I’ve started using AI this way in a lot of my daily work. In my day job, after diving into a problem, I give Claude the right context and iterate with it to get to a problem brief. In my freelance work, I set the parameters—the concept, style, or general functionality—then iterate with the AI.

AI product manager and builder Karo Zieminski, writing in Product with Attitude, calls this “AI-assisted craft”:

AI-assisted craft means the human sets the intention and the standard for the work, then directs how it gets made. AI gets a defined supporting role. Supporting, as in: it does not get to make the decisions. The practice applies across knowledge work and digital creation, from writing and research to coding and design.

Zieminski separates assistance from direction:

AI-assisted. The human is the primary maker. The choices, mistakes, revisions, and final form are theirs. AI is one of the tools they use.

AI-directed. The model produces the work; the human directs it. That direction must be consequential enough to shape the result. One prompt followed by a shrug is generation with supervision theatre.

Both require the human to make consequential choices. In my workflows, that happens throughout the iteration, not only when I write the first prompt.

Zieminski’s bounded-task rule makes that concrete:

“Improve this” is not a bounded task.

Give the model a job with sharp edges: do this, not that.

Research for me, BUT bring me facts, not conclusions. Challenge my assumptions, BUT do that through Socratic questions so I have to do the thinking. Explain this code block, BUT test whether I understood it. Suggest design fixes BUT don’t bleach my personality out of it. Whatever it is, leave space for my judgment.

I agree, with one small addition: setting the boundary starts the work. AI can’t answer the question at the other end for me: Would another change improve it, or is it time to stop asking?