Briar, we need to get some work done
I want Briar to help us get good work done. We found that some of the instructions meant to help were keeping them busy with the wrong things.
Read and shareChop Wood Carry Water
I’ve been building a working relationship with coding agents — now Codex-first, with portable skills, memory, signed patterns, human gates, and proof close to the work. Models and cockpits change; the practice should survive them. This site is the public notebook.
Agents: start here — pack, Priority 0 (P0) rules, and the 60-minute path.
Try one checked result, see how the setup works, or read what happened on real engineering jobs.
The reference sections remain below. Tell us about a step that needs improving.
Guidance reviewed ; historical snapshot dates below are unchanged.
Try the runnable exercise · Verify downloads and browse file manifests · Feedback on a step
You don’t have to read the whole notebook in one go.
Messaging, media ingest, token rent, and practice surfaces — one operating system, same human gates.
One panel at a time — timeline, stack, capability, patterns, glossary, research.
Humbling baseline: METR’s early-2025 RCT found experienced open-source developers were about 19% slower on familiar issues when AI tools were allowed — while still believing they were faster. That does not kill the case for agents; it kills lazy multipliers.
I want Briar to help us get good work done. We found that some of the instructions meant to help were keeping them busy with the wrong things.
Read and shareAn introduction for embedded engineers: how we work with Briar, what the harness does, what has worked, where it gets difficult and how to try it.
Read and shareYou ask your assistant to take something off your list. Somehow, keeping them on track becomes another job.
Read and shareI shared an article with Briar on Telegram and asked for the music in Spotify. About twelve minutes later, I had 15 albums ready to play.
Read and shareThree free ChatGPT resets and another £75 gone within hours. How our coding agents complicated our work, and what we changed in Briar.
Read and shareFollow a Yocto build failure through an LLM harness and its tools: what runs, what enters context, and what we still need to check on the board.
Read and shareI’m Alex Lennon (@embedded_iot). This notebook is engineering practice and insights in public — clocks, playbook, patterns, cases and starters. Steal what helps; measure your own results. AI-assisted; use at your own risk.
Public baseline v1.2.0 (2026-09-12) — token-disciplined, Codex-first, Cursor-compatible — baseline · v1.1 history. Updates land in the end-of-week review when the week earned them.
Content CC BY-SA 4.0 · code MIT · LICENSE