AI-generated release notes from your merged stories, in your voice, with one-click edit.

Release notes are typically written by someone reading through closed Jira tickets and rephrasing them into user-friendly language. Stride does the rephrasing automatically: every release surfaces a draft from the merged stories, in your team's voice, with the option to edit before shipping.

Outcome

Release-note authoring time drops from ~90 min/release to ~10 min/release

Stride telemetry, Q1 2026

The problem

Release notes get written by whoever loses the lottery — usually the day before the release ships, by reading through 20-50 closed tickets and rephrasing them. Quality varies with who's writing; some teams skip notes entirely; customers don't know what shipped. The work is mechanical (rephrase ticket → user-facing language) and AI is great at it.

How Stride solves it

When a release is cut, Stride generates a draft from the stories merged into it. The drafts use your team's voice (calibrated from your existing release notes) and group changes by category (new features, improvements, fixes, security). The release manager edits as needed and publishes. Total time: 5-10 minutes vs 60-90.

Auto-generated release notes from merged stories per release
Voice calibration from existing release-note history
Categorisation: features / improvements / fixes / security (mirrors changelog convention)
Story-to-note traceability: every bullet links back to its source story
Skip-internal flag on stories that should not appear in customer-facing notes
Multi-channel publishing: in-app changelog, RSS feed, email digest, Slack post

Best for

Customer-facing software products with weekly-or-faster release cadence and a real customer base that reads release notes.

Not for

Internal tooling teams where release notes are never read. Also not a great fit if your stories are written in dev jargon — the AI translates but the input quality bounds the output quality.

Frequently asked

How does the AI know my team's voice?

It reads your last 10-30 release-note entries and calibrates tone, length, vocabulary, and structure to match. New teams without history start with a sensible default (concise, customer-focused, slightly informal). The calibration improves over time.

What about stories that shouldn't be in customer-facing notes?

Each story has a "skip in release notes" flag for internal-only work (refactors, infra, internal dashboards). The AI honours the flag. By convention, anything tagged "internal" auto-skips.

Can I publish to multiple channels?

Yes — the same release notes can publish to your in-app changelog, RSS feed (changelog.xml), email digest to opted-in users, and Slack release-bot. All four channels share the same content from one edit.

How accurate is the categorisation?

High for clear-cut stories (a defect-tagged story → Fixes). Lower for stories that span categories (an "improvement that also fixes a bug" lands wherever the AI guesses). The release manager edits before publish — same workflow you have today, just with less authoring.

See release notes automation in Stride

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