty, rigidity, possibly some bad faith interpretation and straw manning—while the one you’re criticising has (some) nuance and doubt and seems open to the idea of being wrong.
> What's the complain exactly?
What complain? OP asked a question. Carmack created Doom, Quake in 2, 3 years. What has he created in 4 years of AI? Should be exceptional if one of the most productive programmers ever says it makes him more productive.
What does he have to show?
That reminds me of something on my last job. Before AI, we had not so good communication, but if we had a question, the person on the other end will try to give you a passable answer. After AI, everyone seems to be a proxy for the LLM tools they're using and any misleading statement you point out is answered by "Why don't you use $llm_tool to check it out?".
You're comparing the challenge of building game engines in the 90's with the more open-ended AGI research. It's different enough that I don't think it's valid to conclude he's less productive now based on impact over time.
Silly question.
He's doing research, not product work now.
So people are right to say he has nothing to show to back his claims.
This is... not a great take.
I'm a practical optimist. I see us as being in the age of engineering for AI -- like the early days of the steam engine. We're going to get a ton of things wrong and impractically implemented. But we don't anticipate the train conductor to build the steam engine on their train -- we just expect it to work as targeted.
(Note I'm not being pollyannish here -- a lot of codegen downright sucks).
This comment frames it like he's a known vibecoder, is he?
As opposed to producing great things without AI? He hasn’t produced anything impressive since 90s/early 00s.
Well said, Kung fu master
I mean.. I'd bet he has certainly made a lot more money since AI arrived than he did before
Sure, among all these other people doing 'incredible work' for 30+ years publicly, well into their 50s, John Carmack sure is a disappointment by comparison.
I sense sarcasm. But I think you misinterpreted the parent’s point. I read it as: yes, Carmack has made huge contributions but, has not publicly released anything noteworthy since the advent of AI coding. Of course that doesn’t mean he won’t, just that so far nothing he released has backed up his statement.
Can you imagine a football fan going up to Ronaldo and saying hey, I saw an interview you did last week - I think you may be lost in the weeds there with your training regimen and outlook. I want to let you know - I remain a skeptic.
I mean, when you start scoring goals like you did 5 years ago Ronaldo, but until then, I remain a skeptic about that training regimen.
As for misinterpreting - maybe you're misinterpreting. Or maybe it's unproductive and dare I say presumptuous to reply to people you know nothing about with 'you're probably wrong and I'm probably right'. Do you do that in real life? Working out great, I can only assume given you've adopted a similar approach here, or?
Did Ronaldo say he's never been a better football player?
Do you believe a 50 year old software engineer is mentally no longer able to work?
Should they be forced to sit back and tell stories of the good old days because their knees are blown out?
Do you believe that one of the greatest living programmers is so washed up at 50 that _even with the greatest LLM tools_ cannot ship something publicly in four years to back up his claims?
I would rather listen to someone with current merits than someone who has not produced anything notable in years. Especially if the topic is current trends in software development.
I mean his post boils down to "Get on the bandwagon because you might otherwise miss out. All the cool kids do AI now."
There are valid concerns there (and you should probably be playing around with LLMs), but he voiced none of them. He just led with a metaphor about obsolescence and then continued spreading FOMO with an authoritative voice.
Perhaps he is actually lamenting being the out of touch kung fu master, but his pride won't allow him to articulate the ways in which he identifies with that?
He also runs an AI company now called Keen something. So he’s yet another biased hypester at this point.
Would a person who is lost in the weeds come up with such excellent though-formulations like this?
> Musashi would probably have been pretty enthusiastic about assault rifles.
Musashi famously "retired to a cave, Reigandō, living as a hermit to write The Book of Five Rings" (https://en.wikipedia.org/wiki/Miyamoto_Musashi), for those not in the know.
Edit: Had to re-read a bunch of stuff about Musashi, and to Carmack's credit, seems to have been a relatively pragmatic guy when it comes to the choice of weapons in a battle, talking both about the benefits and drawbacks of firearms (although they were slightly different ones than we have today)
I’d be pretty relieved, too, if I thought the scope of AI’s impact could be described by just an assault rifle.
“Fun” fact: Even the creator of one of the most widely recognised and used assault riffles wasn’t enthusiastic about it by the end.
https://www.npr.org/sections/thetwo-way/2014/01/13/262096410...
