🧠 Prompt Engineering
Learn to communicate effectively with AI coding agents. Prompt quality was one of the most critical success factors in our experiments - good prompts led to clean, scalable code, while vague prompts caused hallucinations and wasted time.
Why Prompt Engineering Matters
A prompt is the main way you feed task-level context to AI. Since the model can’t guess what you’re thinking, it relies entirely on what you say and how you say it.
Well-crafted prompts:
- Improve accuracy and consistency
- Reduce hallucinations
- Make AI-generated code easier to validate
- Save time during reviews and rework
What You’ll Master
- Fundamentals - Core principles and practical techniques
- Advanced Methods - Three Experts, Multiple Iterations reasoning
- Shot Techniques - Zero-shot, one-shot, and few-shot prompting
- Real Examples - Templates you can use immediately
Core Principles
- Be specific - Clear action, expected output, constraints
- Provide context - File names, project structure, dependencies
- Break it down - One focused task per prompt
- Iterate - Refine prompts based on results
- Validate - Always review and test AI output
Think of each prompt like a task you’d hand to a junior developer: detailed but focused, with clear expectations.