The Product Context Gap
AI coding assistants like Cursor, Claude Code, and GitHub Copilot are brilliant at how to build things. They know programming languages, frameworks, and code patterns. But they have no idea about your business.
| What AI Knows | What AI Needs to Know |
|---|---|
| Programming languages | Your ICP and customer segments |
| Frameworks and libraries | Past architectural decisions |
| Code syntax and patterns | Why features were rejected |
| Documentation (if you paste it) | Team velocity and capacity |
| Current file contents | What's already built elsewhere |
This gap is why AI coding assistants often suggest features that already exist, miss critical business requirements, or build things that don't serve your strategy.
Code Context vs. Product Context
Code context is what the code does: function signatures, file contents, syntax, dependencies.
Product context is why the code exists: business requirements, customer needs, strategic alignment, decision rationale.
Both are essential. Code context helps AI write correct code. Product context helps AI write the right code.
See the Difference
Without Product Context
You: "Add a feature for team collaboration"
AI: "I'll add real-time collaborative editing, presence indicators, and a commenting system..."
With Product Context (via Brief)
You: "Add a feature for team collaboration"
AI: "I see we decided against real-time collaboration in Decision #42 because it's not core to our solo-founder ICP. Our personas are primarily individual users. Did you want to revisit that decision, or focus on async collaboration instead?"