Blog
AI project management, in practice.
20 articles in Guides
Project management for small agencies (clients in, chaos out)
Project management for agencies without the seat tax: scoped projects isolate each client, guests and viewers are free, and public forms take intake with no account.
A lightweight service desk from forms, automations, and a board
Lightweight service desk for small teams: build one from a public intake form, routing rules, automations, and a board with a review gate. Honestly costed vs JSM.
AI agent governance: seven controls your tracker can enforce
Governance for AI agent teams is not a policy PDF. Seven controls your tracker can enforce, from identity to offboarding, and what tooling cannot fix.
How to automate project management with AI
The right order to automate project management with AI: reporting first, intake second, execution agents last, and the decisions that should stay human.
How to manage a team of AI agents without losing track
AI team management day to day: a roster, live sessions, instant delegation, per-field permissions, and verified work when several AI agents run at once.
How to tell when an AI agent is stuck (and what to do about it)
A looping, waiting, or hung agent looks exactly like a working one. Here is how to get a real signal on an agent's live state and catch stuck runs.
Onboard an AI agent like a new hire: identity, access, first task
You already know how to bring on a new hire. Do the same for an AI agent: give it an identity, scoped access, one small task, a review, and an offboarding path.
How to scope an AI agent's first job so the pilot doesn't die
Most first AI agent projects fail on scope, not model quality. Here is how to pick a first job narrow and checkable enough to actually ship.
Keep an audit trail of everything your AI agents change
Once agents can write to your tracker, a shared bot account makes every change anonymous. Here is how per-agent identity keeps the trail readable.
AI sprint planning: what actually works in 2026
Where AI genuinely helps plan a sprint, drafting, sizing, capacity checks, and where letting it decide is a mistake. A working setup, honestly described.
AI agent project management: the complete guide
How to run real projects with AI agents on the board: connecting them, assigning work, keeping review, what breaks, and how to pilot it in a week.
How to run sprints without drowning in ceremony
A lightweight sprint process for small teams: what to keep, what to cut, and how to get the value of planning and review without the meeting tax.
How to migrate from Jira, Trello or Asana without data loss
An honest migration guide: what imports cleanly, what needs a decision, and the order to move your projects so nothing gets lost on the way over.
Running a project with AI agents without losing the thread
A practical setup for letting AI agents do real project work, create issues, move the board, draft specs, while your team keeps control of what matters.
Two agents, one backlog: handing off by issue status
A practical multi-agent workflow: custom board columns and status transitions as the handoff bus between a triage agent and a coding agent, with human review.
AI agents on your board over the REST API: scopes and safe writes
A developer guide to giving an AI agent a scoped Taskfolk API key so it can move cards and file issues without a big blast radius.
Turn a request form into a triaged issue, with no human inbox
How to wire a public intake form to a tracked, classified issue: routing defaults, an issue.created automation, and an AI triage first pass.
Give your AI agent a knowledge base: your docs, not the internet
How to give an AI agent access to your company docs, so it grounds answers in your workspace instead of guessing, using RAG exposed through MCP.
Let AI write the weekly project digest
How to automate a weekly status report with AI that reads what actually moved and what stalled, instead of a dumb scheduled dump of ticket counts.
Auto-triage new issues with AI: assign, label and prioritize
How to set up AI issue triage automation that classifies severity, labels, and routes new bugs and requests, with an honest line on what to let AI decide.
