Generative AI: Prompt Engineering Basics

Chapters

1Foundations of Generative AI

2LLM Behavior and Capabilities

3Core Principles of Prompt Engineering

4Writing Clear, Actionable Instructions

Choose Strong Action Verbs Define Scope and Boundaries State Acceptance Criteria Include Constraints and Limits Numbered Steps and Checklists Avoid Ambiguity and Vague Terms Use Negative Prompts Sparingly Disclose Time and Context Domain Vocabulary and Glossaries Reference Styles and Citations Multi-Task Prompt Patterns Question Framing Techniques Brevity vs Completeness Hints and Nudge Strategies Avoid Leading the Model

5Roles, Personas, and System Prompts

6Supplying Context and Grounding

7Examples: Zero-, One-, and Few-Shot

8Structuring Outputs and Formats

9Reasoning and Decomposition Techniques

10Iteration, Testing, and Prompt Debugging

11Evaluation, Metrics, and Quality Control

12Safety, Ethics, and Risk Mitigation

13Tools, Functions, and Agentic Workflows

14Retrieval-Augmented Generation (RAG)

15Multimodal and Advanced Prompt Patterns

Courses/Generative AI: Prompt Engineering Basics/Writing Clear, Actionable Instructions

Writing Clear, Actionable Instructions

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Craft precise directives with scope, constraints, and acceptance criteria that remove ambiguity and reduce rework.

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Multi-Task Prompt Patterns

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