It's hard to discriminate out just one specific thing, but a batch of generally connected stuff:
1. I've been doing a lot of experimenting with neuromorphic and analog computing. ChatGPT has been my research assistant / lab partner throughout and has helped with doing experiment write-ups, analyzing scope waveforms (it's really impressive how good it is at parsing screnshots from the scope, using the graticule / divisions, and other on-screen indicators to figure things out), finding reference material, and providing general electronics advice. I've learned a TON of new stuff about using my oscilloscope, using some features I'd never used before.[1]
2. Along with that, I'd long wanted to get my lab all set up to use LXI for remotely controlling all (well, "most") of my test equipment. Once I did the work of physically connecting all of the instruments to the LAN, ChatGPT wrote most of the first cut of a batch of Python programs using PyVISA to control the various instruments (oscilloscope, function generator, power supply, multimeter, programmable load) and to download data from them.
3. I'd been "meaning to learn KiCAD one day" for about 15 years. About a month ago I said something to that effect to ChatGPT and it handily replied "I can help you with that." About 6 or 7 hours later I was sending Gerbers to JLCPCB with my first custom PCB design, and 4 days later I had my first boards in my hand. Soldered one up and it worked first time! Yay. Now granted, the circuit was VERY simple (a 555 timer blinking an LED) but the point was to learn the tool and the workflow, not the actual end product. About two weeks later I started on my second board, planning to do it with much less AI assistance (I worry a lot about cognitive abdication / brain-rot / etc). But right out of the gate, I ran into the point that KiCAD did not have a symbol for an obsolete component I was using (the 2N6027 PUT). So I turned to ChatGPT again and it helped me create a custom symbol. After that little diversion, I went back to the schematic and board layout. This time around, it only took about 85 "turns" with the AI to get to "Gerbers sent to JLCPCB" whereas the first time it took about 120 "turns". So I'm feeling pretty good that I am actually learning and retaining some of this knowledge and not "just following instructions from the AI". I do hope to get to the point soon of doing a board with NO assistance from the AI whatsoever.
Those are the ones that stand to me. There's other stuff of course, but those are ones that have really made a difference for me and/or really impressed me.
[1]: One thing I did that helped a lot, was creating a "Project" and uploading all of the user manuals and programming guides for my various instruments. So the GPT always has access to the actual documentation and doesn't have to rely on its "memory".
I have also found that AI has accelerated my learning. Rather than spending time searching for the right material, it just presents the material and guides you as you work through the topics.
Yep. Another thing I do, is ask all sorts of weird questions about various things that pop into my mind, and after it explains a bunch of stuff to me, I ask it "write up a summary of all of that and put it in a file in $APPROPRIATE_GIT_REPO".
I do have it configured to use the Github MCP server and have given it access to 3 or 4 of my repos. Along with that, I put an AGENTS.md file in each repo and gave ChatGPT in general a custom instruction that says "at the beginning of each session, or when prompted by the user, consult the appropriate AGENTS.md file and follow the instructions found there."
I then keep various files in the various repos that catalog our discussions, decisions, speculations about future research directions, yadda, yadda, yadda. And I "incorporate by reference" by mentioning those files in the AGENTS.md. Setting all that up took some work, but it makes the AI much more reliable than trusting it to rely on its "memory".
It's hard to discriminate out just one specific thing, but a batch of generally connected stuff:
1. I've been doing a lot of experimenting with neuromorphic and analog computing. ChatGPT has been my research assistant / lab partner throughout and has helped with doing experiment write-ups, analyzing scope waveforms (it's really impressive how good it is at parsing screnshots from the scope, using the graticule / divisions, and other on-screen indicators to figure things out), finding reference material, and providing general electronics advice. I've learned a TON of new stuff about using my oscilloscope, using some features I'd never used before.[1]
2. Along with that, I'd long wanted to get my lab all set up to use LXI for remotely controlling all (well, "most") of my test equipment. Once I did the work of physically connecting all of the instruments to the LAN, ChatGPT wrote most of the first cut of a batch of Python programs using PyVISA to control the various instruments (oscilloscope, function generator, power supply, multimeter, programmable load) and to download data from them.
3. I'd been "meaning to learn KiCAD one day" for about 15 years. About a month ago I said something to that effect to ChatGPT and it handily replied "I can help you with that." About 6 or 7 hours later I was sending Gerbers to JLCPCB with my first custom PCB design, and 4 days later I had my first boards in my hand. Soldered one up and it worked first time! Yay. Now granted, the circuit was VERY simple (a 555 timer blinking an LED) but the point was to learn the tool and the workflow, not the actual end product. About two weeks later I started on my second board, planning to do it with much less AI assistance (I worry a lot about cognitive abdication / brain-rot / etc). But right out of the gate, I ran into the point that KiCAD did not have a symbol for an obsolete component I was using (the 2N6027 PUT). So I turned to ChatGPT again and it helped me create a custom symbol. After that little diversion, I went back to the schematic and board layout. This time around, it only took about 85 "turns" with the AI to get to "Gerbers sent to JLCPCB" whereas the first time it took about 120 "turns". So I'm feeling pretty good that I am actually learning and retaining some of this knowledge and not "just following instructions from the AI". I do hope to get to the point soon of doing a board with NO assistance from the AI whatsoever.
Those are the ones that stand to me. There's other stuff of course, but those are ones that have really made a difference for me and/or really impressed me.
[1]: One thing I did that helped a lot, was creating a "Project" and uploading all of the user manuals and programming guides for my various instruments. So the GPT always has access to the actual documentation and doesn't have to rely on its "memory".
I have also found that AI has accelerated my learning. Rather than spending time searching for the right material, it just presents the material and guides you as you work through the topics.
Yep. Another thing I do, is ask all sorts of weird questions about various things that pop into my mind, and after it explains a bunch of stuff to me, I ask it "write up a summary of all of that and put it in a file in $APPROPRIATE_GIT_REPO".
I do have it configured to use the Github MCP server and have given it access to 3 or 4 of my repos. Along with that, I put an AGENTS.md file in each repo and gave ChatGPT in general a custom instruction that says "at the beginning of each session, or when prompted by the user, consult the appropriate AGENTS.md file and follow the instructions found there."
I then keep various files in the various repos that catalog our discussions, decisions, speculations about future research directions, yadda, yadda, yadda. And I "incorporate by reference" by mentioning those files in the AGENTS.md. Setting all that up took some work, but it makes the AI much more reliable than trusting it to rely on its "memory".