Context Engineering for AI
Go beyond basic prompting. Learn to design the entire information environment your AI works with — context windows, memory systems, RAG, and agent architectures.
You’ve been writing prompts. Maybe even good ones. But if you’ve ever watched the same AI that nailed one task completely botch another — even with a similar prompt — you’ve hit the wall that prompt engineering alone can’t fix.
The problem isn’t your prompt. It’s everything around it.
Context engineering is the discipline that picks up where prompt engineering leaves off. Instead of just crafting the perfect instruction, you’re designing the entire information environment your AI operates in: what it knows, what it remembers, what tools it can reach, and how all of that is structured.
Andrej Karpathy put it this way — think of the LLM as a CPU, the context window as RAM, and your job as the operating system. You’re not just writing commands. You’re managing memory.
This course teaches you to think like a context engineer. By the end, you’ll be able to:
- Diagnose why your AI outputs are inconsistent and trace it back to context problems
- Apply the four core techniques — write, select, compress, and isolate — to any AI task
- Structure your context using XML tags, system prompts, and few-shot examples that actually work
- Design memory systems for conversations that span multiple sessions
- Build context configurations for AI agents, coding assistants, and business workflows
What You'll Learn
- Explain the difference between prompt engineering and context engineering
- Apply the four core context techniques — write, select, compress, and isolate — to real tasks
- Design structured context using XML tags, system prompts, and few-shot examples
- Implement memory management strategies for multi-turn AI interactions
- Evaluate context window utilization and optimize for cost and quality
- Build a complete context engineering system for a real-world use case
After This Course, You Can
What You'll Build
Course Syllabus
Who Is This For?
- AI tool users who want to level up from prompt craftsman to systems thinker
- Developers, product managers, and business analysts who work with AI regularly
- Professionals who want more reliable, consistent AI results
Frequently Asked Questions
Do I need to know prompt engineering first?
Basic experience with AI chatbots helps, but you don't need formal prompt engineering training. If you've used ChatGPT, Claude, or Gemini a few times, you're ready.
Which AI tools does this course cover?
The techniques work with any LLM — Claude, ChatGPT, Gemini, Copilot, open-source models, and more. We use examples from multiple platforms.
How long does the course take to complete?
About 2 hours of reading and exercises. Each lesson is 10-15 minutes. You can complete it in one sitting or spread it across several days.
Is there a certificate?
Yes. Complete all 8 lessons and pass the quizzes to earn a verifiable Context Engineering certificate with a unique credential ID.
