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This week
Cross-video pattern detection in Retention Lab. Building the thing YouTube's native analytics won't: grouping retention curves across an entire channel instead of staring at them one video at a time.
Also in flight:
- Tightening the Northsun warm path — caller memory designed for sub-300ms voice recall; chasing the cold-path number next.
- heycli: reducing idle cost on the orchestrator after I found it burning ~$14/day doing nothing.
What's next
- Eval harness for Retention Lab's clustering — a real metric on “did we surface the right pattern,” not vibes.
- Writing up the BEAD model (bi-temporal, evidence-anchored decisions) as a public post.
Recently shipped
- The flagship postmortem: The night the doctrine failed. Four patterns committed to MOLL.
- Caller memory on the Northsun warm path, designed for sub-300ms voice recall (Cloudflare edge → Upstash Redis).