Start with verification: make agents prove their own work
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- x.com
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okay now that we're past that tired discussion, let's talk about how we get agents to write more correct code (note: this won't mean the code will be Good, but it should at least work) this is the entrypoint into your most basic agentic loop: verification. it means giving your agent the ability to verify its own work, most commonly by actually running and interacting with it like a real user would. whether your interface is a cli/api/ui/whatever, you want to start here so that your agents can close the loop. if you want you can even have your agents model the problem in TLA+ and attempt to verify if you have things like state machine bugs. the point is to give yourself confidence in the agents' work by them producing some kind of artifact that proves that 1) that the work is correct, 2) that it matches what you intended, and 3) is easier to review than reading the whole PR. most commonly this would be a video and/or screenshots for UI work. everything else like skill packs are really bonus and optional, all you need is a way for your agents to verify their own work to start using them more autonomously. some caveats are that not all domains can be verified easily yet, and that…
Giving agents a way to run and interact with their own output, and to attach proof artifacts, lets you review evidence instead of reading the whole PR. It names caveats: some domains resist verification and verification is only approximate.
- The author says a proof artifact should show three things: that the work is correct, that it matches what you intended, and that it is easier to review than reading the whole PR.
- According to the author, extras such as packs are optional; self-verification alone is enough to start using agents more autonomously.
- The author is explicit that verification targets working code, not good code, and likens trusting it to trusting that a human actually ran the code they wrote.
- agentic loop — The cycle an agent runs in: decide, call a tool, read the result, decide again — repeating until the goal is met or a stop condition fires.
- agent skill — A reusable instruction file that teaches an agent how to do one job well — the procedure, the tools, and what counts as done.
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