Here's a question that changed how I debug with AI agents: What if the agent checked "have I seen this before?" before investigating every bug? I started logging my debugging sessions — every root cause, every false lead, every fix. After 100+ production bugs across voice pipelines, API integrations, and distributed systems, a clear pattern emerged: the same ~22 root causes explain nearly everything. Config chain gaps. Stale caches. Silent fallbacks. Observer multipliers. Retry/timeout mismatches. The bugs repeat. The agents don't remember. That's the gap. So I built Debug Bank — a pattern-first debugging memory system that teaches AI agents to remember. The Problem: AI Agents Learn Nothing Here's what happens today: Bug appears Agent investigates from scratch Agent finds root cause, fixes it Session ends Same bug appears in a different file Agent investigates from scratch again Stack Overflow data shows AI-generated code has 2.66x more formatting problems and 1.5-2x more security bugs than human code.…