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

10Iteration, Testing, and Prompt Debugging

11Evaluation, Metrics, and Quality Control

12Safety, Ethics, and Risk Mitigation

13Tools, Functions, and Agentic Workflows

Function Calling Patterns Parameter Schema Design Tool Selection Prompts Planner–Executor Architectures Grounding via External Tools Error Handling and Retries Timeouts and Circuit Breakers Result Summarization Prompts Chaining Tool Calls Calculators, Coders, and Browsers Tool Availability Checks Permissions and Scopes Semantic Caching Strategies Observability and Logs Fallback to Tool-Free Modes

14Retrieval-Augmented Generation (RAG)

15Multimodal and Advanced Prompt Patterns

Courses/Generative AI: Prompt Engineering Basics/Tools, Functions, and Agentic Workflows

Tools, Functions, and Agentic Workflows

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Integrate function calling and tools, design planner–executor patterns, and manage errors, scopes, and observability.

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Fallback to Tool-Free Modes

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