The Complete Guide · 7 chapters
Context Engineering: The Complete Guide
A prompt is one message; context is everything the model can see when it reads that message. Context engineering is how you control that environment so an agent behaves reliably across hundreds of runs — not just once. This guide starts with what context engineering is, then works through the practice one chapter at a time: how it differs from prompting, what to put in an agent's context window, the practices that hold up in production, the tooling, and the wider system an agent runs inside. Read it start to finish, or jump to the part you need.
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01
What Is Context Engineering?
Context engineering is the practice of giving AI agents the right information to act well. Here's what it means, why it matters, and how it works in practice.
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02
Context Engineering for AI Agents: A Practical Guide
Context engineering determines what your AI agent knows at every step. Here's how to structure, retrieve, and manage context so agents work in production.
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03
Context Engineering Best Practices for AI Agents
Stop getting bad AI outputs. A practical guide to context engineering best practices — with a checklist marketers can apply to agents and automations today.
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Free tool · from Letaido
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Take our quick quiz on agents, prompting methods, and AI fundamentals — get your score, see how you compare, and jump to the guide behind every answer.
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04
Context Engineering Tools: What Actually Works in 2026
A practical breakdown of context engineering tools by use case — retrieval, memory, prompt pipelines, and agent workspaces. Pick the right fit for your stack.
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05
Loop Engineering: How to Design an AI Agent That Doesn't Go Off the Rails
Loop engineering is the practice of designing an AI agent's act-observe-iterate cycle. Here's what good loops look like — and what causes them to break.
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06
Harness Engineering: The Scaffolding That Makes AI Agents Safe to Run
Harness engineering designs the tools, constraints, memory, and feedback loops an AI agent operates within. Here's what each layer does and how to build it.
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07
Agentic Engineering: Building Systems That Act
Agentic engineering is the discipline of building AI systems that pursue goals, not just answer questions. Here's what it means and why it matters.
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