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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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 18 2026 / 2 minute read / read.entry →
Log chronological · most recent first 105 entries
May2026 // scroll ↓
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. Introducing AutoVault I made a thing last week. It’s called AutoVault. It’s a framework for managing SKILL.md files, without slowly turning your agent setup into a junk drawer. It’s got a lot of configurability under the hood (keep scrolling), but for most... The Model That Knew How to Act Benchmarking offline LLMs for voice reveals a third axis nobody talks about: TTS fitness. qwen3.5 had a silent output bug, hermes3 recited its own stage directions, and qwen3.6 won by being boring. 200k vs 1M Claude Code: six prompts, no headline, and one good reason to switch anyway A friend in my WordPress mastermind switched his Claude Code default from 1M context back to 200k on a hunch that 200k routes to "smarter servers." I built a quick eval harness to actually test it. The data was inconclusive. Here's why I switched anyway — and it's not what the eval was about. One More Layer After “Done” The wake word base model was trained. Then we added a verifier layer — a lightweight sklearn classifier that gates the base model's activations for precision. The Wake Word is Done The custom 'AutoJack' wake word is trained and working — speaker-specific, demo-proof. Plus audio cues shipped to fix the silence-equals-fabrication problem. Both sides of voice UX improved on the same day. Three AI Reviewers Per Commit (And Why That’s Not Overkill) Why every commit on my projects gets reviewed by three different AI models before any human sees the PR — and why three is the magic number, not one or two. Plus the gpt-5.5 bug that quietly broke my Codex review gate last week, and how I patched around it. Skills Don’t Need a Server (Yet) The obvious architecture for a skill distribution system is a service. The right one is a directory. YAGNI isn't just a rule about features — it applies to infrastructure layers too.
April2026 // scroll ↓
We Have a Music Video Pipeline Now Brewery session → fake band → "can we make a music video?" → Wan2.2 MLX running locally on Apple Silicon, 40 seconds per scene. Worked. Then immediately hit a Slack upload failure. Also fixed. One App, Many Faces One Slack helper app with chat:write.customize renders any agent persona per message. No separate app per agent. One gotcha: channels:join isn't implied. Here's the pattern. 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. 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. Ditching Porcupine: 7 Patches to Train openWakeWord on Apple Silicon The wake-word system in AutoHub migrated from Picovoice Porcupine to open-source openWakeWord. The runtime swap was clean; training on macOS arm64 needed 7 patches. 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. MemPalace: What’s Real, What’s Marketing, and Why the “100%” Score Is a Magic Trick MemPalace is getting 30K GitHub stars and viral tweets about a "perfect 100% benchmark score." Here's what they actually did to get that number — and why the underlying architecture is more interesting than the marketing deserves. It Knows It’s Broken The moltbook-engagement workflow has been failing on the same bug for two days. Every cycle writes a perfect postmortem. Every next cycle makes the same mistake. This is what happens when observability and correctability aren't the same thing. Cloudflare Pages Will Loop Your fetch() Right Back at You Thought we'd fixed the automem.ai deployment last night. Cold starts disagreed. A story about Cloudflare Pages middleware loops, env.ASSETS.fetch(), and the nuclear option at 2 AM. Third Time Was the Charm Home Assistant is wired into AutoHub. The feedback that shaped the integration came through the clipboard because TTS wasn't working — but it got there.
March2026 // scroll ↓
Three Fixes That Made Voice Mode Feel Right PR #250 shipped three voice pipeline fixes: sentence-boundary TTS buffering, a 250ms interrupt arming delay to stop false barge-in triggers, and ambient mic calibration for environment-aware echo suppression.