> WorldEnder
> Its just that, it used to be free. All I needed was a computer.
https://xcancel.com/rustishard/status/2098853622263976328#m
Same here.
In particular regarding free as in freedom, so about access and control. Just like I never enjoyed working with proprietary coding platforms, OS, or IDEs, I’m not particularly excited about proprietary models.
Check out DeepSeek v4.1 Flash, just released, and I am enjoying it more than Claude. No one can run it locally.. Yet.. But give it a few years and I wouldn't be surprised if models of that capability were standard for programming laptops.
We don't know the training set so it's still not very transparent - and means giving away some control. Then again, it does look better than closed weights
His analogy might be accidentally appropriate given MMA-fighters propensity to develop CTE.
Common table expression?
> Chronic traumatic encephalopathy (CTE) is a progressive degenerative brain disease caused by repeated head injuries and hits to the head.
Fighting is competitive and single-minded in a way that programming very much is not. The purpose of fighting is to defeat, often kill, an enemy who wants to do the same thing to you. In that world, there’s no room for anything but the most advanced techniques and technology.
Most jobs, programming included, aren’t like that at all. There’s an element of competition, but you don’t get killed by somebody who does it better. Maybe they get paid more, but you can still have a job too.
I read this advice like: in a world of backhoes, don’t be a guy with a shovel. Except a guy with a shovel is still very useful in the modern world. Backhoes are great but can’t do everything. And even for jobs they can, the shovel might be good enough.
It does say something about our culture, doesn't it? That something as mundane and non-violent as computer programming gets compared with violent combat.
I suppose it comes down to how hyper-competitive some people are, particularly the "greats", that working on software is in the same category as fisticuffs.
Why are we always at war?
Because someone profits from it. If your man had truly embraced Zen after, y’know, becoming wealthy enough to never need anything, it feels like freedom from want would have come pretty easy. Instead we have to find our examples in poor people after they die.
This post brought to you by DraftKings. Reach Nirvana and its five bucks off your next bet on the Bardo!
It's funny, but to relax I was reading Tim Berners-Lee's FAQ for kids. He has a section about "I'm interested in Math -- what exciting stuff is there we don't do at school?". He quickly sketches out what ideas might get us to Maxwell's Equation, ironically enough. But, what a joy it is to see a person who believes in the public domain, and who we have everything to thank for right now, saying "The main thing is, to have fun."
https://www.w3.org/People/Berners-Lee/Kids.html
Competition drives innovation
There is a purely strategic reason for keeping some hand code skills exercised. If you outsource the coding away completely you become dependent on entities that can pull the plug on you. Not arguing it's the right choice to rein in the agentic coding just that there is some rationale for doing so
So, more people are excited for the vision of Idiocracy to be fully realized.
> The introduction chronicled the evolution of swordsmanship and martial arts in general from pragmatic battlefield necessities to sports, historical curiosities, and hobbies.
Eh? Martial arts has always been a mix of utility and cultural artifact.
Greco-Roman wrestling flourished in a/alongside of military utility. Greeks and Romans had swords, shields, spears, bows and arrows. Boxing also traces its history all the way back to the Greeks.
Japanese, Korean, and Chinese arts developed in a society with, also, swords, shields, spears, bows and arrows. Notably these cultures often included weapons training ("kobudo" in Japanese) in their curriculum but that did not phase out the empty-handed aspect of the art.
Catch wrestling developed among sailors who would not be strangers to guns and rifles.
BJJ developed, well, today.
There has always been a component of sportsmanship and self-improvement in martial arts. Carmack misreads this introduction, methinks.
https://news.ycombinator.com/item?id=49668392
I don't think with the models we have, you shouldn't need to even write a single line of code. What you need is to prompt it right, check for over engineering, check for edge cases, test it very thoroughly. That means don't accept it writing 10,000 lines of code that you cannot review or test properly. Make modules small enough that can be reviewed/tested properly.
I like ai, with IT i can Program again, after being Out of Touch with it for some years. I can Focus in the Thing i actually want to do instead of setting Up 5 different ENVs only to find out that the Framework only works with an Intel processor
Shut up and show us the code, Carmack! Now that you take AI money, you are a hollow influencer.
BTW, for you it would have been pretty bad if coding had been solved in the Quake-3 era. Quake-3 was technically sound but had excruciatingly boring and bland gameplay.
