How to stop context switching when you work with AI

AI makes it so easy to start ten different projects that you can finish none of them. By the end of the day you worked a lot and still do not feel you got what you needed to get done. Tomi, founder of SupaKid Studios, says a lot of that feeling is context switching.

Here is how he cuts it down.

Why it happens

You open one agent for a bug, another for a landing page, a third for a customer reply. Each one needs you to remember where it left off, check what it did and answer its questions. That is a lot of small switches, and each costs focus.

Current models can run their own swarms of workers. So you do not have to talk to all of them. You can talk to one.

The routine

Tomi's daily loop has four parts.

1. Set weekly priorities with your chief of staff agent. Know the three things that matter this week.
2. Spend about 30 minutes each morning choosing what needs you today. That could be a decision, a review or one specific task. Everything else belongs to someone else.
3. Let managers own their projects. A project manager keeps the task board and its agent team moving. You mostly talk to the chief of staff instead of bouncing between agents.
4. One chat per specific task. For a bug fix or App Store materials, open a fresh chat. When it finishes, review the result, have your chief of staff update your task tracker, then archive the task chat. Keep the chief of staff as your ongoing conversation.

Details on setting up the structure are in the AI chief of staff guide.

The rule: inputs and outputs only

Your job is to define the input and review the output. Keep each cycle fast and small. If the result is not what you expected, improve your instructions. Do not jump into the middle and start steering every step. That is where the switching comes from.

Cut the tool searching too

Part of context switching is tool switching: always looking for a new model or app. Tomi's view is that most people do not have a tool problem. Pick a setup that matches your work (see which AI setup you need) and stay with it for a month before you change anything.

How we do it at SupaKid Studios

Tomi runs several businesses and client projects. He described a setup where a personal agent sits on top, with product managers per project and engineering managers under them, each waking on a 30 minute interval to check a task board. He mostly talks to the personal agent and it delegates down. That means that at the end of the day he can look at what was decided and shipped, instead of reconstructing which of twenty chats did what.

It is also how he handles work for clients. We run AI-driven engineering and operations with a clear owner on each lane, and clients approve what goes out.

If your job is a regular computer job and not a business, the same idea applies at smaller scale. See how to automate your job with AI.

What goes wrong

• Too many open chats. Archive finished ones.
• You become the router. If you paste messages between agents, you are the bottleneck. Let the manager do it.
• No weekly priorities. Without them, the loudest task wins.
• Reviewing everything. Review what needs your judgment. Let managers handle the rest.
• Starting new projects when stuck. AI makes starting free. Finish one first.

Try it for a week

1. Pick your top three priorities for the week.
2. Each morning, write down what needs you today, in 30 minutes or less.
3. Use one chat per task and archive each when it is done.
4. At the end of the day, ask your chief of staff what shipped and what is blocked.

If you want help setting this up, SupaKid Studios offers coaching for founders who work with AI agents. A 30-minute call is enough to find where your day leaks focus.