Lilly Tech Systems
Learn Prompt Engineering
Master the art and science of writing effective prompts for AI models. From zero-shot basics to advanced techniques like Chain of Thought and meta-prompting — all for free.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What is prompt engineering? Why it matters, how LLMs interpret prompts, and career opportunities in this field.
2. Fundamentals
Prompt anatomy, clarity, role assignment, output constraints, and the CRISP framework for structured prompts.
3. Techniques
Zero-shot, few-shot, Chain of Thought, Tree of Thought, ReAct, prompt chaining, and more.
4. Advanced Patterns
Meta-prompting, structured output, prompt templates, multi-modal prompting, and compression techniques.
5. System Prompts
Write effective system prompts, design personas, set behavioral constraints, and build safety guardrails.
6. Domain-Specific Prompts
Specialized prompts for coding, writing, data analysis, research, and education domains.
7. Testing & Iteration
Evaluate prompt quality, A/B testing, red teaming, prompt versioning, and iterative refinement.
8. Best Practices
Top 20 tips, common mistakes, model-specific advice, prompt security, and cost optimization.
What You'll Learn
By the end of this course, you'll be able to:
Write Effective Prompts
Craft prompts that consistently produce high-quality, accurate results from any AI model.
Apply Advanced Techniques
Use Chain of Thought, few-shot learning, ReAct, and other proven prompting strategies.
Design System Prompts
Build robust system prompts for chatbots, assistants, and automated workflows.
Test & Optimize
Evaluate, iterate, and refine your prompts using systematic testing methodologies.