I’ve been building Ouroboros to solve the "infinite token burn" problem in agentic coding. Most failures I've seen come from ambiguous inputs, leading to agents that "look busy" by refactoring the same code over and over without real progress.

To reach true Human Outside The Loop stability, I’m experimenting with two "math gates"

Ambiguity Gate: The Socratic interview phase doesn't end until the calculated ambiguity drops below 0.2

Convergence: Instead of fixed iterations, the loop stops when the system's schema stabilizes across generations

At a recent hackathon in Korea, I used this to let an agent run unsupervised for 7 hours overnight. It generated ~100k lines of code (including 70k lines of tests/mocks) and successfully built a hardware-integrated system while I slept.

The "Deep Interview" pattern from this project was recently merged into the oh-my-claudecode (OMC) v4.6.0 release as an official skill.I'd love to hear your thoughts on how to measure "real" architectural progress in long-running agent loops versus shallow code churn.