Module 2 of 4Lesson 3 of 5~15 min
Describing the task in a structured prompt
A structured prompt gets you a usable deliverable on the first try, where a vague request produces generic text you end up rewriting. You learn to phrase a request to AI as a real work brief, cutting down the back-and-forth and getting a result you can stand behind in front of your team.
Lesson objective
By the end of this lesson, you will be able to write a prompt that describes the expected deliverable, process and quality bar, in separate blocks (role, context, task, data, format, criteria), and explain what each block contributes.
Topics covered
- structured prompt
- prompt structure
- writing a prompt
- prompt engineering
- AI brief
Where it fits
Delegate, describe, verify
How do you get a reliable result from generative AI, and know when not to trust it?
Lessons in this module
- Choosing what to hand over to AI
- Understanding what an LLM does when you prompt it
- Describing the task in a structured prompt (this lesson)
- Four techniques that change the result
- Checking and iterating with discernment
What you will learn in the course
This lesson is part of the course Prompting for Product Managers: delegate, describe, verify
- Decide, for a task in your product cycle, whether to hand it to AI, in which mode (automation, augmentation, agent), and what you keep.
- Explain how an LLM behaves (prediction, dated knowledge, working memory, instruction following) to anticipate its mistakes and pick the right fix.
- Write a prompt that describes the deliverable, the process and the quality bar, with context, delimited data and examples when needed.
- Evaluate an AI output (content, process, behavior) against explicit criteria, then improve it through targeted iterations.
- Produce PM deliverables with AI (feedback synthesis, persona, interview guide, user stories) from real data, and check that they are faithful to it.
- Configure standing instructions and a dedicated assistant for a recurring task, test it on real cases, and decide when to move to an agent.
- Apply diligence rules (shared data, transparency, accountability) before using or circulating work produced with AI.
Related courses
- Build reliable Claude Skills for your product workAdvanced · ~2 hr 30 min
- Choosing and using AI tools at workAll levels · ~1 hr 40 min
- Understand what LLMs do well, and where they failAll levels · ~2 hr