Fortunately, coding has not been solved.
Is there a name for this pervasive psychological phenomenon where someone reads an ancient text and becomes convinced of its profound relevance to their own field? Seems to be especially common amongst the influencers of the tech sphere.
> But don’t be the out of touch Kung Fu master, heir to lifetimes of tradition, that gets mauled by an amateur MMA fighter.
Seems like a fundamentally poor analogy. Software development is collaborative, not competitive.
Within a company it's collaborative. Between companies it's absolutely competitive.
Open source is collaborative, and isn't exactly a niche thing, even at commercial companies.
Again, within the project sure. But there is fierce competition between different open-source projects!
Use and learn the tools, even if it sucks and is painful. It does not take long to feel how they work at all.
Once you have that you can pick and choose when to engage this new tool at will to "not fall behind."
It doesn't have to be all or nothing.
Yep. Having to type the code is a form of accidental complexity, and with it gone, you can focus more on the problem to solve, getting it down faster.
Of course it's possible for it to go off the rails. Consider that a wildly swung sword can do damage you can't do with your bare hands. To prevent this, constrain your model to the solution shape you want by grounding it; give it contact with reality; ways to run the code it's generating and refine it to meet your goals; granular tests; etc.
The new job is in how you wield the tools and it is at least as complex as the old.
I guess in ten years we'll see which is the out of touch Kung Fu master.
I do see a whole set of people doing mystical passes in the air, sometimes with wires holding 'em up, in a set of ritual beliefs propped up by vast accumulations of power, money and pride, not to be questioned.
Didn't expect Carmack to be among those waving his hands about.
If it's so amazing, let's see the amazing thing he does. Go ahead. I'm sure Doom needs a really on-point web page with Inter.
So what does this guy have to show for working on AI research for more than half a decade at this point? Apparently full time too.
Why is Carmack still someone we look up to in the present? I'm aware of what he did in the past but compared to the likes of Torvalds and Bellard he doesn't seem to still be doing anything noteworthy other than yet another AI company.
My problem with AI is not that they aren't useful, John. Like everything else in life the question is what we shape ourselves to be as a culture, as a community, what is the path we want to take. It's not on the same scale than ditching assembly instruction for a C compiler.
I get why most people get with the flow of what competition taught us: if you can't fight them join them. Yet I think it's demoralising we're forced to live the life forced upon us by a few techbros without real collective intelligence about the use of our resources and goals for the future. Again, it always has been a bit like that but never at this scale.
We're souless automatons feeding a machine god.
> Musashi would probably have been pretty enthusiastic about assault rifles.
Cringed.
He and others can host their brain in the cloud for all i care.
Would love to see Carmack create a product with AI, instead of stealth promoting his shovel company on the worst website on the internet.
It would seem that the AI craze has shown a flaw in stereotypical "software engineers": an obsession over quantity and speed over everything else. A desire to belong to the group, a desire to exhibit the fact that they are not being left behind. While FOMO is a thing for all peoples, those in tech are particularly susceptible, given the nature of the field.
I have yet to see evidence that AI produces code that is higher in quality than human-written code. I have yet to see anyone show that burning through tokens is economically smarter than paying human engineers. All that is being revealed is how companies and software engineers truly feel about the work they do.
This technology is impressive, and we cannot doubt this. However, it seems that those within Silicon Valley are desperate to showcase the innovative spirit which has been absent for two decades.
> obsession over quantity and speed over everything else
i think this is a problem larger than just programming; we see it everywhere in western(ish) culture more and more ime....
Andre,
I agree with you wholeheartedly; I was just talking with one of my friends yesterday about this. I don't think AI is causing most of the problems we are discussing, it is simply exacerbating them to such a degree that they are hard to ignore.
thanks for the thoughtful reply ^^
yes, regardless how one feels about "ai", its obvious to me its basically gasoline being dumped on this "faster and more" culture we are all suffering from...
Also, don’t be the one who fights sharp swords with Marvin Minsky’s useless boxes.
I also code as a hobby. It seems like a pretty good thing to have as a hobby.
Resubmission of I recently went through a translation of Musashi's Book of Five Rings - https://news.ycombinator.com/item?id=49660833 (1 comment)
I assume he’s referring to videos like this? https://youtu.be/gEDaCIDvj6I
If so… Very poor choice of metaphor. Nothing resembles AI coding quite so much as the mystical master waving his hands in karate-style movements, seeing dozens of his opponents helplessly bowl themselves over, and eventually coming to believe he truly has the power to defeat any enemy.
