15 posts tagged #headless.
The loop engineering parts list from June 2026, classified by one question: five blocks are context moves, one is a schedule, and the genre's signature failure is fixed by a seventh block the list never counted.
A frozen spec substitutes for the memory a disposable agent doesn't have - but only if every task is genuinely independent. The arithmetic for when a flat-rate build loop actually holds.
While you watch an agent work, you are quietly doing two jobs: judging what it may touch, and judging when the work is actually done. Headless mode deletes you from both at once. The gate that inherits the second job fails two separate ways unless it has two teeth.
Raw frequency tells you which failures are real. It still ranks them wrong. Weight each promoted category by what one instance costs, and the rule that looked #2 by count drops to last.
Against a 1-in-12 hallucination rate on a checkable failure, a deterministic hook with one capped retry drives the shipped-wrong rate to exactly zero and moves the remaining risk onto one computable number: the halt tax.
A one-line bug report about an agent carries exactly one testable fact: how often the failure fires. Turn the report into a committed synthetic scenario, then let that fact size how many reruns a fixed verdict is worth.
The agent is an agreeable judge of done and the harness is a blind one. Two brakes, a third exit state, and the one night a $1.75 bill hides a lie.
A relay of fresh sessions inherits every earlier decision through the plan file's checkboxes. But the model that ticks a box has every incentive to believe its own diff. An unaudited checklist is a bet, and this is the arithmetic that prices it.
An event can fire a headless agent run as reliably as a hook fires inside a session. But wiring the event only removes the human who had to remember to ask. The one who caught bad output has to be rebuilt as code too: rules for what a careful review would do, guards for what it would never let happen unattended.
A suite thorough enough to catch a real regression is too slow and noisy to gate every PR. Split the same 50 cases into a 32-case deterministic gate and an 18-case nightly judge sweep, and a team merging 8 PRs a day gets 156 minutes of blocked PR time back every week - without dropping a single case.
Your local review habit and your CI gate are two implementations of one question, and nothing forces them to agree. Write the policy once, pin the context, and both surfaces run literally the same check for about two cents a call. The same 30 weekly pull requests on Anthropic's managed Code Review run $450 to $750.
The blocker to running an agent overnight was never capability - it's trust. Layer a sandbox, an allowlist, and a scoped credential right, and one laptop's worst-case reach falls from 399 addressable things to 63, all recoverable with git checkout.
A one-line AGENTS.md fix that visibly resolves the case you were chasing can still fail its own regression gate. Fixing one case here drops a six-case eval from 0.833 to 0.500 - and only a baseline that ratchets upward catches it before a user does.
An unattended loop that reads git log -5 each pass has a five-pass memory. In a 12-item plan, the decision made at pass 3 ages out at pass 9, two passes before pass 11 needs it. One line in PLAN.md pointing at the commit hash recovers it, for zero extra commits.
Task selection is the one decision still routing every ticket through you. Write the priority order down once, and the 80 touches a sprint costs you collapse to 1 - same agent, same backlog.