Most AI coding tools stop at generation. That’s the easy part. The real question: what happens when an AI has to verify its own output? I built Agent Factory to test that. It’s a loop: generate → execute → fail → fix → repeat The key shift: The system doesn’t “think” about correctness — it observes real runtime behavior. That changes everything. Some behaviors: → Runs until it passes, not until it looks done → Uses actual execution errors as feedback → Recovers from crashes via checkpoints → Fully local GitHub: https://github.com/BinaryBard27/Agent_Factory Where do you think this kind of loop breaks first — complex systems, external APIs, or scale? submitted by /u/FreePipe4239
Originally posted by u/FreePipe4239 on r/ArtificialInteligence
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