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.
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.
The traditional SaaS method of asking customers what they want doesn't work for AI because customers can't imagine what's possible with the technology's "jagged" capabilities. Instead, teams must start with a deep, technology-first understanding of the models and then map that back to customer problems.
Technical founders often create a perfect solution to a real problem but still fail. That's because problem-solution fit is useless without product-market fit. An elegant solution that isn't plugged into the market—with the right GTM, pricing, and messaging—solves nothing in practice. It's unheard and unseen.
Instead of searching for a market to serve, founders should solve a problem they personally experience. This "bottom-up" approach guarantees product-market fit for at least one person—the founder—providing a solid foundation to build upon and avoiding the common failure of abstract, top-down market analysis.
This reframes the fundamental goal of a startup away from a supply-side focus (building) to a demand-side focus (discovery). The market's unmet need is the force that pulls a company and its product into existence, not the other way around.
A visionary founder must be willing to shelve their ultimate, long-term product vision if the market isn't ready. The pragmatic approach is to pivot to an immediate, tangible customer problem. This builds a foundational business and necessary ecosystem trust, paving the way to realize the grander vision in the future.
Moving from a science-focused research phase to building physical technology demonstrators is critical. The sooner a deep tech company does this, the faster it uncovers new real-world challenges, creates tangible proof for investors and customers, and fosters a culture of building, not just researching.