Prompt Engineering Best Practices: From Basics to Robust Systems
Mastering prompt engineering is essential for getting consistent, accurate, and safe responses from large language models. This guide curates the most useful resources to help you understand patterns, pitfalls, and powerful prompting strategies.
Prompt engineering is no longer just a hack—it’s a core discipline. Whether you're building agent workflows or RAG pipelines, your prompts are the interface between logic and language. Below are the best resources and projects to solidify your skills.
🔍 Core Topics Covered
- Designing effective prompts for different use cases
- Few-shot and chain-of-thought prompting
- Persona-based and system-instruction prompting
- Common mistakes and how to fix them
- Prompt formatting, safety, and evaluation
📚 Recommended Resources OpenAI – Best Practices for Prompt Engineering A concise and clear breakdown of what works and what doesn't—great for quick wins. https://help.openai.com/en/articles/6654000-best-practices-for-prompt-engineering-with-the-openai-api?utm_source=chatgpt.com
PromptingGuide.ai – Prompt Engineering Guide A deep and interactive resource covering personas, few-shot, tools, and safety. https://www.promptingguide.ai/
Lakera AI – The Ultimate Guide to Prompt Engineering (2025) A modern, production-oriented guide on how to create robust prompts at scale. https://www.lakera.ai/blog/prompt-engineering-guide?utm_source=chatgpt.com
Wikipedia – Prompt Engineering Excellent for understanding the evolution, formal strategies, and taxonomy. https://en.wikipedia.org/wiki/Prompt_engineering
🛠️ Build a Project
- Create a prompt evaluation notebook:
- Write prompts for summarization, classification, and reasoning tasks.
- Compare responses across different prompt styles (zero-shot, few-shot, CoT).
- Score accuracy, consistency, and hallucination manually.
- Optional: Add prompt logging and versioning with tools like LangSmith or LlamaIndex.
🧠 Reflect Are your prompts robust to input variation? Do small changes in wording produce large differences? Can others easily understand and reuse your prompt strategies?
My two cents: Check out this app—it’s still a work in progress but already provides a whole lot of useful information! https://promptengplayground.vercel.app/