brexhq/prompt-engineering resource

Health v2 · maintenance only

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Adoption not part of the score

9585 stars · 514 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Brex's prompt engineering guide, a documentation-style resource covering strategies, guidelines, and safety recommendations for building systems on large language models like GPT-4. It explains LLM fundamentals, prompt hacking, data embedding formats, chain of thought, and fine-tuning based on production lessons.

Use cases

• learn prompt engineering for llms
• write better gpt-4 prompts
• understand prompt injection and jailbreaks
• structure data in llm prompts
• apply chain of thought prompting
• decide between prompting and fine-tuning
• build production llm applications safely

When to choose

• you are new to prompting LLMs and want a practical, production-oriented guide
• you need strategies for embedding data and getting structured output from models
• you want to understand prompt hacking, jailbreaks, and safety recommendations

When to avoid

• you need runnable code or a library rather than prose guidance
• you need up-to-date coverage of the newest models, since the guide last saw a release in 2023
• you want an interactive course or tutorials with exercises

Facets

learning-resource · maturity maintenance

prompt-engineering llm-inference rag documentation large-language-models artificial-intelligence tutorials cross-platform llm-guide gpt-4 prompting-strategies chain-of-thought llm-safety best-practices natural-language-processing

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