Validation by analogy — it worked for Slack, why not for us — is the most common and least useful form of market research. It describes what was possible in a different context, for a different team, at a different time. None of those variables transfer to your situation.
Most validation frameworks are designed to get a yes. The customer interview ends with someone saying the idea sounds promising.
LLM-native products fail not because the model’s average output quality is poor, but because users encounter the variance the average hides. Designing for the mean is designing for an experience that no real user has. This post explains the failure pattern and how to build LLM products that handle variance as a first-class design constraint.
The customers who churn silently are more informative than those who complain. Silence means the product did not matter enough to warrant a conversation. A product that does not matter enough to cancel is a trial that ran long — and silent churn is the evidence that the product never became indispensable.
Most AI-native startups validate the technology before they validate the problem — the reverse of the order that matters. A technically impressive solution to a problem nobody urgently has is still a product without a market. The AI works. The question is whether the problem it solves is urgent enough to pay for.
Most founders building on foundation models worry about model failure. The real risk runs the other direction: the model improves, and the capability that justified your product is now a built-in feature. This post explains how to identify which parts of your differentiation are exposed to this risk and how to build around it.
Using AI to generate your first version and using AI to learn your market are two different activities. The code is now cheap to produce. The insight that tells you what to build is not. Founders who conflate the two end up with faster-produced products that solve the wrong problem.
Building in public as a validation strategy attracts the wrong audience. The people who follow founder journeys are systematically different from the people who will pay for the product. Optimizing for audience engagement actively misleads you about the market you are trying to reach.
Conviction and stubbornness are indistinguishable from the inside. The difference is only visible in retrospect, which means founders who pride themselves on not pivoting are often confusing identity protection with strategic clarity. Persistence is only a virtue when what you are persisting toward is still the right direction.
