Artist's co-founder warns that the biggest mistake founders make is building technology too early. Her team validated their text-based learning concept by manually texting early users, confirming the core hypothesis and user engagement before committing significant engineering resources.

The goal of early validation is not to confirm your genius, but to risk being proven wrong before committing resources. Negative feedback is a valuable outcome that prevents building the wrong product. It often reveals that the real opportunity is "a degree to the left" of the original idea.

The barrier to building AI products has collapsed. Aspiring builders should create a one-hour prototype to focus on the truly hard part: validating that they're solving a problem people actually want fixed. The bottleneck has shifted from technical execution to user validation.

Large companies often identify an opportunity, create a solution based on an unproven assumption, and ship it without validating market demand. This leads to costly failures when the product doesn't solve a real user need, wasting millions of dollars and significant time.

In AI, low prototyping costs and customer uncertainty make the traditional research-first PM model obsolete. The new approach is to build a prototype quickly, show it to customers to discover possibilities, and then iterate based on their reactions, effectively building the solution before the problem is fully defined.

Don't let the novelty of GenAI distract you from product management fundamentals. Before exploring any solution, start with the core questions: What is the customer's problem, and is solving it a viable business opportunity? The technology is a means to an end, not the end itself.

For deep tech startups aiming for commercialization, validating market pull isn't a downstream activity—it's a prerequisite. Spending years in a lab without first identifying a specific customer group and the critical goal they are blocked from achieving is an enormous, avoidable risk.

In the rush to adopt AI, teams are tempted to start with the technology and search for a problem. However, the most successful AI products still adhere to the fundamental principle of starting with user pain points, not the capabilities of the technology.

Crisp.ai's founder advocates for selling a product before it's built. His team secured over $100,000 from 30 customers using only a Figma sketch. This approach provides the strongest form of market validation, proving customer demand and significantly strengthening a startup's position when fundraising with VCs.