Most advice on how to delegate tasks to AI stops at "write clear instructions and define success criteria." True, but useless on its own — you could say the same about delegating to a new hire. The part that actually determines whether delegation works is what happens after you hand off the task: how you review it without babysitting it, and what happens the moment the AI hits something it shouldn't decide alone. We built Comuna's AI coworker around exactly that loop, so this is the version of the advice that includes the part everyone else skips.
What can you actually delegate to an AI today?
Reversible, well-specified, low-judgment work — the same category any manager hands to someone new. Drafting cards or tickets from a messy meeting transcript. Triaging an inbox or backlog by type and urgency. Chasing stale items for a status update. Filling in a recurring checklist. Summarizing what changed this week.
What doesn't belong on that list yet: final calls between two reasonable priorities, anything that ends in reassigning or removing a person's ownership, and irreversible actions — deleting a project, closing an account — without a confirmation step. That's not a limitation unique to any one tool; it's true of every AI agent honest enough to say so.
How do you write instructions an AI will actually follow?
State the outcome, the boundary, and what "done" looks like — in that order, every time. "Clean up the backlog" is a vibe, not an instruction; an AI (like a new hire) will guess at what you meant and guess wrong half the time. "Label every card in the Support column by urgency using our existing three tags, and flag anything older than 5 days for me to look at" is a task an AI can actually execute and you can actually check.
Three things belong in every delegated task, not just the complicated ones:
- The outcome. What does the finished task look like, concretely? Not "improve the docs" — "add a troubleshooting section to the setup guide covering the three errors support tickets mention most."
- The boundary. What's explicitly off-limits — don't delete anything, don't message the client directly, don't close a card without a resolution note.
- The definition of done. How will you (or the AI) know the task is finished, not just started? A checklist beats a vague goal.
Standing instructions work the same way but persist: "always leave a resolution note when you close a card" is a boundary you only have to set once.
How do you review delegated work without micromanaging it?
Review the output, not the process — and only the outputs that changed. If an AI moved twelve cards this week and eleven were routine triage, reading the activity log for all twelve defeats the point of delegating. The fix is to review by exception: skim a daily or weekly summary of what changed, and only open the item the AI itself flagged as uncertain.
This only works if the summary is honest about what actually happened, not a generic "all tasks completed" message. Comuna's Daily Brief exists for exactly this — a short note of what the AI coworker touched and finished, delivered only on days it did something, so you're not scanning empty updates to find the one that mattered.
A useful rule of thumb: match the review cadence to the reversibility of the work, not to how much you trust the AI that day. Routine, reversible triage (labels, status nudges, checklist fields) can go a full day or week between reviews — if it's wrong, fixing it costs a click. Anything closer to irreversible (closing a project, messaging a client, deleting something) should never wait for a scheduled review at all; it belongs in the escalation loop below, checked before it happens rather than after.
What should the escalation loop actually look like?
The AI should stop and ask, not guess, the moment a task stops being mechanical. In practice that means: when it hits a decision that depends on taste rather than a rule — "should this go to Done or Blocked," "which of these two overlapping cards is the real one" — it opens a specific request instead of picking an answer and moving on.
A good escalation names the choice, not just the fact that one exists. "I'm not sure if this card should be marked Done — the checklist is complete but there's an open comment asking for review. Approve as Done, or should I leave it In Progress?" is reviewable in five seconds. "I had a question about card #34" is not. In Comuna, this shows up as a small request in your inbox — you approve, ask for changes, or reject, and the AI picks up your answer on its next run.
How do you know what the AI actually did, after the fact?
Attribution, not trust, is what makes delegation auditable. If every AI-made change is signed — this card moved because Claude moved it, this comment is ChatGPT's — you can check what happened after the fact instead of taking a "task complete" message on faith. That matters more a year into delegating than it does on day one, once you've forgotten which of last Tuesday's forty changes were yours and which were the AI's.
This is where most delegation advice online goes quiet: it tells you to "monitor outputs" without saying how you'd actually distinguish an AI's edit from a human's after the fact. Comuna signs every AI action with its own badge — no anonymous "system" edits — specifically so review by exception (above) has something concrete to check.
Does the AI work on its own, or only when you ask?
Only when triggered — and any delegation advice that implies otherwise is overselling it. AI coworkers connected via MCP (Claude, ChatGPT) are pull, not push: they act when you open a chat and ask, or when a scheduled prompt fires, not continuously in the background watching your board. The realistic pattern people use is a recurring scheduled prompt — once a morning, "check the board and do what's safe" — which gets you something that feels ambient without pretending the AI is awake 24/7 on its own initiative.
That's a real boundary, not a workaround. Delegation that assumes always-on autonomy sets an expectation no current AI agent meets honestly.
Frequently asked questions
How do I delegate tasks to AI without losing control of the outcome?
Give it the outcome, the boundary, and the definition of done up front, then review by exception instead of re-checking everything: skim a summary of what changed and open only the items the AI flagged as uncertain. The control comes from the escalation step, not from watching every action live.
What tasks should I delegate to AI first?
Start with reversible, well-specified, low-judgment work: drafting cards from a transcript or note, triaging a backlog, chasing stale items for status, filling recurring checklists. Our deeper breakdown of what agents can and can't do yet is in AI agent task management: what actually works.
Can I trust an AI to know when NOT to act?
Only if the tool is built to escalate instead of guess. The honest agents stop and ask when a decision needs judgment rather than a rule — reassigning ownership, closing something ambiguous, deleting anything. If a tool never asks you anything, that's not confidence; it's a missing escalation path.
Does delegating to AI mean it works while I sleep?
Not automatically. MCP-connected AI (Claude, ChatGPT) is pull, not push — it acts when you or a scheduled prompt trigger it. A daily scheduled prompt gets you close to "handled overnight," but it isn't a background process running unsupervised.
Comuna's AI coworker is built around this exact loop — instructions, review by exception, escalation — directly on your Kanban board, free with no paywalled tier at comuna.work/free. To connect Claude or ChatGPT, see our integrations. For what's realistic to hand off today, read AI agent task management: what actually works.
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