AI in Project Management Tools & The 3-Question Test | Sanjana
Sanjana, a project manager at Humanitarians AI, explains how to use the AI features now built into project tools without treating them as autopilot. She offers a three-question test and a four-verb rule for deciding what AI drafts and what people decide.
AI has quietly arrived inside project tools such as Jira, Trello, Asana and Notion. It can write tickets, summarize a stand-up, and suggest what to do next. Sanjana, a project manager at Humanitarians AI, argues that the real question is not whether it is smart but which project work you should hand to it and which you should keep. The video answers with a simple three-question test.
Autopilot or fast intern
The central idea is that the AI in these tools will not run the project for you. What it is good at is busy work: turning notes into tickets, summarizing, and tidying. The judgment stays with you.
The video describes a familiar pitch, that an AI button will basically manage your project. Lean on it that way and it will confidently commit dates it has no way to know, working from a board that is half out of date. It does not fail loudly. It fails politely, with a clean-looking answer. Treated as an autopilot it is a liability; treated as a very fast intern it is a gift.
The three questions
Before handing anything to the AI, the video suggests asking:
- Is it mechanical? Is the task reshaping information that already exists (summarizing, drafting, sorting), or is it a call such as choosing what matters?
- Is it reversible? Can you check it in seconds and undo it, or do teammates act on it the moment it is posted?
- Is the truth actually in the tool, or does it live in someone's head, a client call, or a Slack thread the AI cannot see?
Three greens means let the AI draft it. Any red means the AI can suggest, but a human decides.
A task that passes: stand-up notes into tickets
In the first worked example, a messy stand-up note is handed to the AI with the instruction to turn it into clean tickets, decide nothing, and set no dates. Four messy lines come back as four clean cards: two bugs, a content task, and an ops note, each with a type and a rough size. Scored against the test, it is mechanical, fully reversible because all four cards can be read and fixed in about ten seconds, and everything it used was in the note. Three greens, and ten boring minutes saved.
A task that fails: committing the sprint
The same tool and the same AI are then asked to pick the sprint and commit the dates. This scores three reds. Choosing what matters is a judgment call, the moment dates are posted five people plan around them, and the reason for the real priority was a customer call that never made it onto any card. The video adds a subtle case: even a request to summarize progress turns red if the board is stale, because the AI will then report fiction with confidence.
The four-verb rule
The video turns this into a rule that works in any tool. Give the AI the two verbs it is built for: draft and surface. Let it draft tickets, summaries and first passes, and let it surface what is stale, unowned or blocked. Keep the two verbs that need a person: decide and commit. What the team does this sprint, what date it promises, and how someone is doing are human calls. The skill is not using AI or avoiding it, but knowing where the line is.
Key takeaways
- Treat built-in project-tool AI as a fast intern, not an autopilot.
- AI is strong at busy work: notes to tickets, summaries, tidying.
- Test any task: is it mechanical, is it reversible, and is the truth in the tool?
- Three greens means the AI can draft it; any red means a human decides.
- AI should draft and surface; people should decide and commit.
- A stale board turns even a simple summary into confident fiction.
- A good AI answer returns clean drafts plus a short list of questions it cannot answer itself.
Try it yourself
Open your own board and paste in a real mess, such as loose notes, half-written cards, or a stand-up transcript. Ask Claude to draft the tickets and surface what is stale, but to stop at judgment: it should not pick the sprint or commit dates, and for every call it cannot make it must ask you the one question it would need answered. If it quietly makes the decisions for you, you have found exactly what to catch.
