SUMMARIZATION
Audience-split release notes: route customer-facing vs internal changes
On each release, this classifies merged PRs as customer-facing or internal, then writes two tailored summaries.
How it runs
The automated pipeline, trigger to output.
- TriggerGitHub release publishedGitHub
- ActionFetch merged PRs with labelsGitHub
- ActionClassify each PR: customer-facing vs internalOpenAI
- LogicBranch into customer and internal buckets
- ActionPublish customer changelog note to IntercomIntercom
- OutputPost technical recap as Linear updateLinear
What it does
One release, two audiences. The workflow reads the PRs in a release, decides which changes customers will notice versus which are internal-only, and produces two separately-toned summaries: a friendly, jargon-free note for customers and a precise technical recap for the engineering org.
When to use it
When the same release needs both a public-friendly announcement and an internal record, and you don't want one team's noise leaking into the other's view. Great for product-led teams shipping continuously.
How it works
- 1A GitHub release-published event triggers the flow.
- 2It pulls the merged PRs for the release with their labels and descriptions.
- 3An OpenAI step classifies each PR as customer-facing or internal based on labels and impact.
- 4A logic branch splits the set into two buckets.
- 5The customer-facing bucket is rewritten as a warm changelog note and posted to Intercom.
- 6The internal bucket is summarized technically and written as a Linear project update.
Set it up
What you configure once, before turning it on.
- 1Connect GitHubRepos, issues, pull requests, actions.
- 2Connect OpenAIModels, embeddings, files.
- 3Connect IntercomConversations, contacts, articles.
- 4Connect LinearIssues, projects, cycles, triage.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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Run it inside a business
This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.

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