Lately I spend a lot less time writing code myself. I ask an AI to implement something, check the result, and have it fix whatever bothers me. Meanwhile, I move another task forward. The time I spend with my hands on the keyboard has shrunk; the time I spend deciding what to ask for and keeping track of several streams of work has grown.
What I do is slowly starting to look like a manager's job. Just as that thought settled in, a question followed: won't AI eventually take over this managing, too?
AI hands out the work, too
Handing work to several AIs, managing order and dependencies, and pulling the results together is called orchestration.
Picture a coordinating AI that asks a research AI to gather information. It passes the findings to an implementing AI, and once the implementation is done, has yet another AI review it. If there are problems it requests fixes, and it only checks in with a human where human judgment is needed. With a setup like that, a person no longer has to make the rounds giving instructions to each AI one by one.
Some of what I do now, "that implementation's done, let me check it," "next, I'll hand off this task," could surely be delegated as well. Of course, deciding what counts as success and verifying the results would still be human work. Even so, "move to the side that uses AI, and the managing stays with humans" is far from guaranteed.
And I can't see why AI's management should stop at other AIs. If it can grasp the state of human work too, it wouldn't be strange for it to take on the team's project management.
What "how's it going?" is really for
At work, exchanges meant to check on status come up constantly. "How's it going?" "Are you stuck on anything?" "When do you think it'll be done?" The person asked stops to explain; the person asking organizes the answer and, if needed, passes it on. Someone makes slides for the weekly meeting, and a boss uses those slides to report further up.
Part of why all this is needed is that information about the work is scattered. The code is on GitHub, the discussions are in Slack, the specs are in documents, the schedule is on a calendar. And some of it lives only in someone's head.
Gathering all that up and turning it into a picture of the work as a whole is, in effect, one of the jobs a manager does. If AI could collect the necessary information and sort out how pieces of work relate, people might not have to go around asking nearly as often.
To talk about that, though, we need to separate the AI that supports an individual's work from the AI that looks across the whole organization.
The AI at hand, and the AI in the cloud
On supported Macs, Apple Intelligence's on-device model is already running. AI being built into the OS has, in other words, already begun.
What I imagine beyond that is an AI sitting right next to a person's work. Which document is open, which code is being changed, what the person is trying to do. Within what it's been permitted to see, it grasps that context and helps. If I could consult it without handing over files and explaining the background every time, the effort it takes to ask an AI for help would drop sharply.
That said, a personal Mac grasping my situation is a different thing from understanding the whole company's. Seeing the whole team takes a system that handles shared code, documents, conversations, and schedules. That part could plausibly fall to an AI in the cloud.
Say it connects one person's "waiting on an answer about the spec" with another person's "that answer needs confirmation from the customer." Suddenly the report "work is blocked" turns into "who needs to confirm what for this to move."
Not that local and cloud split the roles neatly. A device may call a cloud model, and a company may run models in its own shared environment. What matters is not just where the AI runs, but what information it can see and what it has been entrusted with. An AI that supports the individual, and an AI that surveys the organization from shared information. If the right information can flow between them, individual work and the team's progress get tied together.