AI Pilots to Production

Engineering AI Products and Escaping Pilot Purgatory.

Most AI initiatives stall after a convincing demo. Roughly 88% of AI pilots never reach production — not because models are weak, but because teams confuse a notebook with a product, skip the business contract, ignore unit economics, and ship architecture that cannot survive real traffic, real data, or real compliance.

This course is an engineering and operating playbook for escaping pilot purgatory. You will learn how to lock baselines before kickoff, fund scale only against held-out evidence, design wrappers and evaluation loops that keep agents safe, and transfer ownership to the business with bounded autonomy.

Who it is for

Founders and C-level leaders, product managers, architects, AI/MLOps engineers, security and compliance owners — anyone accountable for moving AI from experiment to P&L impact.

What you will leave with

• A clear distinction between a demo and production readiness
• Templates and frameworks for contracts, metrics, budgets, and RACI
• Architectural patterns for cost, reliability, evaluation, and fallbacks
• A go-to-production path: audit, shadow mode, and phased autonomy

How the course works

Ten modules, taken sequentially. Each topic ends with a short check; each module has a checkpoint quiz. Content is English-first. Prefer a human pass over quiz answers and factual claims before treating the course as final.