Context Engineering
The real skill isn't prompting—it's architecting what AI knows before it reasons.
Last updated: May 2025
Beyond Prompt Engineering
Most AI tutorials focus on crafting better prompts. But prompts are just one input to the AI's reasoning process. Context Engineering is the discipline of architecting the entire informational environment where understanding emerges.
“The prompt is the question. The context is the classroom.”
The Three Pillars
System Prompts
Persistent instructions that shape AI behavior across an entire session or project.
- • CLAUDE.md files - Project context and memory
- • Role definitions - Expert personas and constraints
- • Output formats - Structured response patterns
Tools & MCP
External capabilities that extend what AI can perceive and do in the world.
- • Model Context Protocol - Standardized tool integration
- • File operations - Read, write, search codebases
- • External APIs - Web, databases, services
Conversation Design
The flow of information that shapes how understanding develops over time.
- • Information sequence - What to reveal when
- • Feedback loops - Iterative refinement patterns
- • Context windows - Managing what AI remembers
Context Engineering in Practice
The CLAUDE.md Pattern
Every project I work on has a CLAUDE.md file at its root. This isn't just documentation—it's the AI's persistent memory and operating manual for that specific context.
# CLAUDE.md ## Project Context This is a Next.js 15 portfolio site... ## Critical Patterns - Always run `npm run pre-deploy` before commits - Use Radix UI for complex components - Data lives in /data/*.json, never hardcoded ## Memory Triggers - "READ FIRST, EDIT SECOND, ALWAYS" - "lint before commit - no unescaped entities"
This context shapes every interaction. The AI knows the tech stack, the conventions, the pitfalls to avoid. The context does the heavy lifting so the prompts can stay simple.
Why Context Engineering Matters
Consistency Over Cleverness
A well-engineered context produces reliable results with simple prompts. You don't need prompt wizardry when the AI already understands your world.
Compounding Knowledge
Context engineering creates reusable assets. A good CLAUDE.md file saves hours across hundreds of future interactions.
Trust Through Structure
Clear constraints and patterns build trust. When the AI knows its boundaries, you can give it more autonomy with confidence.
From Tools to Colleagues
Context engineering is the bridge from “AI as tool” to “AI as capable colleague.” It's how you onboard an AI the way you'd onboard a team member.