Yin, Yang, and the LLM: Engineering Reliability into AI Code Scanning

How Statistical Quality Control, Not Prompt Engineering, Reduced My AI Accuracy Problems In the rush to integrate Large Language Models (LLMs) into cybersecurity, we’ve hit a wall: Noise. Most AI-driven scanners either miss real issues or flood developers with “hallucinated” findings that look plausible but have no basis in reality. After some code review and scanning sessions with just a system prompt that went horribly wrong, I decided I needed a new approach.