Release Notes Production Workflow

Every merged PR becomes customer-facing copy within 4 hours, across every channel.

Updated 2026-04-18
Tycoon solution

AI Head of Content + AI CTO run a ship-to-notes pipeline. Every merged PR that touches user-facing code gets summarized into customer voice, categorized (new feature / improvement / fix / breaking), pushed to the changelog page, drafted as in-app announcement, queued for the monthly email digest, and turned into 1-2 social posts. Sales and support get a weekly internal version.

How it runs

  1. Detect user-facing ships

    GitHub webhook fires on every merge to main. AI CTO reads the PR title, description, file diff, and linked Linear issue. Classifies: user-facing (ships something customers can see/use) or internal (infra, refactor, tests). Only user-facing ships continue in the pipeline.

  2. Rewrite in customer voice

    AI Head of Content reads the PR and writes 2-3 versions: a 1-sentence changelog entry ('You can now export reports as CSV'), a 30-second in-app announcement with screenshot, and a 150-word blog-style entry for the bigger features. All in your brand voice, no dev jargon.

  3. Publish to changelog page

    Changelog entry ships to your /changelog page (Mintlify, Hashnode, or custom Next.js route). Includes date, category tag, screenshot if relevant, 'related docs' links. RSS feed auto-updates. Search indexes the new entry.

  4. Draft in-app announcement

    For features (not bug fixes), AI Head of Content drafts an in-app announcement using your Beamer, Canny, or in-house equivalent. Includes the headline, body copy, screenshot/GIF, and CTA (link to docs or the feature itself). Queues for your approval — most you approve, some you edit or skip.

  5. Queue for monthly digest email

    Entries accumulate in a 'next month's email' Notion doc. Around the 28th, AI Head of Content assembles the monthly 'what shipped' email: 5-8 features grouped by theme, 1-2 featured with screenshots, 3-5 smaller improvements listed. You review and ship via Customer.io / Loops / Resend.

  6. Social media versioning

    For the 3-5 biggest features each month, AI CMO drafts 1 Twitter post (hook + screenshot + link), 1 LinkedIn post (longer-form with business framing), 1 for your Discord community. Queues in Typefully/Buffer for your review. You usually approve with minor edits.

  7. Internal sales/support brief

    Every Friday, AI Head of Content posts a #ship-this-week digest to your Slack: what went live, who built it, customer-facing language, docs links, known limitations. Sales uses it for demos. Support uses it to answer 'is this new?' correctly.

Who runs it

  • hire/ai-head-of-content
  • hire/ai-cto
  • hire/ai-cmo

What you get

  • Every user-facing ship becomes a customer-visible communication within 4 hours
  • Changelog page stays current with zero manual effort
  • Monthly 'what shipped' email sends on schedule with real specifics
  • Social media posts about real features (not recycled marketing)
  • Sales knows what's new at the start of every week
  • Support reduces 'is this a new feature?' tickets by 60-80%
  • Marketing has a steady drumbeat of product content without chasing engineers
FAQ

Frequently asked questions

Clear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.

How does it avoid writing 'we shipped bug fixes' for actual bug fixes?

Bug fixes are their own category — they go into the changelog page with specific descriptions ('Fixed: CSV export would fail when dataset exceeded 10,000 rows') but not in the monthly email or social media unless a customer specifically requested the fix. The distinction matters: customers want to know their reported bugs got fixed (high trust), but they don't want a marketing email about bug fixes (feels like noise). Tycoon splits them appropriately — changelog = complete, email = feature-forward.

What about breaking changes or deprecations? Those need more careful communication.

Yes, and they follow a different path. Breaking API changes trigger a 30-day advance notice workflow: email to affected customers (identified by API usage in your telemetry), docs update highlighting the migration, Slack/Discord announcement, in-app warning banner for users who use the deprecated path. The timeline is enforced — the code can't merge to main until the deprecation notice is scheduled. AI Head of Content drafts all the copy; AI CTO enforces the merge gate.

Our product has 3 surfaces (web app, API, CLI). Each has different audiences. How does this handle that?

Three separate changelog feeds, one pipeline. Every PR gets tagged by surface (web/api/cli) via label or file-path detection. The changelog page has filters so customers can subscribe to only the surfaces they care about. Emails/social/in-app all target the right audience — API customers get API updates, CLI users get CLI updates, web users get web updates. Shared features (like 'this is now in all 3 places') publish to all feeds.

How accurate is the 'user-facing vs internal' classification? We don't want internal refactors announced.

After 30 days of training on your codebase patterns, accuracy is 95%+. The AI reads file paths (changes in src/pages/dashboard → user-facing, changes in scripts/migrations → internal), PR descriptions, and linked Linear tickets. Misclassifications surface in the review queue before publishing — you can tag 'internal only' to skip. Over time the AI learns your specific conventions. Most misclassifications err toward over-publishing (surfacing internal work as user-facing), which is caught in review, not under-publishing.

We're B2B with enterprise customers. They hate surprise feature announcements — they want managed rollouts.

The pipeline supports this. Features tagged 'enterprise-sensitive' go into a separate workflow: enterprise account managers get a preview 1 week before launch with talking points, customers with active tickets on the affected area get a personal note from their account rep, and the public announcement holds until all priority accounts have been briefed. The automation handles the coordination; humans handle the relationships. Typical workflow: 5-10 day staggered rollout for big features, same-day for small ones.

Related resources

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Internal Weekly Digest on Autopilot | Tycoon Workflows

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