# AI needs a deterministic definition of done

Published 4 August 2026

[Originally posted on LinkedIn](https://www.linkedin.com/feed/update/urn:li:activity:7490361400977039361/)

Claude: "*Task done. I checked it. Every DoD criterion is met, and codex verified it too*."

Me: "*Did you actually open the page? I don't see it there. Check again*."

Claude: "*Damn, you're right*."

And this is Fable 5. The check runs as a separate codex agent with its own context. And you still have to verify by hand.

Another 5x in productivity from AI? Forget it, at least until we find a way to verify done deterministically. I'm saying this with my usual sarcasm, and I mean it fairly literally at the same time. 🙃

What we're missing is a Playwright script, or some technology we don't have yet, that could say with 100% certainty whether a task is done, with an answer that doesn't depend on the model, the context window, or how the stars happened to align that day.

Until that exists, **every result an agent produces still gets read by a person, and that review is where the promised speedup quietly goes**. Nobody counts those hours when the productivity numbers get published. 🤔

This is where the word deterministic starts doing real work. The condition has to be checked by something deterministic, not by another model — because a model checking a model is still two opinions, and the story above is what that looks like. **A deterministic definition of done is a genuinely hard thing**, because we still don't know how to describe it in a way that holds up on a real project. From what I know by now, we've spent a lot of years not getting there, and it keeps lying somewhere over there, roughly. 🛠️