Multi-Project

Context Switching Between Too Many AI Projects Kills Your Day

Waiting on one agent, you peek at another project, then a third. Why context switching costs more with AI agents, and a simple rule to keep switches cheap.

By Tu Nguyen · · 2 min read.md

A developer glances anxiously between two monitors full of code from different projects.

The agent is running a long task on project A. Two minutes to wait. You open project B “just to check”. B needs a small fix, so you start it. Then A finishes, but you’re mid-thought in B. Then a notification from C.

By lunch you’ve touched five projects and moved none. This is part 2 of Busy, Not Shipping — after busy all day, nothing shipped — about the switch that looks free and isn’t.

Agents create gaps, gaps invite switches

Working alone, you rarely wait on yourself. Working with agents, you wait all the time — for a build, a test run, a long refactor. Those gaps feel like wasted time, so you fill them with another project.

The switch itself takes a second. Coming back is what costs: re-reading where you were, what the agent changed, what you were about to decide. Do that twenty times a day and the gaps you were “saving” cost more than they saved.

Make switches cheap instead of rare

You won’t stop switching — with agents, some switching is the point. The goal is to make each one cheap.

A switch is cheap when you can reload a project in seconds. That needs three things written down, per project:

  1. Where it is — the phase.
  2. What’s next — one action.
  3. Where the conversation is — the session to resume.

If you can see those three things for every project on one screen, coming back is a glance, not an archaeology dig. That’s the core of running many projects in parallel.

Only switch to projects with a written next step

A simple rule that prevents most bad switches:

While an agent runs, only switch to a project whose next step is already written down.

If B’s next step is “write 3 screenshot captions”, you can do it in the gap and come back. If B’s next step is “figure out what’s going on”, don’t open it now — it will swallow the afternoon.

The same rule makes session handoffs easy: the written next step is exactly what you’d stop re-explaining to the agent.

Three active, the rest parked

Decide each morning which three projects are active today. The others are not forgotten — they’re parked, visible, with their next step written. When an active project is waiting on an agent, switch to another active project, not a parked one.

At the end of the day, write the next step for each active project before closing. Tomorrow’s switches start cheap.

Where ShotMatic fits

ShotMatic shows every project on one screen as one line — phase, next step, stuck or not — with ✦ to resume the exact Claude session for that task. Coming back to a project is reading one line and clicking once.

FAQ

How many side projects can I work on at once with AI agents?

Many can be open, but only a few should be active on the same day. Three active projects with cheap switches beats ten with expensive ones.

What makes context switching expensive?

Reloading the project into your head: where it was, what the agent was doing, what you decided. If that lives only in memory, every switch means re-reading chats and diffs.

What should I do while an agent is running?

Review the previous result, write the next step down, or switch to a project whose next step is already written. Avoid opening a project you'd have to rediscover.