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Building or refining generative AI models? This guide shows why scraped data falls short—and what to use instead. Learn how real-world behavior signals, clustering, semantic scoring, and visual diversity improve output. Plus, see how Shutterstock’s licensed data and services reduce risk and boost performance. Train smarter, faster, and more responsibly.

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Day 4

Coffee with Your Customer

If your idea survived the FILTER framework, congratulations. But don’t make the mistake of assuming that now you understand your customers.

Filter told you there’s a market, not how they think, what language they use, or what would actually make them pull out their wallet. Those insights only come from sitting across from real humans and having conversations.

This makes it one of the vital chapters of this book, where you will be embarking on the most humbling journey of your entrepreneurial life. If done right, you might realize that 90 percent of what you think you know about the customer is wrong—and perhaps that’s exactly where you want to be.

You must be wondering why we still need to sit across from real people and ask them uncomfortable questions when AI can predict human behavior with startling accuracy. It’s indeed impressive how AI can tell you what people do, but only humans can tell you why they do it. And the “why” is where fortunes are made and lost. In the age of AI, always remind yourself: algorithms give you patterns, but only humans give you reasons.

Your brain is a pattern-matching machine that loves to confirm what it already believes. Every assumption you make about a customer is a potential landmine that could destroy your business overnight. Yet most founders treat customer interviews like checkboxes. The problem isn’t that they don’t talk to customers. It’s that they talk to the wrong people, ask the wrong questions, and interpret the answers through rose-colored glasses.

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