Simon Willison, a developer who writes widely about working with AI tools, recently described the experience plainly: AI has multiplied how much he can produce, but not how much he can keep track of.

"I can churn out code a hundred times faster. I don't have the cognitive capacity to stay on top of 100 times the amount of code."

The claim underneath that quote is worth understanding even if you never write a line of code. When an assistant generates something for you — an essay, a plan, a spreadsheet of options, a batch of emails — the cost of producing it drops close to zero. The cost of knowing what's in it does not. You still have to read it, check it, remember it, and be responsible for it. That human review step is the new bottleneck, and it does not speed up just because the machine did.

Willison is talking about code, where this problem is sharpest. A developer who lets an agent write a hundred times more code now owns a hundred times more code to verify, and code that was never fully understood is code that breaks in ways no one can diagnose. If you are a non-developer using AI to generate large volumes of code, content, or workflows, the same arithmetic applies to you, with an extra wrinkle: you may have even less ability to audit what comes back. A developer can at least read the code the agent wrote. If you are asking an assistant to produce a workflow you don't understand end-to-end, your review capacity isn't just the bottleneck — it may be close to zero, which means you are trusting output you cannot check.

The practical implication is not "use AI less." It is that throughput is a vanity metric. The real question when using an assistant to run parts of your life or work is whether the volume of output stays inside the volume of attention you actually have. Generating ten drafts is easy; choosing between them requires you to have read ten drafts. Delegating a recurring task to an agent is easy; noticing when it quietly starts doing the wrong thing requires you to keep watching it.

This is not a product or a feature — it is an observation about how this kind of work actually feels, from someone doing it daily. Nothing here needs to be installed or adopted, and nothing about it is speculative: Willison is describing shipping work, his own current practice, not a prediction about where things are headed.

What the observation does not give you is a fix. Willison does not offer a system for expanding cognitive capacity or a rule for how much AI output one person can responsibly supervise. That limit is unresolved — arguably it is the central unresolved problem of assistant-heavy work. The honest version of the advice is closer to a warning than a technique: the speedup is real, the bottleneck moved to you, and the failure mode — signing off on work you never actually absorbed — is quiet and easy to fall into.