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How to make AI coding-agent work reviewable

Turn agent work into a bounded repository contract with named validation and a written implementation summary.

Direct answer

Make the review unit a repository artifact, not a chat session: define the objective, allowed paths, validation command, and acceptance criteria before implementation; then require a summary of the changed paths and passing evidence before review.

Day Shift hierarchy from specification through slice, phase, milestone, task, implementation summary, and reconciliation.

Practical guidance

Make the next review decision easier.

Give reviewers a stable boundary

A task definition records the objective, implementation target paths, and validation before an agent edits code. The reviewer can compare the result to that declared boundary instead of reconstructing intent from prompts.

Keep evidence beside the change

An implementation summary captures completed work, changed paths, and validation results in the repository. That makes the evidence available to a later human or agent without relying on a chat transcript.

Finish with acceptance review

Reconciliation rolls task evidence back to the milestone acceptance criteria, creating one explicit decision point for whether the work is accepted or needs follow-up.

Verified demo evidence

A public CLI result, not a completion claim.

This command and result are from the website’s checked-in synthetic repository demo. Substitute your own repository paths and validation command when you apply the workflow.
$ day-shift task new --milestone-overview <milestone-overview> --full-set
Created 2 declared tasks and implementation summaries

Authorship and sources

Trace this guidance to maintained product evidence.

Maintainer
Tianna McCoy ↗Day Shift maintainer; responsible for the repository-native workflow and release evidence referenced here.
Last updated
Tested Day Shift
v0.1.24

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A practical checklist for handing work to a coding agent and receiving reviewable implementation evidence back.

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Require executable validation up front and recorded results before coding-agent work can be accepted.

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Plain-language explanation of the Human-Agent-Contract: explicit intent, scope, validation, evidence, and reconciliation for coding-agent work.

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