Learn the core principles and proven patterns of prompt engineering for large language models. Discover how few-shot, chain-of-thought, and RAG techniques improve AI output accuracy - and avoid common pitfalls that lead to vague or wrong answers.
Few-shot prompting improves LLM accuracy by 15-40% using just 2-8 examples. Learn the top patterns that work, where to apply them, and how to avoid common mistakes.