Nice. LLMs can prove barely anything, providing some sources, or doing pure math that already circulates. AFAICT, so far, no novel ideas have been proven, i.e. the "these systems never invented anything"-paradox for three years now.

Symbolic AI seems to prove everything it states, but never novel ideas, either.

Let's see if we get neurosymbolic AI that can do something both could not do on their own — I doubt it, AI might just be a doom cult after all.

This applies to coding agents. If the agent can't run the code, it's unlikely that it can produce working code. Add to running: linting, running tests, compiling, code review and any other tool/process humans do to check if software is 'good' or working.

If the agent can apply these processes to the output, then we're on our way to getting good chunk of our work done for us. Even from the product pov, if the agent is allowed to experiment by making deployments and check user-facing metrics, it eventually could build software product - but we should still solve the coding part as it seems easier to objectively verify quickly.

Wow, 2001. Legitimately prescient.

And verification ("evaluation" we call it now) really is the key, although most people working on "AI apps" haven't figured it out yet.

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