24 posts
Run a monthly drill with a deliberate violation. Verify which controls reject it, report failures, and confirm cleanup. The drill attempts real merges, including an administrator override; use a disposable test repository and inspect the…
Run the task queue on a schedule. Separate urgent failures, requests for your decision, and routine logs. Detect missed runs, and understand why a watch on the same machine cannot detect that machine's complete failure.
Add a separate reviewer, require automated checks before merging, and verify the deployed result before marking a task complete. Configure a runner, a GitHub workflow, and command restrictions, with explicit limits on what each can verify.
Give each task acceptance criteria, dependencies, and a status. Define how the agent selects the next eligible task and when it must stop. Includes a queue template and a five-item exercise.
Write down the actions agents may take, the actions requiring your approval, and the evidence they must provide before reporting completion. Includes a permission template and exercises that check whether an agent follows it.
I cap my setup at roughly ten coding agents across several subscriptions, with three or four per vendor. A seven-agent wave exposed failures in network access, checkouts, test ports, and generated files. The counts and the preflight chec…
Thirty days of running an agent fleet from chat: 8.7 billion tokens, 70,227 calls, 2,861 sessions, a 98 percent cache hit rate. At each vendor's list price that traffic bills $7,566. Three subscriptions covered it for $599. Where the tok…
Document which repository owns each part of the project. Assign each agent a specific scope and a separate checkout to prevent overlapping edits. Includes layout instructions and a repository-splitting exercise.
Turn a project rule into a script that detects violations. Run it before each push and test it with a deliberately invalid change. Learn what a local Git hook checks and how it can be bypassed.
Write a decision record documenting what you chose, which alternatives you rejected, and when to reconsider. Instruct agents to read relevant decisions before proposing changes, then test whether they retrieve them.
The full path to an agent platform that edits its own instructions is already published, scattered across seven articles that never mention each other. I run that architecture as one person: supervisor and worker tiers, verification guar…
A Windows Task Scheduler default fed my Claude Code memory pipeline its own transcripts for nine days: 21,264 junk sessions, 38 GB of exhaust, and an 18,428-session backlog that was really 1,924. The durable fix: postconditions that outr…
I split a day of development across two AI subscriptions: judgment on the Anthropic meter, typing on Moonshot's. Five merged PRs later, here is where the tokens went, how K3's pricing actually compares, and how I'm tuning the mix.
Record what a feature must do, what is outside its scope, and how you will verify it. Create a specs directory and template, then give the agent an approved spec to implement.
Spec-driven development, pointed at a life. Why my principles and goals live as markdown an AI agent reasons over, and the one rule that makes handing an agent your life safe: it can challenge the record, but it never writes it.
I built a quant research platform, then built an agent to operate it: a scheduled Claude session that reads the boards, keeps a pre-registered track record, and texts me three times a day without ever saying buy.
In one working session I designed a read-only advisor and spent the rest of it being the customer of another. Both ran on the same short discipline: surface the decision and never seize it, verify before you assert, pilot before you fan…
The most dangerous result is the one you want to be true. Your own review is compromised by the same motivation that produced the finding, so the fix is a standing skeptic whose job is to refute, not confirm, before you act on anything.
The instinct with agentic tooling is to add: more agents, more skills, more clever prompts. The leverage runs the other way. Here is the test I use to decide whether a piece of work should be a script, a hook, a skill, or an agent, and w…
Boris Cherny mapped five execution archetypes on the Claude Code team, and noted they cut across job titles. His framework describes a team dividing labor across people. Run a fleet alone and the same five split a different way: across y…
A year of building and operating a small fleet of finance and content products almost entirely through an AI coding agent. What worked, what was hard, the honest failures (including a flagship signal that measured nothing and an edge tha…
Four days after I said goodbye to Opus, an export-control directive pulled Fable 5 offline and the fallback became the workhorse again. What I shipped in the window, what it cost, and the model-tiering plan for when Fable comes back.
Anthropic shipped Claude Fable 5 and Mythos 5: same model, two names, one safeguard layer apart. What the new frontier model means for running agents in production.
A small ARM box that started as a local LLM experiment and ended up a self-governing node: private retrieval, a resident agent under a written constitution, a code-enforced safety fence, and a nightly job where it audits itself and files…