Take 5 developers. Put them on the same Git repo. Let them freely use Cursor, Copilot, or Cline without any shared rules. In a month, your architecture will have no soul left. Welcome to the Silent Divergence.
Generative AI, by definition, produces what it has seen most often across public GitHub repositories. For a technical team, the risk is massive: the total loss of your code's identity. If your studio's DNA (like ours at Vibrisse) is eco-design, hardcore accessibility, or squeezing 60fps out of React Three Fiber, a "vanilla" AI will suggest generic solutions — often bloated and over-engineered. It silently erases your team's expertise commit by commit, replacing it with invisible technical debt.
Code doesn't lie. Generic AI does.
The "Best Practices" War and the Illusion of Authority
Worse than the statistical average, I regularly observe what I call the LLM War. Developer A asks ChatGPT for a solution; it proposes Pattern X, swearing it's the state of the art. Developer B asks Copilot; it pushes Pattern Y as the absolute standard. Each developer merges their code with blind trust in "their" AI. The result? The team parasitizes itself, the architecture becomes schizophrenic, and PR debates drag on forever ("But Claude told me this was the best practice!").
