AI AGENTS

New Error Pattern to Linear Triage

When Axiom detects a log pattern that never appeared before a deploy, an agent decides if it is a real regression and, when it is, files a deduplicated Linear issue with sample…

CategoryAI Agents
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerAxiom monitor on new error patternAxiom
  • ActionFetch sample events and trendAxiom
  • ActionLLM classifies regression vs noiseOpenAI
  • LogicDedupe against open Linear issuesLinearLinear
  • OutputFile or comment Linear issue and ping SlackSlack

What it does

This agent watches for genuinely new error-shaped log patterns that surface right after a deploy. For each one it decides whether it looks like a real regression worth tracking, and if so opens a Linear issue with representative samples, frequency, and the deploy commit that likely introduced it. It dedupes against open issues so the same pattern never files twice.

When to use it

Use it when new errors slip through because they are low-volume at first and only get noticed once they spike. This catches the first occurrence and routes it to the team's tracker with enough context to act.

How it works

  1. 1An Axiom monitor fires when a previously unseen error template crosses a small occurrence threshold.
  2. 2The agent pulls sample events and the count trend for that pattern.
  3. 3An LLM step classifies it as regression, transient, or expected noise, and drafts a title and description.
  4. 4A logic step checks Linear for an existing issue matching the pattern fingerprint and skips if found.
  5. 5It creates or comments on a Linear issue, then notifies the owning team in Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AxiomLog streams, queries, dashboards.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  4. 4
    Connect OpenAIModels, embeddings, files.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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