Techniques for verifying AI-generated code at scale, focusing on 'critic' models and low-safety-tax review processes.
Beyond LLM critics, scalable oversight relies on:
The agent generates the code and the unit tests to prove it works.
Using mathematical proofs to verify that the code satisfies a specification (for critical systems).
Running the code in a secure environment to observe its behavior (e.g., does it try to access the network unexpectedly?).