AI Teammates Need a Chief of Staff
Give a team ten brilliant individual contributors and no coordination, and you get ten people building ten slightly different things. The same is true for AI agents. Capability isn't the bottleneck anymore. Coordination is.
The agent coordination problem
As soon as you have more than one agent — or one agent working across more than one thread — you inherit every problem a human team has:
- Who owns what?
- What's blocked on what?
- Which decision already got made?
- What context does the next step need?
Left unmanaged, agents interrupt each other, duplicate work, and lose the thread exactly like an under-managed team does.
Enter the Chief of Staff
In an organization, a chief of staff doesn't do the work — they make the work flow. They hold the map, protect the priorities, chase the loose threads, and keep everyone pointed at the same outcome.
An AI Chief of Staff plays the same role for a system of agents:
- Holds the map — the live model of goals, tasks, and dependencies.
- Routes the work — decides what happens next and who (or which agent) does it.
- Carries the context — hands each step exactly what it needs to succeed.
- Closes the loop — verifies outcomes and feeds them back into memory.
Why this is the unlock
Once coordination is a first-class role rather than an afterthought, adding capability actually helps. More agents make the team faster instead of noisier.
This is the throughline of everything I'm researching: delivery becomes fluent when something is genuinely responsible for the flow — not just the tasks.