Spec-first AI workflows manufacture false certainty in unknown territory. Real progress comes from touching constraints first, then documenting what the system proves to be true.
Early warning signs of product and organizational drift are predictable. The only question is whether you act early, or pay later to unwind avoidable decisions.
Detailed specs do not stop feature drift when teams skip the verification loops that align mental models before anything gets built.
360 feedback and performance cycles don’t develop people if roles and expectations aren’t defined. Without clarity, feedback becomes performance theater.
Shipping more features doesn’t mean progress. If revenue is flat and users are confused, you’re likely optimizing output instead of outcomes.
PRDs decay on contact with reality. This post outlines an AI-native operating model that turns documentation from writing into evidence-based extraction.