Here is the failure this fixes, and you have almost certainly built it by accident.
You have a multi-step task. Research something, turn it into a draft, review the draft, produce the final thing. So you do it in a conversation: ask, read, ask again, paste, correct, ask again. It works. It takes an hour, it works, and by message twelve the model is contradicting a decision it made in message three, you cannot tell which message introduced the error, and next week, when you need the same output for a different input, you do the whole hour again from scratch.
Chaining prompts by hand is the intuitive fix and it only solves half of it. You still have four requests where the second one's input is "whatever the first one said", which is not a specification, and nothing between them that you could inspect even if you wanted to.
The alternative is to design the thing rather than perform it.
Chaining prompts is a habit. Naming each one's role, inputs, outputs and handoff is a system, and only the second one can be rerun, inspected or repaired.
Treat each prompt as a specialised agent. It has one job, a defined input, a defined output format, and a handoff to whatever comes next. This is the architecture behind production AI systems: content pipelines, research assistants, automated code review, document generation workflows. It is not more prompting. It is design.
Why specialisation beats one clever prompt
The instinct is to write one very good prompt that does everything. It reliably loses to four narrow ones, and the reason is boring: an agent asked to extract concepts and write questions and format output does all three at medium quality, because its attention is genuinely divided and its output has to serve three purposes at once. A Content Analyst that only extracts, handing to a Question Designer that only writes questions, produces better work at both steps and leaves you something readable in between.
The cost is honest. This takes upfront design time, an hour perhaps, and it is overkill for anything you do once. What you get for that hour is a pipeline you run on demand, for years, on inputs you have not thought of yet.