PoC vs MVP vs production: know which one you're building

A surprising number of stalled AI projects are really just confusion about what's being built. A proof-of-concept, a minimum viable product, and a production system are three different things with three different bars — and treating one like another is how budgets evaporate.

Proof-of-concept: does it work at all?

A PoC exists to kill or confirm an assumption fast and cheap. Can the model do the task with our data, in principle? It should be scrappy, throwaway, and time-boxed to days or a couple of weeks. The cardinal sin is letting a PoC's success convince everyone the hard part is done. It isn't — it's barely started.

MVP: is it worth using?

An MVP is the smallest thing a real user will actually rely on. Now the unglamorous 80% arrives: error handling, edge cases, evaluation, a usable interface, basic guardrails. An MVP is narrow on purpose — one workflow, done properly — but it's real software, not a demo.

Production: can it be trusted, at scale, for years?

Production is a different universe: monitoring, security, governance, cost control, observability, and the operating model to keep it healthy as the world changes underneath it. This is where most of the genuine engineering lives, and where the projects that skipped readiness come undone.

Why this matters

The danger is silent category drift — a PoC that gets quietly promoted to production without ever paying production's tax. Name which one you're building, fund it accordingly, and be explicit about the gate it has to pass to graduate to the next. Half of delivery is just refusing to pretend a demo is a product. [[A line here about an engagement where naming the category reset everyone's expectations would land well.]]