I Built a Debugging Memory for AI Coding Agents — Here's the System Behind It

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.