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AI Strategy·7 min read

Why Most AI Prototypes Fail Before They Ship

The graveyard of AI projects isn't filled with bad technology. It's filled with good technology pointed at the wrong problem.

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In this article

→Failure pattern #1: Starting with the technology, not the problem
→Failure pattern #2: Building for the demo, not for the user
→Failure pattern #3: No path from prototype to production
→Failure pattern #4: Skipping the data conversation

May 12, 2026

All Articles

Enterprise6 min read

The Hidden Cost of Legacy Systems in the AI Era

Technical debt has always been expensive. In the age of AI, it's becoming a strategic liability — and most leadership teams don't know how much it's costing them.

April 28, 2026

AI Strategy5 min read

How to Scope an AI Feature Without a Data Science Team

You don't need a team of ML engineers to ship meaningful AI features. You need a clear hypothesis, access to the right APIs, and a validation process that doesn't waste six months.

April 10, 2026

Product Design5 min read

Design Systems Are the Infrastructure Your AI Product Team Is Missing

AI products move fast. Design systems are what let you move fast without breaking things — but most AI teams treat them as a luxury they'll get to later.

March 22, 2026

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