PROJECT MANAGEMENT

AI agent assesses a slipped blocker and proposes a cross-board replan

On a blocker slip in Asana, an agent walks the dependency chain across Asana and Monday, estimates the cascade delay, drafts revised target dates with rationale.

CategoryProject Management
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps5
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerAsana blocker marked slippedAsanaAsana
  • ActionAgent gathers dependency chain from Asana and MondayAsanaAsana
  • LogicLLM estimates cascade and drafts revised datesOpenAI
  • OutputPost replan proposal to Slack for approvalSlack
  • ActionOn approval, write new dates to Asana and Mondaymonday.com

What it does

When a blocking Asana task slips, an agent reads the full dependency chain spanning Asana and a linked Monday board, reasons about how the delay propagates, and produces a concrete replan: which downstream dates should move, by how much, and why. It posts the proposal to Slack for a human to approve before anything changes.

When to use it

Use it when a slip's downstream impact is non-obvious and a project lead would otherwise spend an hour manually re-sequencing dates. The agent does the chain analysis; the human keeps the decision.

How it works

  1. 1An Asana trigger fires when a blocker task is marked slipped or its due date passes incomplete.
  2. 2The agent gathers dependents from Asana and the mirrored items on the Monday board.
  3. 3Using an LLM reasoning step, it estimates cascade impact and drafts new target dates with justification per task.
  4. 4It posts the structured replan proposal to Slack with approve and reject actions.
  5. 5On approval, the agent writes the revised dates back to Asana and Monday.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect AsanaTasks, projects, milestones — everywhere.
  2. 2
    Connect monday.comVisual work management for teams.
  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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