Prompt engineering: external guides and reading list
External guides, blog posts, and primary sources worth reading on prompt engineering — from Anthropic and OpenAI's official docs to the best independent writers in the field.
Most teams discover the same prompt engineering blogs in roughly the same order — Anthropic's docs first because they're shipping Claude, then Lilian Weng for the survey, then Simon Willison because he's linked everywhere. By the time they've read those three, they're ahead of 80% of the field.
This page is the rest of the list. External writers, blogs, and official docs we actually re-read. Curated for signal: every entry below is one we'd send to a teammate who asked "where should I learn this?"
Where to start
How to use this list#
Don't try to read everything. Pick based on what you're building this week:
- Building Claude-specific features? Anthropic's docs + the engineering blog.
- Working on agents? Lilian Weng's agent post + Anthropic's "Building effective agents".
- Evaluating prompts? Hamel Husain's blog + Eugene Yan's patterns post.
- Just exploring? Simon Willison's blog + r/LocalLLaMA for daily pulse.
Official model-vendor guides#
Each frontier model vendor maintains a prompt engineering guide. They're indispensable when working with that specific model — see our companion guides: ChatGPT, Claude, Gemini.
- Anthropic Prompt EngineeringAnthropic
The official Claude prompt engineering guide. Particularly strong on XML tags, prefilling, and the Claude-specific patterns. Required reading if Claude is in your stack.
Official guidance from OpenAI. Covers structure, role messages, function calling, and structured outputs. The companion to the API docs.
Official Gemini prompting documentation. Strongest on long-context and multimodal patterns — the things Gemini does best.
- DAIR.AI Prompting GuideDAIR.AI
The most comprehensive open prompt engineering guide. Heavy on academic techniques — strong reference for the research side of the field.
Foundational long reads#
Posts so good they're effectively textbooks. Bookmark and revisit.
- Prompt Engineering Guide (Lilian Weng)Lilian Weng
A deeply researched survey of prompt engineering techniques with citations to primary papers. Best single resource for understanding why each technique works.
- LLM Powered Autonomous Agents (Lilian Weng)Lilian Weng
A definitive primer on LLM agents — planning, memory, tool use, reflection. The companion to anything you read about ReAct or autonomous agents.
Practitioner-grade patterns for building production LLM systems. Reads like a senior engineer's field notes — highly applicable.
- Building LLMs for Production (Hamel Husain)Hamel Husain
Honest, opinionated takes on shipping LLM applications. Particularly strong on evaluation, fine-tuning trade-offs, and unglamorous reliability work.
Practitioner blogs to follow#
Independent engineers and researchers writing useful posts at a regular cadence.
- Simon Willison's WeblogSimon Willison
The most useful daily LLM blog. Simon ships, breaks, and writes about it. Strong on prompt injection, tool use, and the practical limits of current models.
- Sebastian Raschka — Ahead of AISebastian Raschka
Research distillation with a teacher's clarity. Best for understanding the underlying ML concepts — RLHF, attention, fine-tuning — at a working level.
- Chip Huyen — Designing ML SystemsChip Huyen
Production ML and LLM systems. Particularly strong on the operational side: monitoring, evaluation, cost, latency.
- Andrej Karpathy — Talks and PostsAndrej Karpathy
The clearest explainer in the field. The "Let's build GPT from scratch" video is the single best 90 minutes you can spend on understanding what LLMs actually do.
Engineering blogs from labs#
The labs that build the models also publish engineering posts. Often the most authoritative source on what each model is capable of.
- Anthropic Engineering BlogAnthropic
Engineering posts on Claude, agent design, evaluation, and safety. "Building effective agents" is essential reading for anyone designing production agents.
- OpenAI CookbookOpenAI
Worked examples for OpenAI APIs — function calling, embeddings, fine-tuning, structured outputs. More useful than the docs in many cases.
- LangChain BlogLangChain
Practical write-ups on building chains and agents. Vendor-tilted but full of useful patterns even if you don't use LangChain itself.
Communities and forums#
Where to keep a finger on the pulse of the field. Faster than blogs; noisier.
- r/LocalLLaMAReddit
The active community for open-source LLM work. New model releases, fine-tuning tips, prompt engineering — a real-time pulse of where the open ecosystem is going.
Where new tools, papers, and product launches surface first. Comments are often more informative than the linked piece.
- AI Engineer Summit talksAI Engineer
Talks from practitioners shipping production LLM products. Higher-signal than most AI YouTube — engineers explaining what they actually built.
Quick reference#
The 60-second summary
Five categories: official vendor docs, foundational long reads, practitioner blogs, company engineering blogs, communities.
Read three to start: Anthropic's docs, Lilian Weng's survey, Simon Willison's blog.
The discipline: consistent input beats occasional binges. Follow 3-5 practitioner writers; check in weekly.
Pick by what you're building, not by completeness. Read what advances the work in front of you.
What to read next on PromptShip#
Coming back to our own guides, the highest-leverage pieces if you're shipping LLM features: few-shot, Chain-of-Thought, RAG, prompt injection. For papers behind the techniques, papers. For tools, tools.
Put this guide to work
Save your prompts, version every change, and share them with your team — free for up to 200 prompts.