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AI Prompt Engineering · Lesson

Modular Prompt Sections

Separating context, instructions, constraints, and output format cleanly.

The Problem with Monolithic Prompts

A monolithic prompt stuffs everything into one paragraph: background, task, rules, examples, and output format all mixed together. As prompts grow in complexity, monolithic structure causes:

  • Models misapplying rules to the wrong sections
  • Difficulty debugging which part caused a bad output
  • Impossible-to-maintain prompt strings
  • Inconsistent behavior across model versions

Modular prompts solve all of these problems.

The Five Core Prompt Sections

A well-structured prompt has five distinct sections, each with a clear purpose:

  • Context — Background the model needs to understand the situation
  • Task — What the model must do, stated clearly
  • Constraints — Rules and limits on the response
  • Output Format — Structure, length, and schema of the expected response
  • Examples — Demonstrations of correct behavior

Not every prompt needs all five. Use only what is necessary.

All lessons in this course

  1. Using XML Tags as Delimiters
  2. Modular Prompt Sections
  3. Header-Body-Footer Prompt Pattern
  4. Prompt Organization Best Practices
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