How Linear brought AI from bug reports into reviewed fixes

The problem.

Bug investigation needs more than a short issue title. Linear wanted an agent’s first pass to include the surrounding discussion, relevant code and diagnostic evidence.

What changed.

Its June 2026 release connected Linear Agent to Claude Code and Codex. The documented workflow runs coding sessions in a managed environment, creates a pull request and presents the changes for review before merging.

As described by Linear and Linear.

What was reported.

Linear reported resolving roughly 30% of incoming bug reports with its internal workflow, mostly on the first pass. This is the company’s reported experience with that workflow. Source: Linear

What we take from it.

For an application team, the valuable unit of work is a verified repair. We would start with a small group of recurring, reproducible issues and establish what a correct result looks like. A report should explain the affected journey, what happened and what the person expected. A useful attachment could be a redacted error trace or a minimal example. That gives the investigation something concrete to test.

The review needs to follow the behavior through the application. A repaired filter, for example, should return the right records, preserve access restrictions and behave sensibly when there are no matches. We would compare the proposed change with the reproduction steps and inspect nearby behavior that could be affected. Clear ownership matters here: someone should decide whether the evidence is sufficient for release and handle questions the agent cannot settle.

A trial should account for the complete cost of reaching that decision. We would record investigation time, review time, corrections and any reopened issues alongside accepted fixes. Results should be separated by issue type so easy repairs do not hide failures on harder work. Keeping the original report, proposed change and verification together gives the team a record it can learn from as the trial expands.

How to evaluate a similar idea.

Start with your situation and a question you can test. These are evaluation steps we would discuss before choosing an implementation.

1. 01

   Choose a bounded issue set

   Begin with recurring problems that have clear reproduction steps and an owner who can verify the repair.

2. 02

   Prepare useful evidence

   Include expected behavior, relevant diagnostics and necessary context, with sensitive information removed where appropriate.

3. 03

   Review the affected journey

   Check the original failure, permissions and nearby behavior before deciding whether a change is ready to release.

4. 04

   Count the follow-up work

   Track review effort, corrections and reopened issues. Compare similar issue types when evaluating the trial.