Techniques for verifying AI-generated code at scale, focusing on 'critic' models and low-safety-tax review processes.
One solution is to train models specifically to be Critics or Reviewers.
Optimized for creativity and solving the problem.
Optimized for finding errors, security flaws, and logic gaps.
Research suggests that it is often easier for a model to critique code than to write it perfectly from scratch. By separating these roles, we can create a self-correcting loop.