Most teams use AI in silos — quietly, individually, with an unspoken awkwardness about what's AI-generated. The result: faster output with hidden fragility.
The first shift was making AI official: a versioned context file, shared across the team, updated with every feature. AI stopped being stateless. Early results showed 40–50% fewer prompt iterations.
But shared context kept failing when engineers weren't clear on the problem before prompting. AI output quality tracks directly to problem clarity — and that was the missing piece. So we built IDEA: Intent, Diagnose, Explain, Architect — a mental model for thinking before prompting.
We'll demo IDEA live, show a real context file, and share what broke along the way. You'll leave with the IDEA framework, a context file template, and a prompt quality checklist.