Practical Prompting · Intermediate

Lesson 4: The Anatomy of a Great Prompt

Five components that turn a vague request into a specification the model can actually satisfy.

By the AIVraj Editorial Team 8 min readLast updated July 22, 2026
What you will learn
  • Write prompts using the role-context-task-constraint-format pattern
  • Know which component to add when output disappoints
  • Build reusable prompt templates
In this lesson
  1. The five components
  2. A worked upgrade
  3. Which component to add
  4. Templates beat inspiration
  5. Practice

The five components

Nearly every strong prompt contains the same five parts, in this order:

A worked upgrade

Weak: "Write about our new pricing."

Strong: "You are a SaaS product marketer. We are moving from three plans to two and raising the entry price from $9 to $12 for new customers only; existing customers keep their price for twelve months. Write the in-app announcement for existing customers. Constraints: under 120 words, reassuring but not apologetic, no marketing adjectives, lead with the fact that their price is unchanged. Format: one short paragraph, then three bullets, then a one-line link CTA."

The second prompt is longer to write and roughly ten times more likely to produce something publishable, because every decision the model would otherwise guess at has been made by the person who actually knows the answer.

Which component to add

Diagnose by symptom:

SymptomMissing component
Correct but genericContext
Right content, wrong shapeFormat
Too long, too floweryConstraints
Shallow or naive treatmentRole
Answers several things badlyTask (split it)

Templates beat inspiration

Once a prompt works, save it with placeholders and reuse it. That is precisely what the tools on this platform are: a stored system prompt, a role, a quality bar and an output format, with a form for the two or three variables that actually change. The Prompt Library applies the same idea to free-form chat.

Practice

Take your last disappointing AI result. Add exactly one missing component from the table above and rerun. Repeat. You will usually find that two additions — context and format — account for most of the gap.

Practise with these tools

Frequently asked questions

Do longer prompts always work better?

No — denser prompts do. Extra words that add no constraint or context simply consume context window. Every sentence should remove a decision the model would otherwise guess.

Should I use role prompting with reasoning models?

Role still helps set vocabulary and depth, but reasoning models depend far more on a clearly specified task and success criteria than on persona framing.

Next lesson
Lesson 5: Iteration Patterns — Getting from Draft Three to Done
Continue
More reading: Learning Center · AI Glossary