Concepts
The ideas behind kanman: teams, stories, runs, the outcome gate, decisions, policies, budgets, conventions and maintenance mode.
Read these pages to understand what kanman does on its own, where it stops and asks, and how it proves its work.
Teams
A team is one AI team: one tracker project, one or more repositories, one policy, and a board that mirrors your tracker.
Stories and acceptance criteria
A story is a small, verifiable piece of work with acceptance criteria and a Demonstrate block that shows the outcome.
Runs
A run is kanman working on one story: planning, implementing, verifying and handing over, with every attempt, cost and decision on one page.
The outcome gate and evidence
kanman never takes the executor's word for it. The outcome gate proves each story against its acceptance spec, and the evidence pack shows the proof.
Decisions
Everything that needs a human lands in one place: the decision inbox. Each decision comes with kanman's recommendation and a few clear options.
Policies, presets and authority levels
Each team has one policy: what kanman may touch, how much it may spend, when a human must approve, and which choices it may make alone.
Budgets and cost
Hard spending limits per run, per day and per month, a cost meter on every run, and two ways to pay for model usage.
Conventions (team memory)
kanman learns your team's rules from review feedback, turns repeated objections into conventions, and shows you exactly what it learned and why.
Maintenance mode
With the Hardening preset, kanman looks after the codebase between stories: dependency updates, vulnerabilities, broken links and drift, as a steady, capped trickle of small stories.