camdenclark

2 ms·

1.
by camdenclark 10d ago
Separate but if you run CI at any scale you should have an agent working to improve CI constantly and alert you to any regressions / flakiness. It's something that agents can do in the background and open PRs for your team.
2.
by camdenclark 11d ago
You need blocking! Fundamentally this is an entity resolution problem. An LLM can score pairwise really well but scoring all the pairs would be insanely computationally difficult. If you can constrain the set of potential matches up front b
3.
by camdenclark 27d ago
Absolutely the first one could be achieved using one of those tools. But Monty makes it feel so native, it even packages a type checker so you can provide stubs for the external functions (so you provide feedback to the agent on the type of
4.
by camdenclark 27d ago
The main property that's really important is that Monty VM state is fully serializable and resumable. So you can run the VM code until you get to a host call, then serialize and persist the state to disk. Then, at a later time you can
5.
by camdenclark 27d ago
1. Control and guardrails. I want agent-authored code to be able to express itself in code but I want to own the external tools that are available to the agent. 2. Suspension and resumption. Monty's VM state is fully serializable so I
6.
by camdenclark 27d ago
Funny -- I just built a pure go wrapper myself because this one is super out of date! https://github.com/CamdenClark/monty-go It implements the new subprocess model for spawning Monty VMs that help keep your main threa