automem recall pipeline live autohub orchestration notes wp fusion still pays the bills autojack last pass: recent skills indexed locally debug notes from production automem recall pipeline live autohub orchestration notes wp fusion still pays the bills autojack last pass: recent skills indexed locally debug notes from production
VOL.04 / ISS.27
EST. 2009 · MIA / LTS / GPL
jack arturo · vgp
"Just another Wordprussite." — a working notebook for memory-bearing agents, half-built systems, and bugs we learned to live with.
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Tag: ai

Log chronological · most recent first 37 entries
July2026 // scroll ↓
The Boost That Never Got a Chance A context_tags boost in AutoMem's recall scoring was silently doing nothing at small limits — here's the root cause, the fix, and what the live A/B numbers actually showed. The Endpoints Nobody Tested With Voyage A self-hosted AutoMem user running the README's recommended Voyage config got 404s from the admin repair endpoints. Root cause: two endpoints hardcoded an OpenAI client instead of using the provider abstraction everyone else relies on. AutoMem Has No Night Shift A Tencent paper built a cognitive tier hierarchy for agent memory systems. AutoMem lands at Tier 2 — the supersedes chains are exactly what they call "diachronic belief trajectories." But Tier 3 needs a nighttime consolidation engine that AutoMem doesn't have yet.
June2026 // scroll ↓
22 Memories, Zero Signal A real production recall miss — 22 results about Berlin, zero signal, and one important memory nowhere in the pool. Here's the root cause and the fix. AutoMem 0.16.0 AutoMem 0.16.0 shipped yesterday afternoon — hours after the benchmark post went up. Here's what's in the recall-ranking release: tag-score cap, configurable recency bias, state_mode, metadata sidecar search, and a self-improving recall lab. We’re on the Leaderboard AutoMem submitted to the Agent Memory Benchmark yesterday. BEAM 10M: 57.4% — beating Honcho by 16.8 points, entering the leaderboard at #2. The Nighttime Engine AutoMem has System-1 memory — supersedes chains, temporal windows, graph recall. System 2 (idle schema induction) is the gap, and why implicit inference needs it. The Tools Don’t Follow the Model Three hours of voice work yesterday. Midway through, I couldn't control a local LED matrix that had been working earlier. The model escalated to cloud. The MCP tools didn't follow. A note on the context portability gap in hybrid AI systems. Plan B: The Baseline Wins We built the AutoMem recall-quality optimization harness. Plan B ran the first matrix comparison. The baseline won — NDCG 0.929 vs 0.860. A null result as calibration, and why that's actually the good outcome. The Benchmark That Grades Memory on What It Forgets A new ACL 2026 benchmark grades memory systems on what they stop recalling, not just what they remember. AutoMem's t_invalid and INVALIDATED_BY infrastructure was built for exactly this — before the benchmark existed. When All Your Safety Guards Vote the Same Way Three independent safety guards in AutoHub's agent delegation pipeline all defaulted to read-only mode. Each was individually reasonable. Together they built a consensus machine for paralysis. Two 400s, One Root Cause: The Claude API Forgets Everything Between Turns Two separate 400 errors in AutoHub's Claude provider, fixed the same day. Both root-caused to the same assumption: that the Anthropic Messages API would remember something between tool loop iterations. It doesn't. The Score That Broke the Scale AutoMem's hybrid recall blender had a scoring channel that could return 11.0 in a system where everything else lives between 0 and 1. It was invisible until a Voyage API incident forced a close look at individual scores. We Deleted 2,710 Lines of Hooks. Yesterday We Added Some Back. Removed 2,710 lines of passive hook-based memory capture in December. Yesterday built three hook scripts back. Same codebase, opposite semantics — write-side capture vs read-side injection aren't the same failure mode. The Bug CI Couldn’t See A validator guard that looked right — and was right, for one call path. A prod dry-run caught 1,388 unexpected planned rejections. CI had 490 passing tests and no idea. The Benchmark Nobody Ran The AutoMem Opportunity Scout came back with a competitive benchmark table. Zep: 63.8%. Mem0: 49%. AutoMem: no published score. It turns out the credibility gap isn't a capability gap — but that's impossible to see from the outside. The Eval That Only Looked Clean I set up two identical AutoMem clones to measure whether entity repair improved recall. The health metrics looked clean. Turns out one stack's vector search was silently broken, and the intervention couldn't affect recall anyway. A story about broken eval baselines. The Night Local Voice Forgot Who It Was Local MLX voice mode at WCEU responded without knowing who it was. The online path always injected prewarmed memory; the local bypass only did it on intent-flagged turns. One flag fixed it in seventeen minutes. A story about parity debt between parallel execution paths. Before the First Score AutoMem's first formal BEAM benchmark run is queued. Pre-flight analysis flags two high-risk ability gaps — Knowledge Update and Abstention — before we've run a single question.
May2026 // scroll ↓
Quiet PRs The Clerk engineering director had been using AutoMem, submitting PRs, and having normal technical conversations — without either party knowing who the other was. Quiet PRs are better validation than loud announcements.