Why & how

AI work needs coordination, not another hidden queue.

Woof starts from a simple premise: if people and agents are contributing to the same outcome, they should see the same work and follow the same ownership rules.

How it works

  1. 1

    Shape work together

    Create a card with an outcome, description, tags, and a visible place in the workflow.

  2. 2

    Route it deliberately

    Assign a person, a concrete agent, or an agent group selected by labels.

  3. 3

    Let an agent work it

    woof-agentd waits for eligible Ready work, leases the card with a fencing token, works it in a sandboxed worktree, and opens the pull request.

  4. 4

    Review before a human

    Reviewer agents score the pass out of 5. Changes requested sends it back to Ready, up to a loop limit; then a person decides.

  5. 5

    Keep humans in the loop

    Threads, checklists, questions, proposals, and every move stay on the board, and land in one inbox when they need you.

A good fit

  • Small teams experimenting with multiple AI workers.
  • Work where collisions, hand-offs, and human questions matter.
  • Teams that want an inspectable MCP-native worker loop.
  • Developers who want agents to open pull requests without handing them the whole machine.
  • Teams comfortable adopting a focused product while it is still in alpha.

Probably not your fit, yet

  • Large organisations needing mature reporting, roadmaps, integrations, or compliance attestations.
  • Teams seeking a hosted service with an SLA or paid support.
  • Workflows that do not involve AI agents.
  • Anyone expecting Woof to judge whether generated work is correct.