Connect Linear and GitHub in AACFlow to automate bug triage, sprint tracking, and PR workflows — powered by AI agents and webhook triggers.
Every engineering team runs the same manual loop: a bug is reported in GitHub Issues, someone copies it into Linear, a team lead manually assigns it, and then Slack fills up with messages asking who owns what. Sprint reviews mean cross-referencing GitHub PRs against Linear issues by hand. Release tracking is a spreadsheet. The automation that should exist simply does not — because wiring together two different systems with real intelligence has always required custom code, dedicated infrastructure, and ongoing maintenance. AACFlow removes that barrier entirely.
AACFlow is an AI workflow platform that connects Linear and GitHub through native connectors and webhook triggers, letting engineering teams automate bug triage, sprint tracking, and PR-to-issue workflows using AI agents powered by Claude Sonnet 4.6 — no custom code required.
Create PR — open a pull request with title, body, base branch, and reviewers
Merge PR — merge a pull request when conditions are met
Create Issue — open a GitHub issue with labels and assignees
Get Repo — retrieve repository metadata
List PRs — fetch open or merged pull requests with filters
Both connectors authenticate via OAuth — you connect your Linear workspace and GitHub organization in AACFlow's credential store once, and every workflow in your workspace can use them without re-authenticating.
Triggers are what make automation reactive rather than scheduled. AACFlow supports webhook triggers for both systems, and setting them up takes under two minutes.
To set it up, add a Linear Webhook Trigger block to your workflow canvas in AACFlow. The block generates a unique endpoint URL. In your Linear workspace settings, go to API → Webhooks, paste the URL, and select the event types you need. AACFlow validates the Linear webhook signature on every incoming event automatically.
Add a GitHub Webhook Trigger block in AACFlow, copy the generated URL and secret, then configure them in your GitHub repository's Webhook settings. AACFlow verifies the X-Hub-Signature-256 header — no additional authentication layer needed.
You can combine both triggers in the same workflow. A common pattern is a Linear trigger that watches for specific labels, then queries GitHub to check PR status before deciding what action to take next.
Manual bug triage is expensive. A senior engineer spending 20 minutes per bug triaging 10 bugs a day loses more than 33 hours a month — time that should go toward building. Here is how AACFlow handles triage automatically.
Trigger: Linear Webhook Trigger — fires when a new issue is created with the label bug.
Step 1 — Fetch context. An HTTP block pulls the full issue body from Linear's API, including any linked GitHub issue URL in the description.
Step 2 — AI triage. An Agent block running Claude Sonnet 4.6 receives the issue title, description, and any stack traces. The system prompt instructs the agent to:
Classify severity (P0 critical / P1 high / P2 normal / P3 low)
Identify the likely affected subsystem (auth, payments, data pipeline, frontend, API)
Suggest the best-fit team member based on ownership rules provided in the prompt context
Draft a one-paragraph technical summary for the assignee
Step 3 — Router block. AACFlow's Router block reads the AI's severity classification and routes to different branches:
P0 → immediately page via Slack, update Linear issue priority to Urgent, assign to on-call engineer
P1 → assign to subsystem owner, update priority to High, add to current sprint
P2/P3 → add to backlog, apply the correct team label
Step 4 — Update Linear. A Linear Update Issue block applies the priority, assignee, and team changes in one API call.
Step 5 — Slack notification. A Slack block sends a formatted message to the relevant team channel with issue title, severity, assignee, and a direct link to the Linear issue.
The entire workflow runs in under 15 seconds from the moment an engineer files the bug. No Slack thread needed. No manual assignment. The AI does not replace judgment — it handles the mechanical routing so humans can focus on actually fixing the problem.
The most friction-filled moment in sprint management is closing Linear issues when the corresponding code ships. Developers forget. Issues pile up as "In Progress" long after the code merged. Sprint velocity looks worse than it is. This workflow eliminates the problem entirely.
Trigger: GitHub Webhook Trigger — fires on pull_request events with action closed and merged: true.
Step 1 — Extract Linear issue ID. A Function block parses the PR title and body for a Linear issue ID. AACFlow supports a simple convention: the PR title includes the Linear issue identifier (e.g., ENG-2847) or the PR body contains a line like Closes ENG-2847. The Function block extracts this ID with a regular expression.
Step 2 — Get Linear issue. A Linear Get Issue block fetches the current state of that issue. If the issue is already completed (someone closed it manually), the workflow exits early via a Condition block.
Step 3 — Complete the issue. A Linear Update Issue block sets the issue state to the team's "Done" state. It also adds a comment with the PR URL and merge timestamp, so the issue history is traceable.
Step 4 — Notify. An optional Slack block posts to the team channel: "ENG-2847 closed — PR #1234 merged by @username." Brief, actionable, automatic.
This workflow also works in reverse. You can build a companion flow: when a Linear issue moves to "In Review," AACFlow automatically opens a draft PR in the linked GitHub repository with the issue title pre-populated as the PR name. The two systems stay synchronized without anyone having to manage the sync.
AACFlow workflows are not limited to a single trigger source. You can build workflows where a Linear event queries GitHub, or a GitHub event updates Linear based on what it finds.
A practical example: release tracking. When a GitHub tag is pushed (release trigger), an AACFlow workflow queries Linear for all issues completed since the previous tag date, groups them by team, and generates a release notes draft. The draft gets posted to a Slack channel and a GitHub release description is created automatically.
Another pattern: PR review assignment. When a GitHub PR is opened, an Agent block analyzes the changed files and cross-references them against Linear to identify which team owns that code area. The Router block then requests a review from the correct team lead and creates a linked Linear issue for tracking the review task.
Linear and GitHub are the operational backbone of most engineering teams — but they were not designed to talk to each other automatically with intelligence. AACFlow bridges that gap with native connectors, webhook triggers, and AI agents that understand context rather than just moving data between systems.
The three workflows described here — automated bug triage, PR-to-issue sync, and release tracking — represent a starting point. AACFlow's visual canvas lets your team extend them, combine them, and build new ones without writing infrastructure code. The connectors are already there. The triggers are already there. The AI is already there. You just need to describe what you want the automation to do.
