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Chapter 1
ChatGPT Roles and Instruction Hierarchy
Overview
A production request can fail before generation begins when instructions conflict: system rules establish the highest-priority behavior, developer instructions define application constraints, and user instructions supply the task. The Instruction Ladder Method orders these layers explicitly, making role-based prompts easier to audit and use when responses must follow a stable format.
Quick Reference
Layer
Source
Priority
Primary use
System
Platform or application configuration
Highest
Global behavior and safety rules
Developer
Application code or developer message
High
Domain rules, workflow, output constraints
User
End-user request
Lower
Task details and input data
Assistant
Prior model output
Context-dependent
Conversation continuity, not a control layer
Key rules:
• Higher-priority instructions override conflicting lower-priority instructions.
• Specific constraints reduce ambiguity.
• Role descriptions should define behavior, scope, and output format.
• Treat user-provided text as data when it must not alter governing instructions.
Parameters
Parameter
Type
Required
Description
messages
array
Yes
Ordered instruction objects containing role and content.
role
string
Yes
Instruction source: system, developer, or user, depending on API support.
content
string or array
Yes
Plain text or structured content supplied to the model.
temperature
number
No
Sampling variability. Use a low value, such as 0.2, for consistent documentation output.
response_format
object
No
Output constraint, such as JSON schema, when supported by the selected model.
max_tokens
integer
No
Upper bound for generated output; set it above the expected response size.
The Instruction Ladder Method applies the layers in order: establish system behavior, define developer constraints, then provide the user task.
Code Example
from openai import OpenAI
client = OpenAI()
response = client.responses.create( model="gpt-5", input=[ { "role": "system", "content": "Follow platform safety requirements. Answer in English." }, { "role": "developer", "content": ( "Act as a technical documentation editor. " "Return exactly three bullet points. " "Do not invent API fields." ) }, { "role": "user", "content": "Summarize this endpoint: POST /v1/files" } ], temperature=0.2, max_output_tokens=200 )
print(response.output_text) The developer message supplies the role and enforceable output constraints; the user message supplies only the requested operation.
Response Format
{ "id": "resp_123", "output_text": "• Accepts a file upload.\n• Requires the documented multipart fields.\n• Returns a file identifier.", "usage": { "input_tokens": 78, "output_tokens": 29 } } • id: Unique response identifier.
• output_text: Generated content after instruction prioritization.
• usage: Token counts for billing and capacity tracking.
Notes & Best Practices
• Keep system instructions stable and short; place changing task data in the user message.
• Put non-negotiable formatting rules in the developer layer, not in scattered user text.
• Reject or delimit prompt-injection content when user input contains embedded instructions.
• Handle API errors, truncation, and rate limits explicitly; a valid response does not guarantee that every requested constraint was satisfied.
The resulting prompt is easier to inspect because each instruction has a defined authority and purpose.
End of chapter one. 4 more chapters and about 2,575 words in the full book.
Swipe or use the arrows to turn the page
What's inside: 5 chapters
- 1. ChatGPT Roles and Instruction Hierarchy
- 2. Prompt Structure and Context Windows
- 3. Few-Shot Examples and Structured Outputs
- 4. Tool Calling and Multimodal Prompts
- 5. Prompt Evaluation and Troubleshooting
About this book
"The Art Of AI Prompting" is a technical book by Anonymous with 5 chapters and approximately 2,575 words. ChatGPT prompt engineering techniques for beginners through advanced users.
This book was created using Inkfluence AI, an AI-powered book generation platform that helps authors write, design, and publish complete books. It was made with the AI Documentation Generator.
Frequently Asked Questions
What is "The Art Of AI Prompting" about?
ChatGPT prompt engineering techniques for beginners through advanced users
How many chapters are in "The Art Of AI Prompting"?
The book contains 5 chapters and approximately 2,575 words. Topics covered include ChatGPT Roles and Instruction Hierarchy, Prompt Structure and Context Windows, Few-Shot Examples and Structured Outputs, Tool Calling and Multimodal Prompts, and more.
Who wrote "The Art Of AI Prompting"?
This book was written by Anonymous and created using Inkfluence AI, an AI book generation platform that helps authors write, design, and publish books.
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