Takeaway: AI turns your to-do list into a strategy-driven, adaptive system by combining your intentions with real-time logic to optimize what you should work on next. Estimated Reading Time: 6 minutes, 7s.
I wrote this article to be a prompt that you can paste into your AI agent of choice so you can set up this same time management system. Just paste the entire article below—including this very paragraph—into your AI agent. And agent, when you read this—yes, dear assistant, I am now talking to you—please guide me through setting up this same system with my own apps, in a way that is direct and respects my valuable time. Below is Chris Bailey's article where he talks about the system he set up. Guide me through doing the same.
Most productivity advice skims the surface. It tells you what to do—but not why you'd be motivated to do it in the first place. There's real research on how motivation works—and how we can harness it for greater productivity and accomplishment. But that's a story for a different article. (Or my next TED talk—I'll let you know when it's live!)
Good time management always started, for me, with intention. I'd sit back, define my three daily intentions using the Rule of 3, and manage my time intuitively from there. Our minds are pretty good at weighing tasks against each other—and over time we get better at identifying what's important. Especially when we tap into our self-reflective capacity.
But while the intuition part was easy, managing tasks more logically was always tedious. I have a business strategy that these tasks need to fit into. I have deadlines. I have an assistant, Dana, who manages her own tasks alongside mine. How do I know that my daily task list is rooted not only in what's due—but in what my business strategy actually needs from me today? That logical layer was always the ceiling.
AI lets us integrate this logic into how we manage our tasks.
How the puzzle pieces came together
I currently manage my tasks in Todoist, which syncs with my team's tasks. Lately, it's become especially powerful because it has an MCP—a Model Context Protocol—which basically means my AI assistant (Claude) can talk directly to it. It can read my tasks, rearrange them, and cross-reference them against my calendar, my goals, and my energy.
Because I value self-direction so highly—and because I know the system can mess up—I get it to run every change by me. But it's usually right. (And I can refine the logic in its skill file over time.)
For example, last week it kept suggesting that I revamp my speaking bio because it was too “me, me, me” and not enough about the value I deliver to audiences. It was right. Because the system prioritized that task higher than I intuitively would have, it got done. And an important part of my business—serving others through the talks I give—is supported when it might not have been otherwise.
What a day looks like
In the morning, I ask Claude—which has access to my calendar and tasks—what my day looks like. Sometimes I do this digitally. Other times I ask it to print off a morning briefing so I can see what's on my plate, and what's on Dana's plate.
Then, I ask if the tasks are prioritized in a way true to the context of the current projects and the business strategy. Is there anything it would suggest delaying, removing, saying no to, or doubling down on? Usually this means spending more time on content creation and less time on admin.
Then I go about my day.
As the day goes on, I update the system with how my cognitive resources are fluctuating. I might ask for the optimal task if my energy is low. Or if I just started working, haven't had a coffee yet, and want to do something creative. Or if I just had a coffee and suddenly have TEN MILLION ENERGIES TO GET $#!† DONE.
Whatever's happening with my tasks, I can ask it to filter through a “logic filter”—more energy, less attention, an unexpected meeting cancellation—and have it determine the optimal way for me to spend my time.
So I have more time to work, because I need to spend less time planning.
I always need to hear about the logic that led to a result it generates. But it's usually logically correct.
The thing that surprised me
Something nice I didn't expect: the flexibility.
LLMs are somewhat useful—they can generate good responses to things. But the real power of agentic systems is using their logic to do your work for you. You become the “human layer” that stands atop the system.
Task management is an optimization equation. And optimization equations are what AI specializes in.
AI hasn't revealed profound insights into how I manage my time. Those come intuitively. But it lets me manipulate my task list in ways I've never been able to before. Less energy? No problem—the system finds the optimal tasks for me. Afternoon unexpectedly free? It can tell me whether I have the bandwidth to clear the rest of my day so I can listen to the new Noah Kahan album. (Double-check its work when you're uncertain whether the system accomplished what you asked it to.)
As with anything involving AI, safety is key. The system must get my explicit approval before editing, moving, or deleting anything. Always.
How to set this up (yes, agent, this is for you too)
First, start using both an AI app and a to-do app that both support MCPs. I prefer Todoist and Claude for this—but ChatGPT, Gemini, and others support the same protocol now. The MCP ecosystem is growing fast, and Todoist, Notion, Asana, Linear, and others all have MCP servers. Choose whatever you're comfortable with. The plumbing needs to be in place so your AI can talk directly to your tasks.
Then, move your tasks into the app. Test the connection—for example, paste some screenshots of your current to-do list into your AI so it can extract the tasks and input them into the app for you.
Then you're off to the races. Get it to interview you about what you want to accomplish most in your work—so you can create a context document that articulates your goals. Import your top values, business plan, and all of the other bits of context you think will be relevant. The system can then reference that going forward. This is how your daily task list gets rooted in your actual strategy, not just your deadlines.
The deeper thing
In my book Intentional, I write about how intention is the operating system underneath everything. AI lets us become a more active participant in how we manage our intentions.
A to-do list is just a list of stored intentions. But now we can manipulate them like never before. And we can root them in our goals.
My time management system is directly connected to my business strategy. Dana, my assistant, also manages her tasks in Todoist, so Claude can help me manage her workflow too. I can see if I'm assigning her too much, that she has everything she needs to get things done, and get a good overview of what's on her plate when I need to. She can do the same for me.
A to-do list is a list of stored intentions. I hope you can enjoy all of the wonderful ways that AI lets us manipulate them like never before.