If I still edited videos I would have “make no mistakes” fly out of his hands, and the students would have little “you’re absolutely right” and “that’s on me” captions on them as they flip themselves over.
Definitely felt like that stubbornly avoiding TypeScript for too long. My projects eventually forced me to adapt or be left behind.
Don’t tell me what to do
The author of the work that John Carmack is referencing is named Musashi, which is also the (coincidental?) name of a WW2 Japanese Yamato class battleship, which is quite fitting. Musashi the battleship having met its end at the hand of carrier launched aircraft, which remain a dominant technology to this day.
Aircraft carriers are to a small extent superseded in their own right by strategic bombers and ballistic missiles. We may see nuclear aircraft carriers eventually superseded to some extent by missile/drone swarms and missile/drone deployment platforms, or some other threat.
If the new dominant technology, military in the sense of being used to dominate your adversaries in any arena, relies on data centers, is that infrastructure considered pretty robust? Will that data center infrastructure fully supersede the nuclear powered aircraft carriers, as has been done to battleships? Do hardened data centers and the software they run represent the main locus of national front line capability? Are AI researchers more like WW2 pilots, or are they more akin to the people who worked on the Manhattan project?
This post makes me think harder about physical computer infrastructure. Continuing the metaphor, silicon fabs, computer manufacturing supply chains and their related infrastructure are certainly the WW2 drydocks of our modern conflict, the WW2 drydocks having been critical for the Americans to churn out aircraft carriers. And the drydocks were only one piece, but might have been considered one of the most brittle.
Some seemingly brittle pieces of AI/data center infrastructure today are the fabs and the communication links. As far as I know, the fiber optic cables connecting continents are so exposed it's almost ridiculous, the cables lay directly on the ocean floor. If severing these links favors one or another global actor, my main question is why hasn't this already been done? You can ask the same questions about severing oil pipelines and the various global shipping chokepoints. I do wonder if fiber optic cables are defensible at all in the final analysis. And what life would/will be like without fiber optic connection between continents.
I'm not sure how much more durable satellite links are, due to the cascading debris effects of Kessler syndrome.
A key idea is that if the transoceanic communication links between the Americas and Eurasia were to be cut, either powers based in Eurasia or a power based in the Americas would gain an advantage.
Semiconductor fabs... Well, if I were a military strategist in charge of national security, I definitely wouldn't publish the location of every fab. And a a self respecting superpower wouldn't leave its EUV machine production external, or would it?
Fabless semiconductor companies and AI researchers are critical to current national security capabilities in the way that people who developed radar were critical to WWII. In the long enough term some people think that eventually data centers and the software running inside will supersede and encompass these functions. The question being increasingly not if, but when. Some people think that if it can be done by a computer, it eventually will be.
It really is all about timing, the Japanese thought the Pacific conflict with the USA would be short.
John, if the introduction of the translation of Book of Five Rings is so good, could you please share the identifying information including the translator or the person who wrote the introduction?
It's a good analogy that's probably occurred independently to a lot of us. Here's my version from a private email a few weeks ago:
> [...] I don't like the "great equalizer" effect. [...] Like a kung-fu expert who wandered into a wild-west saloon of drunks all packing six-shooters. (I'm still working on this metaphor.)
Might as well share the entire off-the-cuff email, replying to a great software engineer friend who recently went academic, when they asked what I thought about AI development.
> "You're absolutely right," as the chatbots say.
> I think Claude Code (which I think is currently regarded as the best brand for software development) is for banging out *something* when you don't care so much about the quality. Like most applications of generative AI (homework cheating, customer service, usual corporate ticket-closing).
> And I'm definitely not thinking through the problem very well. The first time I noticed this was on UI design, where Claude would emit a generic *something*, and then the mode is to make incremental tweaks, rather than going through the mental exercises and holistic thinking.
> So sometimes I'm thinking like a non-technical manager, giving initial spec, and then iterating on things I notice -- not thinking like a designer, architect, or engineer.
> Or, like a senior engineer who has to mentor a hyperactive intern who bullshits and plagiarizes like crazy, and makes empty apologies like a sociopath when caught, but is the CEO's nephew, so you can't just fire and blacklist them. You just have to get *something* out of them.
