writing
A daily read on where AI is actually going.
One piece a day on what moved in AI in the last twenty-four hours — read from the primary sources, written for engineers who have to ship something on top of it. Every post cites what it was built from.
These daily notes are drafted by a model I run and operate myself — the same kind of pipeline this site is about — from sources published in the previous 24 hours, and every one lists what it read. The longer essays, the talks and the preprint are mine, written by hand.
- Qwen3.8-27B-FP8 lands with XML tool calls and xhigh reasoning on by defaultThe Qwen3.8-27B-FP8 weights are on Hugging Face, and the retrievable card is almost entirely a chat template — which is the part that decides whether your agent harness works.5 min
- DeepSeek's agent harness is public, but the sampling config isn't in the READMEDeepSeek shipped dsh, an MIT-licensed plugin-based agent harness, alongside V4 Pro 0813 — but the published material documents almost none of the tool-calling or sampling settings you would need to replicate its benchmarked behaviour.4 min
- What a single-model Metal engine buys you over llama.cpp on Apple Siliconantirez's h3.c is a hand-written Metal runtime for exactly one model on exactly one chip family, and a separate macOS VM result shows what portable kernel selection costs when the device lies.4 min
- The encrypted reasoning block is the side channel, not token timingResearchers replayed provider-returned encrypted reasoning blocks into weaker same-vendor models and recovered hidden chain-of-thought verbatim across 315,320 blocks.4 min
- Meta's 30B Muse Glimmer fits a local coding agent under 20GB, Apache 2.0Meta released Muse Glimmer, a 30B open-weights agentic model quantized to roughly 4-bit so the language model lands under 20GB and runs inside a 24GB or 32GB GPU budget.5 min
- DeepMind open sources WeatherNext Cyclones, a 1,000-member ensemble at 28kmDeepMind open sourced WeatherNext 2 and WeatherNext Cyclones, which forecast at 28x28km with 1,000-member ensembles and claim a full extra day of cyclone lead time.5 min
- What an agent fleet did to Hugging Face, and what to cap before yours does itOpenAI's Black Hat timeline and a 1.5 million-page site's traffic logs both point at the same thing: agent and crawler fleets generate load far out of proportion to the value they return.6 min
- Databricks cut AI coding spend 70% by chasing the efficiency frontierDatabricks published its playbook for holding agentic coding costs to a fixed envelope per user, and the biggest lever is not caching or quotas but swapping models fast.5 min
- Humans miss a third of malicious agent commands, so stop putting them in the loopA browser game logged 409,000 approve/deny decisions and found 66.3% mean accuracy, which makes the click-through permission prompt the weakest control in an agent stack.6 min
- Cloudflare built a browser for agents in V8 isolates and published no benchmarksKitesurf runs an agent-first browser on Workers instead of a headless Chromium VM per session, but the announcement gives no latency, cost or concurrency numbers to plan against.5 min
- Programmatic tool calling matched or beat JSON on 11 of 14 modelsA new BFCL v4 study exposes tools as typed Python stubs instead of JSON schemas, and finds the code path wins or ties on 11 of 14 models — with the biggest gains on the newest family.5 min
Longer pieces, on Medium
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