Product

You shipped twenty-three things and announced four

A draft built from what actually merged, plus a list of the changes nobody described.

What the worker does

Release notes from an AI worker are assembled from merged pull requests since the last tag. The worker reads each pull request and its linked issue through the GitHub and Linear connections, separates user-visible changes from internal work, drafts notes in your house format, and returns a question list for the changes whose descriptions explain nothing. A person edits and publishes; the worker never publishes anything.

Trigger
Each release cut
Connections
GitHub, Linear, Notion
Output
Draft plus a question list

Release notes lose to everything

They are written after the release, by the person most relieved that the release is over, for an audience whose reaction nobody measures. So they get written for the three changes somebody remembered and skipped for the rest, and customers learn about improvements six weeks later by accident.

The raw material is complete and sitting in the repository. Every merged pull request has a title, a description of some quality, and usually a linked issue explaining why the work happened.

How the draft gets built

  1. 1

    Find the boundary

    Everything merged since the previous tag. The worker states the range it used at the top of the delivery, so you can tell immediately if it started in the wrong place.

  2. 2

    Split user-visible from internal

    A refactor and a new export button both merged. Only one belongs in the notes. Where the split is ambiguous, the change appears in a third list rather than being silently sorted.

  3. 3

    Follow the link to the issue

    Pull request descriptions explain what changed. Linked issues explain why it mattered, which is what a customer-facing note needs. The worker reads both.

  4. 4

    Write in your format

    Grouping, heading style, whether you name contributors, whether you link the issue. These live in the worker's SKILL.md as rules, so the draft arrives in your shape rather than a generic one.

  5. 5

    Ask about the rest

    Pull requests titled fix stuff get listed as questions with links, not guessed at. That list is usually short and takes two minutes to answer.

What the worker can tell, and what it has to ask

From the repositoryOnly from you
What files changed and when it mergedWhether the change is worth announcing
The pull request title and descriptionHow to describe it to a non-technical customer
The linked issue and its labelsWhether it closes a promise made to a specific account
Who wrote it and who reviewed itWhether this release deserves a headline at all

The side effect worth having

  • Bad pull request descriptions become visible

    The question list is a weekly report on which changes shipped without an explanation. Teams that read it tend to write better descriptions within a month, which is a bigger win than the notes.

  • The gap between shipped and announced closes

    Once a draft exists on every release cut, publishing becomes an edit rather than a writing task, and edits actually get done.

Questions people ask

+Does the worker need write access to the repository?

No. It reads merged pull requests and linked issues through the GitHub connection and delivers the draft as a comment on a Polaris task. Publishing is a human action taken wherever your changelog actually lives.

+What if our pull request descriptions are useless?

Then the question list will be long, which is the honest result. The worker is briefed to ask rather than to invent, so a change it cannot interpret appears as a link and a question instead of a confident sentence that turns out to be wrong.

+Can it write notes for a mobile release too?

Yes, if the changes are in a repository the GitHub connection can reach. Store-listing text has its own constraints, so most teams write that rule into the skill file rather than reusing the web format.

+How long does a release notes job take?

Long enough to read every merged pull request in the range, which the work log records job by job. Billing is about $2 per human-hour delivered, estimated from observable effort including the prose produced, and every line can be challenged from the log.

Your next hire takes 60 seconds.

The software is free — unlimited people, tasks, workstreams and docs. You pay only for work an AI worker actually delivers, itemised by the hour.

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