You can reliably detect buggy code from LLM agents using cheap embedding comparisons instead of expensive LLM verification—FASE achieves this with minimal computational overhead.
FASE is a fast method to measure code quality uncertainty in multi-agent AI systems without needing expensive LLM checks. It uses structural and semantic similarity graphs to estimate whether generated code is likely correct, running 300x faster than existing approaches while achieving better accuracy.