I Have an AI Team. I Still Have to Be the Boss.

You explain a decision. Someone helps you think it through. You change direction. Then you ask another assistant to carry out the plan, and it gives you work based on the version of the business you already moved on from.

You correct it. You explain the change again. Maybe you update another assistant, too. Before long, you’re wondering whether managing the help has become a job of its own.

That happened to me with my AI team. Cathy, my name for ChatGPT, and I would work through an idea together. Then I’d ask Eva, my AI executive assistant, to help execute it. Eva would confidently hand me something shaped by information that was several business decisions old.

Ma’am. We have moved on.

Except, as it turned out, we hadn’t. Cathy and I had moved on. Eva had no way of knowing.

I recognized the pattern from an earlier chapter of my work. When I ran a professional organizing business, changing a system was easy while it was just me. Once I had a team, I learned that a decision wasn’t really part of the business until people knew what had changed and what it meant for their work.

I was repeating that lesson with AI.

Fast answers still need current context

AI can produce an answer quickly. That speed can make it look as though it understands the whole business. But speed of output is not depth of context.

In my setup, my AI employees work across different platforms. A useful conversation with one doesn’t automatically become shared knowledge for the others. If I change a priority in a conversation Cathy and I have had, Eva doesn’t know about it just because she’s part of my AI team.

And there’s another wrinkle: even good instructions become less useful as the business changes. The offer shifts. The audience becomes clearer. A new priority takes the place of an old one. If the information an assistant is working from doesn’t change with the business, its answers can keep pointing in the wrong direction.

That can be easy to misread as a tool problem. Maybe the assistant needs better instructions. Maybe I need another platform or a cleverer prompt. But when the real issue is that the information hasn’t caught up, changing tools won’t close the gap.

A new assistant can be genuinely useful. But it doesn’t expand the room the business has to communicate with itself. The missing piece is a clear, shared understanding of what’s currently true.

A shared reference point changes the work

I created an internal company document for my AI team. I think of it as an employee handbook, except the employees actually read it. 

It holds the information they need to do useful work: what my business does, who it serves, where it’s headed, and what we’re working toward right now. It also includes an organizational chart, so each assistant can understand its own responsibilities and what its teammates do.

That last part matters more than I expected. If I tell Cathy that Penny (my blog writer/editor) is helping me flesh out a newsletter, Cathy knows who Penny is, what she does, and why I might bring her into the work. They operate on different platforms, but they can still work from a common picture of the business.

The document isn’t a one-time setup. I review and update it weekly, and I make sure significant changes are communicated across the team. It’s my version of an all-team meeting, without coordinating calendars, stale pastries, or somebody asking a question that was answered fifteen minutes earlier.

This isn’t about creating a perfect record of every conversation. It’s about making sure the important decisions don’t stay trapped in the conversation where they happened. The information needs to be clear enough to guide the work, and current enough to reflect the business as it is now.

What changes when the team knows what matters

When Walter, my AI website developer, joined the team, he had access to the same business context as the others. He created my website so accurately on the first try that I was flabbergasted. I didn’t spend hours explaining what my business does, who I serve, or what I offer. He had the information he needed to get started.

More recently, Littlebird, an AI assistant I use to prepare meeting briefings, helped me get ready for a networking meeting. Along with background information and suggested questions, it surfaced a possibility I hadn’t asked it to look for: the woman I was meeting might be a valuable referral partner for my beta program.

That was one of my current business priorities. Because Littlebird knew that, its recommendations connected the meeting to what I was actually trying to build. It wasn’t only helping me have a pleasant conversation. It was helping me recognize an opportunity that fit the direction of the business.

Shared context doesn’t mean an assistant knows everything or makes every decision for you. It means the work starts from a more accurate picture. When the team, AI or otherwise, understands the destination and their roles, they can contribute beyond the task in front of them. Sometimes they help you notice a possibility you hadn’t thought to ask about.

The handbook is for the boss, too

There’s another benefit I didn’t expect: maintaining the document keeps me honest.

When I review our priorities and update the direction, I have to ask whether the decisions I’m making still support the business I’m trying to build. Sometimes I realize that something I’ve been treating as important isn’t important anymore. Other times, I see that I’ve been exploring new ideas while leaving the things I already committed to unfinished.

Apparently, the boss needs the employee handbook, too.

That’s the part that’s easy to miss when we talk about AI as a way to delegate more work. Capable assistants can take work off your plate, but they don’t remove your responsibility to set direction, communicate decisions, or decide what matters now. They can’t make a shared destination clear if you haven’t decided where the business is going.

The work of leading an AI team is still leadership. The tools may be new, but the need for current information, clear responsibilities, and follow-through isn’t. An assistant can only work from what it knows, and the team is only as current as the last time you told it what changed.

I love having an AI team. They help me do work I wouldn’t have had the time or energy to do on my own. But the most useful improvement hasn’t come from adding more help. It’s come from giving the help I have a clearer picture of the business and its priorities.

I’ve had some practice at that. I just didn’t expect to be applying those lessons to employees who don’t need lunch breaks.

Curious what my AI employees actually do for me? In November, I’m hosting a live workshop series called What My AI Employees Did for Me. I’ll take you behind the scenes of how I use AI employees in my own business: what I’ve delegated, what’s worked beautifully, and what I’ve learned along the way. No theoretical promises about what AI might do someday. Just real examples from a real business, run by a very real human.