PROJECT MANAGEMENT

Triage a late sprint ticket with an agent and recommend defer or swap

When a ticket is added to a locked sprint, an agent reads its description and the sprint's committed work, judges urgency, and either drafts a defer-to-next-cycle note…

CategoryProject Management
Enginepaperclip
Difficultyadvanced
Triggerwebhook
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerLinear issue enters locked cycleLinearLinear
  • LogicFilter to post-lock additions
  • ActionAgent classifies urgency and drafts defer or swapOpenAI
  • OutputSend recommendation to PM for confirmationSlack
  • ActionApply approved labels in LinearLinearLinear

What it does

Applies agent judgment to mid-sprint scope requests. For each ticket added after lock, the agent reads the request alongside the sprint's committed scope, classifies it as urgent or deferrable, and produces a concrete recommendation — defer to the next cycle, or swap it in for a same-size committed ticket — then routes the call to the PM for a final yes/no.

When to use it

Reach for this when late tickets need reasoning, not just point math: distinguishing a genuine production-blocker from a nice-to-have, and proposing what to give up if it must come in now.

How it works

  1. 1A Linear webhook fires when an issue enters the locked cycle.
  2. 2A logic step filters to post-lock additions only.
  3. 3An agent action reads the ticket plus committed sprint scope and classifies urgency.
  4. 4The agent drafts either a defer note or a swap proposal naming the ticket to drop.
  5. 5A Slack message presents the recommendation for PM confirmation; on approval the agent applies the labels in Linear.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LinearIssues, projects, cycles, triage.
  2. 2
    Connect SlackChannels, DMs, threads, mentions.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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.

Run this workflow in your colony.

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