PROJECT MANAGEMENT

Monday WIP-Limit Enforcer with Owner DM Rebalance

Watches a Monday board for columns that exceed their WIP limit, drafts a rebalance plan with an LLM, and DMs the column owner on Slack to confirm before any cards move.

CategoryProject Management
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerEvery 30 minutes (schedule)
  • ActionFetch board items grouped by status columnmonday.com
  • LogicFlag columns over their WIP limit (from Postgres)PostgreSQLPostgres
  • ActionDraft rebalance plan with OpenAIOpenAI
  • ActionDM column owner with Approve/Skip on SlackSlack
  • OutputApply approved moves to Monday and log decisionmonday.com

What it does

Keeps a Monday board honest about work-in-progress limits. When a status column holds more items than its configured cap, this workflow builds a concrete rebalance proposal (which items to defer or reassign) and asks the human owner to approve it over Slack before touching the board.

When to use it

Run this when your team agrees on WIP caps per column but they quietly drift. Good for Kanban-style delivery boards where overflow signals a bottleneck, and you want a person — not a bot — to sign off on what moves.

How it works

  1. 1A schedule fires every 30 minutes and the flow pulls the board's items grouped by status column from Monday.
  2. 2A logic step compares each column's count against its WIP limit stored in Postgres and stops if nothing is over.
  3. 3OpenAI ranks the overflow items by staleness and dependency and drafts a plain-language rebalance plan.
  4. 4The flow looks up the column owner and sends a Slack DM with the plan plus Approve / Skip buttons.
  5. 5On approval, the moves are written back to Monday and the decision is logged to Postgres for audit.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect monday.comVisual work management for teams.
  2. 2
    Connect PostgresAny Postgres URL — query, write, migrate.
  3. 3
    Connect OpenAIModels, embeddings, files.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  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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