One method to lead your team and your agents.

People and AI agents on the same board need a shared method. This is Hilbana's: how an idea becomes a task, who picks it up, who reviews it and what your agents remember for next time.

One board, two kinds of worker.

Hilbana coordinates people and agents over the same issues. The team and the agents read the same board, take work under the same rules and leave a trail in the same place. You set the direction; the method keeps anyone from getting lost or stepping on each other.

Who's it for?

For teams already working with AI agents, or about to, who are done copy-pasting instructions every session.

From idea to done, without losing the thread.

Five pieces so people and agents hand work to each other without dropping it.

  1. 01

    Context on every task

    Every issue carries its instructions, the files it touches, how to verify it and what counts as “done”. The agent does what you expect and the reviewer knows what you asked for.

  2. 02

    Agent-ready queue

    You mark an issue as “agent-ready” when it has everything it needs and nothing blocks it. Agents pull the next one from the queue; you decide what goes in.

  3. 03

    No collisions

    When an agent takes an issue, it locks it. Two agents don't work the same task at once, and your team sees what's in whose hands.

  4. 04

    Control through review

    The agent leaves its work “in review” and a person (or a reviewer agent) approves it or sends it back with notes. Closing belongs to the reviewer.

  5. 05

    Memory that lasts

    When the work is done, the agent saves what it learned: decisions and conventions. On the next task, and the next project, it already remembers, and you don't explain it again.

Issues
DRAPPS-318 Export reports to PDF 🤖
DRAPPS-314 Migrate the sync pipeline 🤖

Who does what.

The method splits the work: everyone knows what's theirs.

  1. The personSets the goal and breaks the work into issues.

    The agentPulls the next ready issue from the queue.

  2. The personWrites the context: what to do and how to verify it.

    The agentWorks from the task's context, no guessing.

  3. The personDecides what's ready for an agent.

    The agentLeaves its work in review; closing belongs to the reviewer.

  4. The personReviews and approves what's delivered.

    The agentRecords what it did and saves what it learned.

Get the most out of it.

Write good context

An agent is only as good as its context. Be specific: the files, the command to verify and a definition of “done” that leaves no doubt.

Actually review

Review is your safety net: check against the definition of “done”, with the issue in front of you. Send work back with clear notes and the agent does better next time.

Let it remember

Save decisions and conventions once and your agents apply them from then on. The more they work, the more they know your way of doing things.

Start working like this today.

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