Why AI Prototypes Stall Before Production

The model is rarely the whole problem. The gap is usually data discipline, evals, deployment, cost, and monitoring — and that gap is what most projects underestimate.

This piece is in draft. The structure is fixed but the long-form is being edited; check back, or ping me if it would be useful sooner.