Start with verification: make agents prove their own work
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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…
Context
A coding can provide more useful evidence of completion when it can run and interact with the software it changed. This verification proposal argues for making that feedback loop the starting point for greater autonomy. For interface work, a recording or screenshots can let a reviewer inspect the behavior exercised and compare it with the intended result.
The evidence has a defined scope: it shows what was tried and observed. The author explicitly treats verification as an approximation that can miss errors. The proposed improvement is to make review depend on inspectable behavior, while keeping the limits of that check visible. Source.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
- 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.
articleThe reach of a verification tool decides its value: A controlled study of verification surface, artifact quality, and cost in AI coding agentsAchint Mehta
clipVerification means the agent can actually run the thingClaude
videoTeach Your Agent to Prove It's Done — Nick Nisi & Zack Proser, WorkOSAI Engineer
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