PROJECT MANAGEMENT

CEO Agent That Proposes a Deadlock Break Plan

When a circular dependency is found in Linear, an agent reasons over the blocked issues to recommend which single link to cut to break the loop with least disruption.

CategoryProject Management
Enginepaperclip
Difficultyadvanced
Triggerschedule
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerRun starts with a confirmed cycle
  • ActionFetch full issue detail for the loop from LinearLinearLinear
  • ActionAgent ranks edges and picks least-disruptive link to cutOpenAI
  • LogicBranch: confidence high enough to auto-route?
  • OutputPost break plan to leads in Slack for approvalSlack

What it does

Finding a deadlock is only half the job; someone still has to decide which dependency to sever. This workflow hands the detected cycle to an agent that weighs issue priority, effort, and assignee load, then recommends the single least-disruptive link to break and explains why, so leads approve a plan instead of debating from scratch.

When to use it

Use it when your team finds deadlocks but stalls on resolving them. The agent turns a raw cycle into an actionable, justified proposal that a lead can accept or override.

How it works

  1. 1A schedule or upstream detector triggers the run with a confirmed cycle.
  2. 2Fetch full detail for every issue in the loop from Linear, including priority, estimate, and assignee.
  3. 3The agent reasons over the loop to rank candidate edges by disruption and pick the best link to cut.
  4. 4It drafts a plain-language break plan with the rationale and the affected issues.
  5. 5Branch: if confidence is high enough, route to leads; otherwise flag for manual review.
  6. 6Post the proposed plan to the project leads in Slack with approve / override actions.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect LinearIssues, projects, cycles, triage.
  2. 2
    Connect OpenAIModels, embeddings, files.
  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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