Advanced Prompt Engineering Techniques
Master advanced prompt engineering — structured output, prompt chaining, RAG, tool use, and evaluation. Bite-sized lessons for practical AI skills.
Structured Output: Get JSON and More from LLMs
Learn how to get AI models to return structured output in JSON, XML, and tables. Practical prompting techniques for reliable, parseable LLM responses.
3 min readPrompt Templates: Build Reusable AI Prompts
Learn to build prompt templates with variables that scale across inputs and teams. Master reusable, parameterized prompts for consistent AI results.
3 min readPrompt Chaining: Break Complex Tasks into Steps
Learn prompt chaining — the technique of splitting complex AI tasks into sequential prompts. Includes patterns, examples, and tips for reliable results.
4 min readLong Context Prompting: Tips That Improve Results
Learn practical long context prompting strategies — from document placement to the 'lost in the middle' fix — so your AI responses stay accurate at scale.
4 min readRAG Explained: What It Is and When You Need It
Learn what retrieval-augmented generation (RAG) is, how it works, and when to choose it over fine-tuning or long context — in a quick, beginner-friendly lesson.
4 min readAI Function Calling & Tool Use Explained
Learn how AI models call external functions and APIs through tool use. Understand how function calling works and how to write prompts that guide it.
4 min readHow to Evaluate Prompts: Metrics & Methods
Learn systematic methods for evaluating prompt quality, from scoring rubrics to LLM-as-a-judge. Move beyond guesswork and measure what works.
4 min read