Generative AI: Prompt Engineering Basics

Chapters

1Foundations of Generative AI

2LLM Behavior and Capabilities

3Core Principles of Prompt Engineering

4Writing Clear, Actionable Instructions

5Roles, Personas, and System Prompts

6Supplying Context and Grounding

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

8Structuring Outputs and Formats

9Reasoning and Decomposition Techniques

Outline-Then-Detail Pattern Scratchpad and Notes Fields Rationale-Lite Approaches Self-Ask and Subquestioning Hypothesis Generation Back-Solving Strategies Plan-Then-Execute Split Compare-and-Contrast Prompts Constraint Propagation Uncertainty and Confidence Cues Verification Steps First Sanity Checks and Estimation Socratic Questioning Prompts Eliminating Irrelevant Paths Chain-of-Thought Considerations

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/Reasoning and Decomposition Techniques

Reasoning and Decomposition Techniques

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Elicit better thinking with outline-first strategies, hypothesis testing, and verification-first prompting.

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Sanity Checks and Estimation

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