Chapters
- 0:00Introduction: AI Features in Jira, Trello, Asana, and Notion
- 0:25Autopilot vs. Fast Intern: Knowing AI's Limits
- 0:50The 3-Question Test for Task Delegation
- 1:15Practical Walkthrough: Converting Standup Notes into Clean Tickets
- 1:40The Autopilot Trap: Committing Dates and Stale Boards
- 2:05The 4-Verb Rule: Draft & Surface vs. Decide & Commit
- 2:30Hands-On Prompt Exercise: Auditing Your Own Project Board
Full transcript(auto-generated, with timestamps)
Introduction: AI Features in Jira, Trello, Asana, and Notion
[0:00]Hi, I'm Sanjana, a project manager at Humanitarian's AI, and this video is about the AI that just showed up inside your project tools Jira, Trello, Asana, Notion. It can write your tickets, summarize your stand-up, even suggest what to do next. So, the real question isn't whether it's smart, it's which of your project work you should actually hand to it and which you should keep. I'll give you a three-question test for exactly
Autopilot vs. Fast Intern: Knowing AI's Limits
[0:25]That. Here's the whole idea in one breath. It's tempting to think the AI in these tools will run the project for you. It won't. What it's genuinely good at is the busy work turning notes into tickets, summarizing, tidying. The judgment stays yours. So, here's the situation. Almost every board you open now has an AI button, and the pitch is always the same. Point it at your project and it'll basically manage it.
The 3-Question Test for Task Delegation
[0:52]But, watch what happens when you actually lean on it. Ask it to run the sprint and it will confidently commit dates it has no way to know. Off a board that's half out of date. It doesn't fail loudly, it fails politely with a clean-looking answer. Treat it like an autopilot, it's a liability. Treat it like a very fast intern, it's a gift. So, before you hand anything to the AI, run it through one test. Three
Practical Walkthrough: Converting Standup Notes into Clean Tickets
[1:16]Questions. One, is it mechanical? Reshaping information that already exists, summarizing, drafting, sorting, or is it a call like choosing what matters? Two, is it reversible? Can you check it in seconds and undo it, or do teammates act on it the moment it's posted? Three, is the truth actually in the tool, or does it live in someone's head, a client call, a Slack thread the AI can't see?
The Autopilot Trap: Committing Dates and Stale Boards
[1:42]Three greens, let the AI draft it. Any red, the AI can suggest, but a human decides. Let's run a real one. Here's a stand-up note, the kind of half-sentence mess we all paste into a board. Watch me hand it to the AI, but only for the mechanical part. Turn this into clean tickets. Don't decide anything. Don't set dates, just draft. And there it is.
The 4-Verb Rule: Draft & Surface vs. Decide & Commit
[2:05]Four messy lines became four clean cards, a bug, a bug, a content task, and ops note, each with a type and a rough size. Now, score it on the test. Mechanical? Yes, it just reshaped what I already wrote. Reversible? Completely, I can read all four in 10 seconds and fix any of them. In the tool? Yes, everything it used was right there in my note. Three greens. This is exactly the work to hand over, and it just saved me the boring 10 minutes. Now, the trap
Hands-On Prompt Exercise: Auditing Your Own Project Board
[2:31]Because AI is helpful on my board is too easy to believe. Same tool, same AI, one step further. Pick this sprint and commit the dates. Score it. Mechanical? No, that's a judgment call about what matters. Reversible? No, the moment it's posted, five people plan around it. In the tool? No, the reason we're doing the export work first is a customer call that never made it onto any card. Three reds. And here's the sneaky one. Even just summarize our progress turns red if the board is stale, because now the AI is confidently reporting fiction. The test is what tells them apart. So, here's the rule you can carry to any tool. Give the AI the two verbs it's built for, draft and surface. Draft the tickets, the summaries, the first pass. Surface what's stale, unowned, or blocked. Keep the two verbs that need a human, decide and commit. What we do this sprint, what date we
Promise, how someone's doing. Run the three question test when you're not sure which side a task is on. That's the whole skill, not use AI or don't, but knowing where the line is. Your turn. Open your own board and paste a real mess into clawed loose notes, half-written cards, a stand-up transcript. This prompt tells it exactly where the line is. Draft the tickets and surface what's stale, but stop at judgment. Don't pick the sprint or commit dates. And this is the important line. For every call it can't make, it has to ask you the one question it would need answered. A good answer comes back with clean drafts and a short list of questions. A bad one quietly makes the decisions for you and now you know that's the exact thing to catch. AI in project management tools with Sanjana Rao for humanitarian's AI. Let it draft and surface. You decide and commit. Thanks for watching.
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