Field notes
Practical writing on customer discovery — methods, stories, and honest lessons from the trail.
So, you want to build a company?
Talented young research scientists eager to translate their innovations into real-world impact often struggle because success requires deeply understanding users' actual needs, a gap best closed not through more technical work but through hands-on Customer Discovery, which becomes far more motivating when framed around the problem you care about rather than the goal of "building a company."
The Founder's Dilemma: To Profit or Not To Profit?
Scientists become founders because they want their discoveries to matter; but turning a validated finding into a sustainable company forces a reckoning most researchers aren't trained for. The core tension: building a product requires capital, but capital requires either a high-growth business model (which can pull the technology away from its original purpose) or non-dilutive funding (which is scarce, restrictive, or too small to matter). Caught between these narrow paths, many scientist-founders take a "D-tour" from their original vision and struggle to tell whether that detour has quietly become a dead end. The way through isn't a perfect answer, but rigorous customer discovery: understanding the real, urgent needs of the people you're trying to serve before spending a dollar on development.
Value To The Customer: Are You Making A Difference?
Building a successful startup depends on two fundamentals: understanding market demand and delivering a credible solution, one built on core technology that generates features and quantifiable benefits, whose net value equals those benefits minus the customer's full costs of purchase, adoption, operation, and disposal. To deliver this value consistently and sustainably, the scientist founder must conduct fundamental economic analysis, beginning with price, since pricing is what enables trade between parties exchanging otherwise dissimilar goods. Setting that price is challenging, requiring the founder to weigh alternatives (including the customer doing nothing), adoption and operating costs, and obsolescence, all while preserving enough value for the customer. Ultimately, the founder must craft a pricing schema that satisfies customer needs while ensuring profits at least match the next-best use of their own time and resources.
Primary Market Research -The Bridge Between Scientific Research and Commercial Application
Scientist-founded startups often fail because creators prioritize their own technological perspectives over real market needs. To avoid this, they must step beyond intuition and structure their commercial efforts around rigorous socio-economic hypotheses. By conducting real-world experiments, founders can identify the specific demand drivers and metrics that matter to actual customers.
Going from idea to commercial value.
Curiosity and creativity are fundamental to our nature, without them, we would not have survived as a species. Yet in our modern, post-industrial world, one type of creator holds particular power: the scientist.
Learning is painful, regardless of what AI says.
While AI is a powerful tool to compress the time it takes to build business plans and strategies, founders must not let it replace their personal learning. Because businesses exist to solve human needs, genuine entrepreneurial intuition - honed through real-life experimentation, tough decision-making, and deep reflection - remains a founder's most irreplaceable differentiator.
You will build it, they won't come.
Scientists and engineers eager to commercialize their research often stumble into entrepreneurship with problems that sound important but fail in the market. They fall into the "Galactic Level" trap, framing issues so broadly—"people want faster, safer medicines"—that they can't be tested or validated with real customers. Worse, they build product-centric pitches around impressive technical feats, assuming a 90% efficiency gain will sell itself. In reality, customers have competing priorities, existing workarounds, and strategic constraints that make even breakthrough technologies a hard sell. If you're a technical founder betting on "build it and they will come," this post explains why that assumption could cost you everything.
The noise of AI
AI tools are helping people who work with words be super productive. Create a document? You can ask AI to do it. Summarize a call? Yep, AI has it. Don't know what to say to a disgruntled customer? There's an AI for that.