Neuro-formal verification (NFV) uses AI coding agents to automatically formalize and verify programs written in mainstream languages by translating them to verification-aware languages like Dafny or CBMC. Experiments on Python code show NFV achieves 57–63% bug detection rates with 90–92% precision, outperforming LLM-as-judge baselines while providing machine-checked proof artifacts.