Context Engineering: Get the Right Information Into Your AI
The skill beyond prompting: deliberately deciding everything the model sees — instructions, examples, retrieved data, tools, and history — in the right amount and order. Why it matters, and how to do it well.
Prompt engineering is about the words you write. Context engineering is the bigger skill that's come to prominence in 2025–2026: deliberately deciding everything the model receives at inference — the system prompt, examples, retrieved documents, tool definitions and their results, the conversation history, and the user's request — plus in what order, how much, and what to leave out. As one influential summary put it, it's the art of filling the context window with just the right information for the next step.
This course teaches the durable principles: the context window as a finite attention budget, why 'just stuff everything in' backfires (context rot, lost-in-the-middle), how to curate high-signal context, how to manage it over long tasks with compaction and external memory, why agents make it urgent, and how to evaluate and iterate. It's grounded in primary sources (Anthropic's engineering guidance, the Lost-in-the-Middle paper, the Context Rot study) and stays honest about what's settled versus still-debated. A natural next step after prompting. Module 1 is free.
What you'll be able to do
- Explain what context engineering is and how it extends prompt engineering
- Treat the context window as a finite attention budget and avoid overstuffing it
- Curate high-signal context: instructions, examples, retrieval, tools, and history
- Manage context over long tasks with compaction, pruning, and external memory
- Engineer context for agents and multi-step systems, and evaluate it empirically
Curriculum
Module 1: What Context Engineering Is
FreeThe shift from prompting to context, why context is everything, the finite context window, and the ingredients you engineer.
Module 2: The Ingredients — Curating What Goes In
PremiumInstructions at the right altitude, examples and tools, retrieval by relevance, and the discipline of leaving things out.
- Instructions at the right altitude12 min
- Examples and tools: curate, don't dump12 min
- Retrieval: relevance over volume12 min
- The discipline of leaving things out11 min
Module 3: Managing the Window — Rot, Order & Memory
PremiumContext rot, lost-in-the-middle, cost and latency, and managing context over long tasks with compaction and external memory.
- Context rot: why longer isn't better13 min
- Lost in the middle: placement matters12 min
- The cost and latency of context10 min
- Compaction and external memory13 min
Module 4: Context for Agents & Real Systems
PremiumWhy agents make context urgent, the write/select/compress/isolate toolkit, the sub-agent debate, and evaluating empirically.
- Why agents make context engineering urgent12 min
- The four moves: write, select, compress, isolate11 min
- The sub-agent debate: isolate or unify?12 min
- Evaluate and iterate: context is empirical12 min
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