AI teams split into 2 camps right now:
Camp 1: Ship constantly. Get the feature out, learn from real users, fix the mess later.
Camp 2: Slow down and build the foundation. Evals, guardrails, clean architecture, reusable workflows, proper infra.
In modern software development, especially with AI, which side do you think actually wins?
Drop your take.