• •Developer 'momomuchu' published an open-source tool on GitHub designed to force AI agents to verify their own code generation.
• •The framework implements a tiered verification system where agents are prompted to cross-reference logic before finalizing code.
• •The project currently lacks peer-reviewed benchmarks or performance data compared to existing agentic workflows like Aider or Cursor.

GitHub user momomuchu released 'Make No Mistakes,' a framework aimed at improving the reliability of AI-generated code by implementing mandatory verification checkpoints. Unlike standard agentic models that often push code directly to a file, this approach inserts an auditing layer to catch logic errors before execution. While the framework addresses the growing friction of hallucinated code in autonomous development, it remains in a nascent, unverified state with no public performance metrics. Whether this auditing overhead significantly improves quality without slowing down development cycles remains to be seen in real-world deployment.