Article
Designing AI Systems That Ship
How to move from AI concepts to production systems with measurable outcomes.
Most AI initiatives fail at the handoff between prototype and production. Teams can train a model, but struggle to operationalize it in real workflows.
A delivery-first AI roadmap focuses on:
- Problem framing: define one clear business metric.
- Data readiness: establish data quality checks and ownership.
- Model fit: choose the smallest model that solves the problem.
- Deployment: package inference with observability from day one.
- Iteration: improve with feedback loops and drift monitoring.
Whether the use case is chatbot automation, recommendation systems, or fraud detection, the same principle applies: production value is the objective, not model novelty.