FOMAT: The Fear of Leaving Your AI Agents Idle
AI & Machine Learning

FOMAT: The Fear of Leaving Your AI Agents Idle

FOMAT means Fear of Missing Agent Time: the pressure to keep coding agents working while you step away. More runtime does not always mean more progress.

By Daniel Mercer • 4 mins read Published: Updated:

Key Notes

  • FOMAT stands for Fear of Missing Agent Time and describes the pressure to keep AI agents busy while their users are away from work.
  • Michael Richman used the term in an April 2026 conference talk, while developer accounts illustrate how supervising several agents can become exhausting.
  • More agent runtime does not automatically mean useful progress because tasks still need clear goals, decisions and review.

You close the laptop, go for a walk and remember another task your coding agent could be doing. Or you get ready for bed and wonder whether you should queue one more job first. FOMAT, short for Fear of Missing Agent Time, gives that feeling a name: the worry that you are wasting an opportunity whenever the machines are idle.

Michael Richman used the term in an AI Engineer Europe conference talk dated April 10, 2026. His examples included thinking of work for an agent while away from the development machine, and returning to discover that an apparently busy agent had stopped almost immediately to ask a question. The phrase adapts FOMO, or fear of missing out, to software that can keep working after its user leaves.

It is an informal label for a developer experience, rather than a clinical diagnosis or a measured trend across the workforce. But it neatly captures a change in the relationship between work and downtime. When a tool can act without you, taking a break can start to feel like failing to keep a small workforce occupied.

The Agent May Be Waiting for You

Richman described the practical problem in a February 22 blog post introducing Cmd+Ctrl. A developer leaves expecting progress, then returns an hour later to find that the agent needed an answer after five minutes. Adding more parallel sessions creates more questions, corrections and windows to track. The automation keeps producing work, but supervision becomes a job of its own.

That distinction matters. An agent with no assigned task is idle; one awaiting a decision is blocked. Both can look like lost time from a distance, yet they call for different responses. The first needs a worthwhile task. The second needs a decision that may require someone to understand the project, inspect a result or choose between competing goals.

Richman’s proposed answer is remote orchestration. Cmd+Ctrl is designed to show session status and let users respond from a phone or browser, with notifications when an agent finishes or needs input. That is the maker’s description of the product, rather than an independent test of its productivity benefits. It addresses the inconvenience of being tied to a terminal, while leaving a bigger question open: when should the human be available?

More Runtime Is Not the Same as More Progress

Developer Simon Willison has described the human cost of managing several agents at once. In his April 2 podcast notes, he said running four in parallel could leave him mentally exhausted by late morning. He also recounted conversations with people who stayed up to assign another batch of tasks and woke early to check on them. Those are personal observations, rather than a survey establishing how common the behavior is.

The pressure has an appealing logic: if agents can write code while you sleep, an unused night looks like forgone output. But generated output still has to fit the project. Consider three agents proposing different changes to the same feature. Each can finish its assignment, yet someone must decide which approach to keep, check how the pieces interact and establish whether the result actually helps users.

At organizational scale, faster generation can move the bottleneck elsewhere. Anthropic says the volume of agent-written code helped drive its development of Scion, a source-control system designed around its internal workload. That is a different problem from an individual developer checking a laptop at bedtime, but both show why agent activity alone is an incomplete measure of progress.

A useful way to assess an agent session is to ask what will count as finished before starting it. A bounded bug fix, a reproducible test or a draft ready for review has an outcome someone can assess. Keeping a session running simply to avoid an empty queue supplies an activity metric without establishing a benefit.

FOMAT makes the tension memorable. Tools that report completed and blocked work can reduce the need to keep checking, but a phone notification can also carry work into every break. The practical goal is a workflow that produces useful results within the time available to direct and review them. An agent waiting until tomorrow does not, by itself, mean today was wasted.

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