> I can do much better design and better implementation myself, but it's good enough. And it's better than at least half the industry software engineers, so a lot of people who never cared much nor got very good, are in trouble. And management is often a poor judge of skill, if they even care.
> Besides the questions of its performance and utility, and all the ethics questions, I don't like the "great equalizer" effect. Now a lot more people can do (or seem to do) many of things I can do. And I'm having a lot of trouble job-hunting, and companies mostly want people to be using or building AI. Hence learning the robo-plagiarism tools. Like a kung-fu expert who wandered into a wild-west saloon of drunks all packing six-shooters. (I'm still working on this metaphor.)
That conversation might've started when I showed friend my new gen-AI portfolio site, so the context would be realist assessment and handling it, spoken to someone who already knows I'm an enthusiastic hardcore engineer.
I mean, there is still a place in the world for a Kung Fu master… it’s just not as someone trying to win in an anything goes combat competition.
If you think there are going to be as many jobs in the future for people writing all their code by hand, I hate to break it to you. However, there will still be some jobs, and fewer people who want to do it. It will still be a path for some people.
Slop posting
So, don't be John Carmack. Got it.
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HN is loaded with out of touch Kung Fu masters. They were the loudest skeptics against AI. Still a lot here.
It's human nature. If your identity is defined by your kung fu and a technology is about to obsolesce your kung fu, then all logic goes out the window as you go all out in protecting your identity. It's mostly for themselves. They have to lie to themselves and tell themselves that they still "matter".
I've been doing martial arts for more than 20 years, some in TMA, some in modern boxing/kickboxing. I have yet to meet an "out of touch Kung Fu master" in person. Nobody thinks they can clear the bar or win in a ruleset they haven't trained for. I mean I don't deny Frank Dux, George Dilman, and the DUST guy exist, nor do I support their claims. It's just that they are larger-than-life personalities to start with and I haven't met them in person.
Similarly, most of the programmers skeptical about AI---me included---don't really do so out of a threat to a domain we've mastered. The problem is, models, to this day, need supervision so they understand requirements, so they know where to properly look for prior art, so that they "understand" the existing architecture. That includes you, Claude. Our kung fu has been six months away from obsolescence since roundabouts 2022 and in 2026 they even rehired a bunch of out-of-touch kung fu masters.
>It's just that they are larger-than-life personalities
That is a very generous assessment of Frank Dux and George Dillman.
Dillman at least started off as the real deal. Dux was a total fantasist. I still find it hard to believe any bought into his 'blood sport' story, let alone made a film about it.
People who are out of touch don’t know they are out of touch. Thats why you haven’t met one. Because they all declare themselves as relevant. And this is also why you can’t recognize yourself as out of touch.
How do you recognize someone who isn’t lying to themselves? It’s hard. There’s no definitive answer but lies people tell themselves tend to be rosy and comforting. When someone tells you their own identity has been eviscrerated by AI that’s not a comforting lie. It’s more than likely a practical analysis.
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It's funny that we almost agree except you have it 100% backwards.
The out of touch kung fu masters are all retired or close to it. They continue to shout about their big bet on AI as loudly as possible to protect their egos and, as a last ditch effort, whatever money they threw in.
After all, everyone who is mid-career and younger cannot possibly be a master of anything. Of course they're using AI at work, but that is an extremely far cry from the AI actually helping. They use it because it's shoved down their throats and they don't want to rock the boat. Working extra hours from home is the perfect way for everyone to save face.
In other words, the older generation is delusional. Nobody is surprised except the older generation.
I never commented on age. So we are actually in perfect agreement. Yes, older people tend to have their identities and expertises ingrained. They have more to lose in terms of identity.
I honestly feel personally attacked by this and I don't consider myself to be an out of touch kung fu master or technologist at all. It is just very odd to read such an inflammatory comment on HN and then have people pretend this is correct and perfectly socially acceptable to say.
Like put your shoes into the person you are arguing against, with some empathy, would you want to be treated this way?
Funny thing coming from a person with such a bio.
You feel attacked? I’m only referring people who are out of touch and lying to themselves. If you’re not doing that then it’s not you.
Unless if you feel it’s referring to you then you’re saying what I said is true. If what I said is true, then it’s not an attack is it? I’m just spitting facts. So don’t get offended, don’t think of it as an attack.