The first time you use an AI assistant for a task, a long chat can feel productive. You explain the project, paste the constraints, correct a few assumptions, and eventually get a usable draft. The second time, much of that context has to be recreated. A different chat, model, teammate, or reviewer may not know what was decided last time. The work starts to feel less like delegation and more like repeatedly reconstructing a shared memory.
That cost is not only typing time. When the brief lives only in a conversation, it becomes easy to lose a boundary, accept an unsupported detail, or call something finished because it reads well rather than because it meets the actual request.
The problem appears in public technical conversations too. One Hacker News commenter put the prompt problem plainly: “a bad prompt can create an output which is meaningless.”
Source: https://news.ycombinator.com/item?id=49395273
Another described the downstream constraint: “Review, CI, and branch workflows were calibrated to human writing speed. The gates did not get faster.”
