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Cooking & life

fx: a 6MB coding agent built to be embedded

Vercel Labs shipped fx — a ~6MB, Zig-written coding agent that cold-starts in 10µs, speaks ACP, mounts MCP servers, and prints JSON. It's not a hosted service; it's a runtime you embed. Here's what it is, where I'd put it in my always-on harness, and how a large logistics operator would use it.

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OpenSpec: The agreement layer that keeps your agent honest

AI coding assistants confidently build the wrong thing when requirements live only in chat. OpenSpec adds a lightweight spec layer — explore, propose, build, archive — so you agree on what to build before any code is written, and the specs persist in your repo as history your agent can read back. Here's the mental model, a real change from a skills discovery portal, and where it earns its keep.

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Loooom v1.0

Loooom v1.0 adds behavioral tests to its skill evaluations. A few early failures exposed assumptions in the tests themselves.

Pride Postcard

Lady Gregory's, Andersonville, Chicago, IL

A table card on a bar reading 'Andersonville Pride' in rainbow letters, surrounded by a word cloud — acceptance, love, community, dignity, equality, celebrate

Table card at Lady Gregory's, in the heart of Andersonville. A whole vocabulary of the month, set in rainbow.

Killing OpenClaw for a native Claude Code setup

I love OpenClaw. I hate that it doesn't run on my Claude Pro subscription. Turns out Claude Code, with the Telegram channels plugin and one CLAUDE.md, is the same harness — minus the daemon, the API bill, and the second LLM provider. Here's the actual recipe, ported from a hotel in Tokyo to a Mac mini in Chicago in forty minutes.

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Claude: Anthropic just shipped most of OpenClaw

I built a 200-line harness called conseiller to test Anthropic's new advisor tool — a fast executor model that consults a stronger model mid-generation. Two days later Anthropic shipped Claude Managed Agents, Multi-agent Orchestration, Dreams, Routines, and Remote Agents. Here's both halves: what I built and what they shipped, and how the pieces fit together into something a lot like OpenClaw.

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How I make tokens last longer

A simple set of habits I use to keep long AI coding sessions from getting bloated: better one-shot prompts, matching model and thinking level to the job, understanding cache behavior, and using cheaper orchestrators when it makes sense.

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