Turn Linear issues into changelogs automatically
If you're a solo founder or a small team shipping fast, you already know the drill. You close a Linear issue, ship the fix, move on to the next thing — and your changelog sits untouched for weeks. Writing customer-facing release notes always loses to writing actual code.
Announcify's Linear integration fixes that. Move an issue to your chosen status, and AI turns it into a customer-ready changelog draft automatically. No context switching, no rewriting ticket titles into something a non-technical user can understand, no excuses.
The problem every indie hacker has with changelogs
Solo devs and small teams almost never have a dedicated person to "do changelogs." It falls to whoever's free, usually the founder, usually last on the priority list. The result is predictable: changelogs go stale, users stop checking them, and all that shipped work goes unnoticed.
Meanwhile, tools like Beamer and AnnounceKit charge $600–$900 a year for a widget that still requires you to write every post by hand. That's a hard sell when you're bootstrapped and already wearing five hats.
How the Linear integration works
The flow is simple by design — built for people who don't have time to configure a complicated pipeline.
- Connect your Linear workspace via OAuth in a few clicks
- Pick your trigger status — whatever your team already uses, like "In review" or "Done." No forced workflow changes
- Move an issue to that status, and Announcify fetches the title and description
- AI drafts a changelog post in plain, customer-facing language — no ticket IDs, no internal jargon
- Review and publish — or turn on auto-publish once you trust the output
You can also generate drafts manually anytime from the Linear Manual Drafts page, selecting exactly which completed issues you want bundled into a post.
Built for teams that care about data privacy
If your product touches sensitive data — fintech, healthcare, legal, anything regulated — sending raw ticket descriptions to an AI model isn't an option. Linear issues often contain client specifics, edge cases, or internal notes that should never leave your workspace unfiltered.
Announcify automatically redacts emails, phone numbers, card numbers, and financial figures from issue content before anything touches the AI model. This isn't an afterthought — it's the reason the integration exists in its current form, shaped directly by feedback from a regulated SaaS founder building for the financial sector.
Why this matters more for small teams than big ones
Large companies can hire someone to own product marketing and changelogs. Indie hackers can't. Every minute spent writing release notes is a minute not spent on code, support, or finding the next customer.
Automating the most tedious 20% of shipping — turning "what did I just build" into "what should my users know" — gives solo founders back time that actually compounds. Ship a feature, the changelog writes itself, you move on.
Customize it to fit your workflow, not the other way around
Every team's Linear setup looks different. Announcify doesn't assume yours matches a generic template:
- Status trigger — pick any workflow state your team already uses
- Label filters — include or exclude specific labels so internal tickets never leak into a public post
- Custom AI instructions — control tone, focus, and what to ignore
- Auto-publish toggle — fully automated, or review every draft before it goes live
Pricing that actually fits solo founders
Announcify's GitHub and Linear integrations are part of the Pro plan — $69, paid once, no subscription. Compare that to Beamer or AnnounceKit's $600–$900 per year for a tool that still makes you write everything manually.
The free plan gives you unlimited manual posts, the embeddable widget, and a public changelog page — no credit card required. Upgrade only when you want the automation.
Try it
If you're a solo dev, indie hacker, or small team tired of changelogs falling to the bottom of the to-do list, connect your Linear workspace and let your shipped work write itself into something your users actually read.