Technology
Topic
AI Proof of Concept & Prototypes
An AI PoC should answer a specific risk: feasibility, data quality, user value, or cost to operate—not produce a flashy demo that cannot graduate into a product. These articles separate prototypes, PoCs, and MVPs so you know what evidence you are buying.
4 articles in this cluster
Concept Lab
Technology
AI PoC vs prototype vs MVP: Pick the evidence you need
Three artifacts, three budgets, one mistake: buying the wrong proof for the decision your board or users need to make next.
Technology
AI proof of Concept: When to build one
The AI idea looks obvious in the deck. The risky assumptions about data, models, and integration usually hide until someone funds the full build.
Technology
Code is a commodity. Software engineering is not.
Everyone says AI made software cheap. Most are counting lines of code—not the judgment, risk, and systems work that actually ships products.
Frequently asked questions
What is an AI proof of concept?
A time-boxed experiment that tests the riskiest AI assumption with measurable success criteria—usually feasibility, accuracy, latency, cost, or user value—before a full product build.
How is an AI PoC different from an MVP?
A PoC proves a technical or value risk. An MVP proves market demand with a product people can use. Mixing them often wastes budget on demos that neither validate tech nor sell.
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