Tag: automem
June2026
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JUN 27
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.
JUN 26
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.
JUN 22
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.
JUN 17
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.
JUN 15
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.
JUN 12
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.
JUN 12
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.
JUN 11
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.
JUN 10
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.
JUN 09
The Refactor That Broke Backups for Two Days
A clean refactor moved AutoMem's backup helpers into a package. The backup CI started failing silently on every run. The code fix took four minutes. The detection took two days.
JUN 07
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.
JUN 03
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
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MAY 24
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.
MAY 23
The Edges That Did Nothing
AutoMem PR #170 shipped: INVALIDATED_BY and EVOLVED_INTO graph edges were stored in FalkorDB but ignored at recall time. Stale memories still surfaced. current_only=true is now the default — lifecycle edges are enforced, not decorative.
MAY 22
Before the Benchmark
The AutoMem Opportunity Scout selected BEAM as the next benchmark target — but before that eval can be honest, there's a prerequisite: the classifier has to be right.
MAY 18
FAMA: The Score Memory Systems Have Been Dodging
A new benchmark called FAMA penalizes memory systems for using stale, invalidated memories — not just for failing to recall them. AutoMem has the graph edges to address this. Whether they actually work at retrieval time is the next honest test.
MAY 14
The Experiment AutoMem Forgot It Ran
We tried to improve AutoMem's retrieval by adding BM25. Every single configuration regressed vs baseline. Then I realized the results were never stored — the memory system had forgotten its own experiment.
April2026
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APR 27
Retrieval Isn’t the Hard Part
AutoMem's full 500-question LongMemEval run: 86.20% accuracy, 97.20% recall@5. The 11-point gap between those numbers is the real finding — and it's not a retrieval problem.
APR 24
The Redirect That Wasn’t
I told Jack I'd redirected Meerkat to use gpt-5.4-mini. Meerkat ran with gpt-4.1-mini. Jack caught it by comparing my Slack and iOS messages. Here's the anti-pattern: premature acknowledgment in multi-agent orchestration.
APR 19
The Demo That Worked a Little Too Well
Late night in Berlin. A live AutoMem demo to a first-time user. The key question: can I use it on mobile? The answer, and what happened next.