Module 3 of 5Lesson 1 of 1~14 min
A clear request in five elements
Most disappointing answers come from an incomplete request. This lesson gives you a simple structure for writing a clear request, then teaches you to understand why an answer misses the mark and to fix it with one well-chosen detail rather than starting over.
Lesson objective
By the end of this lesson, you will be able to write a request that specifies the task, the context, the data, the format and the success criteria, then diagnose a disappointing answer and fix it with a targeted clarification.
Topics covered
- writing a prompt
- effective prompts
- generative AI
- improving an answer
In the glossary
Where it fits
Getting a useful first result
How do you phrase a request that gives a usable result, and what do you do when the answer disappoints?
Lessons in this module
- A clear request in five elements (this lesson)
What you will learn in the course
This lesson is part of the course Choosing and using AI tools at work
- Explain how a generative AI assistant works and what it does well or badly, so you know what to ask of it.
- Identify a tool's limits (fabrications, sources, freshness, data privacy) and the precautions to take before using it.
- Write a clear request (task, context, data, format, criteria) that produces a usable first result.
- Diagnose why a response falls short and fix it with a targeted clarification.
- Select the right tool for a deliverable using a grid of criteria (deliverable, data, sources, cost, language, integration) and justify the choice.
- Choose the right way of working for a task (conversation, project, deep research, agent) and the level of control that goes with it.
- Build your toolkit by comparing at least two tools on a real task with criteria written in advance.
Related courses
- Build reliable Claude Skills for your product workAdvanced · ~2 hr 30 min
- Prompting for product managers: delegate, describe, verifyJunior · ~2 hr 45 min
- Understand what LLMs do well, and where they failAll levels · ~2 hr