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Prompt Engineering

Prompt engineering — what works, what doesn't, and why.

Why learn Prompt Engineering?

  • Better prompts often beat bigger models.

  • A short, learnable craft with high leverage.

  • Critical for cost, latency, and accuracy in any LLM product.

  • Pairs with evals — measure, don't guess.

What you can build with Prompt Engineering

Tuning chatbots and copilots Improving classification and extraction Reducing hallucinations Designing agentic prompts and tools

Prompt Engineering tutorials

2 articles

Hand-written tutorials, ordered as a recommended learning path.

  1. 01 Prompt Engineering Basics A practical guide to prompting LLMs — system vs user prompts, clarity over cleverness, few-shot examples, structured JSON output, chain-of-thought, and eval-driven iteration.
  2. 02 Templates & Patterns How to turn prompts into reusable templates: variables, system messages as contracts, few-shot structure, JSON output schemas, role prompting, and when patterns help versus hurt.