Learn Prompt Engineering
A structured curriculum built from official OpenAI, Anthropic & Gemini documentation. 22 lessons across 3 tracks — beginner to advanced.
Beginner Track
8 lessonsStart here if you're new to AI or prompting. No prior experience needed.
- 1
What is a Prompt? Your First Step into AI
Understand what a prompt is, how AI models process them, and why the words you choose matter more than you think.
4 min read - 2
Clarity & Specificity: The #1 Prompting Skill
Learn why clarity is the single most impactful skill in prompt engineering and how to be specific in ways that dramatically improve your AI outputs.
4 min read - 3
Assigning Roles & Personas to AI Models
Learn how to use role assignment to prime AI models with domain expertise and improve the relevance, tone, and accuracy of their outputs.
4 min read - 4
Formatting Output: Control How AI Responds
Learn how to explicitly control the structure, length, and format of AI responses — so you get exactly what you need, every time.
3 min read - 5
How LLMs Work: What Every Prompter Should Know
A practical, non-technical explanation of how large language models work — and why this understanding makes you a dramatically better prompt engineer.
5 min read - 6
Giving AI the Context It Needs
AI doesn't know who you are, what you do, or what you're trying to accomplish. Learn what context to provide — and how to provide it — so you stop getting generic answers.
5 min read - 7
How to Iterate and Refine Your Prompts
One prompt rarely gets you where you want to go. The best results come from treating prompting as a conversation — refining, redirecting, and building on each response.
6 min read - 8
10 Common Prompting Mistakes (And the Fixes)
These are the patterns that produce bad AI output most of the time. Learn to spot them in your own prompts, fix them, and stop making them by default.
6 min read
Intermediate Track
8 lessonsLearn the techniques used by professionals — few-shot, CoT, XML structure.
- 1
Few-Shot Prompting: Teaching AI by Example
Learn how to use few-shot prompting to dramatically improve AI output quality by showing the model exactly what you want through examples.
5 min read - 2
XML Tags & Delimiters: Structure Your Prompts Like a Pro
Learn how to use XML tags and delimiters to clearly separate instructions from data in your prompts — a technique that dramatically reduces errors on complex tasks.
4 min read - 3
Chain of Thought Prompting: Make AI Reason Step by Step
Chain of Thought (CoT) prompting forces AI to show its reasoning before answering — dramatically improving accuracy on logic, math, analysis, and multi-step tasks.
5 min read - 4
Avoiding Hallucinations: Keep AI Grounded in Facts
Learn what causes AI hallucinations and the specific prompting techniques that dramatically reduce fabricated facts, fake citations, and confidently wrong answers.
5 min read - 5
Constrained Generation: Force Structured Output
Learn how to make AI models reliably output JSON, XML, CSV, and other structured formats — essential for integrating AI into real applications and workflows.
4 min read - 6
System Prompts: Giving AI Standing Instructions
System prompts let you set persistent rules, persona, and context that apply to every message in a conversation. Learn how to write them effectively and when they change everything.
7 min read - 7
Prompting With Long Documents and Large Context
Pasting a 50-page document and asking 'what do you think?' rarely works. Learn how to structure prompts for long-form content, extract what matters, and work around context limits.
7 min read - 8
Multimodal Prompting: Working with Images, Files, and Mixed Content
Modern AI models can see, read files, and process multiple input types at once. Learn how to structure prompts that work with images, documents, data files, and mixed content effectively.
7 min read
Advanced Track
6 lessonsPrompt chaining, evaluation frameworks, tree of thought, and expert patterns.
- 1
Prompt Chaining: Build Multi-Step AI Workflows
Learn how to break complex tasks into a sequence of focused prompts where each output feeds the next — unlocking tasks that a single prompt can't reliably handle.
5 min read - 2
Prompt Evaluation: How to Test and Improve Prompts Scientifically
Move beyond 'this looks good' — learn how to build evaluation frameworks that measure prompt performance with real metrics, A/B testing, and golden datasets.
5 min read - 3
Tree of Thought: Multi-Path Reasoning for Complex Problems
Tree of Thought prompting extends Chain of Thought by exploring multiple reasoning paths simultaneously — dramatically improving performance on complex planning, creative, and decision-making tasks.
5 min read - 4
Meta-Prompting: Using AI to Write Better Prompts
One of the most powerful techniques at the advanced level is turning AI on itself — using it to generate, critique, and optimize your prompts. Here's how meta-prompting works and when to use it.
7 min read - 5
Adversarial Prompting and Red-Teaming Your AI Systems
If you're building anything with AI — a chatbot, a workflow, an automated system — you need to know how it fails under adversarial conditions. Here's how to think about it and what to do about it.
7 min read - 6
Fine-Tuning vs Prompting: When to Use Which
Prompt engineering and fine-tuning are both tools for getting AI to behave a specific way. Understanding when each makes sense — and the real trade-offs — helps you avoid expensive mistakes.
7 min read