AI AGENTS

Open a triaged Linear remediation ticket from a recurring Sentry regression

When a previously resolved Sentry issue regresses, an agent diffs it against the prior fix, drafts a remediation ticket in Linear with proposed steps and an owner.

CategoryAI Agents
Enginepaperclip
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSentry resolved issue regressesSentrySentry
  • ActionFetch new event and original resolving releaseSentrySentry
  • LogicDiff against prior fix, estimate severity and owner
  • ActionCreate triage-state Linear remediation ticketLinearLinear
  • OutputNotify suggested owner for sign-offSlack

What it does

Catches regressions and turns them into actionable, pre-triaged work. When Sentry reopens an issue that was previously resolved, the agent compares the new occurrence to the old fix, identifies what likely broke again, and creates a Linear ticket with a proposed remediation plan, severity, and suggested assignee. The ticket starts in a triage state awaiting human sign-off.

When to use it

Use it when regressions slip through and quietly re-accumulate errors before anyone notices. Good for teams that live in Linear and want regressions to become well-scoped tickets automatically rather than getting lost in alert noise.

How it works

  1. 1A Sentry regression alert fires when a resolved issue reopens.
  2. 2The agent fetches the new event details and the original resolving release or commit.
  3. 3Decision logic compares the two, estimates severity, and proposes a remediation approach plus an owner.
  4. 4It creates a Linear ticket containing the plan, links, and labels, set to a triage status.
  5. 5It notifies the suggested owner so a human accepts or reassigns before work begins.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect SentryErrors, performance, releases.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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