Is your team's AI producing code, or producing product?
Many teams accelerated code generation without moving product metrics. The diagnostic separates internal efficiency from real user impact.
How far has your team really gone with AI?This diagnostic gives you the honest answer.
Fewer than 5% of Engineering teams use AI structurally.
Not a generic quiz. 29 situational questions.
Estimated time: 12 minutes.
What this diagnostic reveals
If the person who knows AI best on your team left tomorrow, would anything break?
It is one of the 29 questions in the diagnostic. The answer tells you whether you have AI capability or dependency on a single person.
Is your codebase ready for an AI to read it, or does it need someone to explain everything every time?
Most engineering teams in Latin America have not yet prepared their technical context for AI tools to navigate autonomously. That is the first thing the diagnostic evaluates.
What you will get
A map of where you are strong and where you are losing time.
Six dimensions evaluated: from whether your codebase is readable by an AI to whether your users notice the difference.
Your archetype: a name, a narrative, and a mirror.
Seven possible profiles. Yours comes with a description you will recognise and can share with your team.
Three moves for the next 30 days.
Not generic. Calibrated to the size of your team and what the diagnostic found.