Anyone actually doing pattern analysis across their agent's traces, or are we all just eyeballing dashboards?

Genuine question. Been thinking about this all week. That Obsidian + Claude guide going around right now is good. Capture everything, let Claude read across your notes, surface connections you missed. I run something similar for my own reading list. It works. But here's what's been bugging me. The same engineers sharing that post have agents in production generating thousands of traces a day. Every trace is a decision the agent made while nobody was watching. Every trace gets dumped into LangSmith or Langfuse and never looked at again. That's not a second brain. That's the graveyard with good folders the guide explicitly warns about. Your Obsidian vault compounds because something reads across it. Your trace store doesn't compound because nothing does. New trace lands, old trace forgotten. The knowledge your agent generates about its own failures evaporates the moment the request returns 200. The asymmetry is wild when you actually look at it. We spend a Sunday wiring up N8N so Claude can find patterns in our reading list. Then Monday we ship an agent to prod with zero mechanism to find patterns across the agent's own behavior. A regression in pattern A and a regression in pattern B look identical in the dashboard. Both returned 200. Both took 4 seconds. Nothing tells you the agent took two different paths to get there. A new failure mode shows up and gets logged next to 40,000 successful runs that look exactly like it. The loop the Obsidian guide describes (capture, connection, return) is exactly what's missing for agents. Capture is already automatic, every observability tool does it. Connection is the part nobody's doing. And without connection there's no return, no ritual of going back and noticing what shifted. So what's everyone actually doing here? Custom clustering on traces? Scheduled LLM passes over recent runs? Some kind of embedding-based grouping? Or is it really just dashboards and prayer?