The core concept is to have a frontier or very smart model run as an agent first for N times. The model get tools, skills etc and instructions. It does the job. At the end it leaves a note (like a retro) explaining what it did and what it could have done better.
As the agent runs, it also writes workflows to do the parts of the job it knows it can do in a more deterministic way (based on previous nodes and thinking traces of other runs etc). We made a dsl for this that has routing, classification, code nodes, etc to build these workflows.
For repetitive tasks (which is our focus) we find that after ~100 cases, the agent most times just runs a workflow end to end instead of looping towards a solution. Workflows are cheap, so the job ends up being way cheaper than an agent in a good model.
Very cool. I was waiting for something like this to pop up.
Is it possible to be added as a data source? I see you're mostly pointing the agent to easy / publicly available sources like the UK.
We have ~200 government registrar integrations now and 500M entities in the system. We essentially have better coverage than OpenCorporates at this stage. https://savvyiq.ai
Would like to hear from everyone: How are you dealing with PRs in 2026? It's our biggest bottle neck.
We are considering looking into attestations, e.g. through the SLSA spec: https://slsa.dev/ to ensure build provenance and verification before it is deployed.
Cool project, I myself have a similar autonomous agent, in python
At rinkesh2010rpp/sudarshana. But I liked your mission control. Will for sure take some inspiration.
Also, what I have is ability to find other agents on run time, running on Modal, and a safety layer that checks every actions taken by the agent.
If your team is using subscriptions, it is a lot more cost effective (and higher quality) to simply use a local orchestrator to automatically deal with PR reviews. We built https://github.com/codealong/codealong in part to help with this.
It hasn't gotten better since a year ago, I don't have high hopes. People need to get better at making smaller decisions and having more opinions, not just prompt "Create page for dashboard".
This is fair feedback. We spent a ton of time in the UI for our hosted product and the main website (agentrun.ai) but very little in the OSS console. We’re spending more time on this now and making it better.
Do it uses the claude code harness (for example) or bypass it? I ask because of the subscription. thanks
Could you explain how the self-improving part works?
I think these are their relevant docs:
https://agentrun.ai/docs/self-improvement
https://agentrun.ai/docs/learning-reference
Yes here is an article about it but I’ll will explain the tldr below. https://agentrun.ai/blog/agentrun-a-harness-for-repetitive-k...
The core concept is to have a frontier or very smart model run as an agent first for N times. The model get tools, skills etc and instructions. It does the job. At the end it leaves a note (like a retro) explaining what it did and what it could have done better.
As the agent runs, it also writes workflows to do the parts of the job it knows it can do in a more deterministic way (based on previous nodes and thinking traces of other runs etc). We made a dsl for this that has routing, classification, code nodes, etc to build these workflows.
For repetitive tasks (which is our focus) we find that after ~100 cases, the agent most times just runs a workflow end to end instead of looping towards a solution. Workflows are cheap, so the job ends up being way cheaper than an agent in a good model.
Very cool. I was waiting for something like this to pop up.
Is it possible to be added as a data source? I see you're mostly pointing the agent to easy / publicly available sources like the UK.
We have ~200 government registrar integrations now and 500M entities in the system. We essentially have better coverage than OpenCorporates at this stage. https://savvyiq.ai
Do you have an MCP? I am adding our internal tool proxy which can be used to plug in any MCP into it.
Yeah, but it's out of date. About to replace it with a new version that has SSO support and other updated APIs. Will be available next week.
Would like to hear from everyone: How are you dealing with PRs in 2026? It's our biggest bottle neck.
We are considering looking into attestations, e.g. through the SLSA spec: https://slsa.dev/ to ensure build provenance and verification before it is deployed.
Would love to hear that too... it's getting incredibly expensive. One of our templates is a code review agent. https://agentrun.ai/blog/saving-80-percent-on-code-reviews-u.... But we're looking to do more beyond making the review cheap.
Cool project, I myself have a similar autonomous agent, in python At rinkesh2010rpp/sudarshana. But I liked your mission control. Will for sure take some inspiration.
Also, what I have is ability to find other agents on run time, running on Modal, and a safety layer that checks every actions taken by the agent.
and happy to talk more.
Thanks
Very cool. Feel free to borrow from us what's helpful and send feedback our way!
If your team is using subscriptions, it is a lot more cost effective (and higher quality) to simply use a local orchestrator to automatically deal with PR reviews. We built https://github.com/codealong/codealong in part to help with this.
very cool. thanks for sharing!
I think I'll need like at least another 3-4 months of new models before I can deal with AI UI/UX design.
It hasn't gotten better since a year ago, I don't have high hopes. People need to get better at making smaller decisions and having more opinions, not just prompt "Create page for dashboard".
This is fair feedback. We spent a ton of time in the UI for our hosted product and the main website (agentrun.ai) but very little in the OSS console. We’re spending more time on this now and making it better.