One thing I'd love to see: what does "actually works" mean in measurable terms? The engineering is sophisticated, but I'm curious about user-facing impact - did memory injection improve task completion or satisfaction? How often do users invoke /memory forget? What's the false positive rate on extraction?

These systems are hard to evaluate because failure modes are subtle - the AI "knows" something but uses it awkwardly, or surfaces context that feels intrusive. Would be great to hear what metrics you're tracking to validate the complexity is paying off.