Before building, founders in complex industries must deeply understand the operational rigor and nuances of their target vertical. This 'operator market fit' ensures the solution addresses real-world workflows, as a one-size-fits-all approach is doomed to fail.

For early-stage MedTech startups, key milestones for investors are not just regulatory successes. They are fundamental proofs of concept—showing the device works in a model and demonstrating how it would function in a clinical setting. This builds an investor's vision of the product's future.

Truly transformative healthcare companies often solve "boring" but fundamental problems. Instead of tackling surface-level symptoms (e.g., appointment booking), the best founders dig deep to fix the complex, underlying infrastructure issues of the healthcare system, creating a durable competitive moat.

Companies with radical, long-term visions often fail by focusing exclusively on their ultimate goal without a practical, near-term product. Successful deep tech companies balance their moonshot ambition with short-term deliverables that provide immediate user value and sustain the business on its journey.

The core innovation for the Cobra OS wasn't a complex discovery but the disciplined application of a known principle: miniaturizing endovascular devices always makes them safer. By focusing on shrinking the device, they inherently improved safety by reducing the size of the arterial access site.

Successful MedTech innovation starts by identifying a pressing, real-world clinical problem and then developing a solution. This 'problem-first' approach is more effective than creating a technology and searching for an application, a common pitfall for founders with academic backgrounds.

While the primary goal of making the Cobra OS smaller was to improve safety, an unexpected benefit emerged. The device's smaller profile made it suitable for patients with smaller anatomies, such as women, opening a major new clinical application in postpartum hemorrhage.

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.

Unconventional AI operates as a "practical research lab" by explicitly deferring manufacturing constraints during initial innovation. The focus is purely on establishing "existence proofs" for new ideas, preventing premature optimization from killing potentially transformative but difficult-to-build concepts.