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Chapter 12: Context Engineering for AI-Driven Development

Context windows are the "working memory" of AI development tools. Just as engineers optimize RAM allocation in systems, AI-native developers engineer context windows for AI tools. Context engineering is the foundation of productive AI collaboration.

This chapter teaches you to engineer context windows using hands-on discovery pedagogy. You'll master manual observation, AI collaboration, compression techniques, persistent memory, and tool selection through progressive experiments that build deep understanding. You'll experience context degradation, pollution, and recovery firsthand before learning systematic frameworks.

Chapter 12 taught you what to SAY to your AI agent. This chapter teaches you what your AI agent KNOWS when you say it—and how to manage that knowledge effectively across sessions and projects.

🎯 Before You Begin​

What You'll Learn​

By completing this chapter, you will:

  • Manually observe and track context window utilization — Identify degradation symptoms (repetitive suggestions, forgotten patterns, performance drops) during AI sessions without AI assistance
  • Apply progressive loading strategies — Use Foundation → Current → On-Demand phase loading to manage large codebases, maintaining context utilization under 70% through AI collaboration
  • Execute context compression and isolation strategies — Create checkpoint summaries and restart sessions to reclaim context space, use separate sessions for unrelated tasks to prevent pattern cross-contamination, apply clear decision frameworks
  • Design memory file architecture — Create CLAUDE.md, architecture.md, and decisions.md files that enable persistent intelligence across multi-session projects
  • Select appropriate AI tools — Choose between Claude Code (200K context, deep reasoning) and Gemini CLI (2M context, exploration) based on context requirements, reasoning depth needs, and task complexity
  • Write context-aware specifications — Create complete, implementation-ready specifications for context-aware development tools that orchestrate all accumulated patterns (capstone: specification-only, NO implementation code)