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.

Unlike software, where customer acquisition is the main risk, the primary diligence question for transformative hardware is technical feasibility. If a team can prove they can build the product (e.g., a cheaper missile system), the market demand is often a given, simplifying the investment thesis.

Unlike software, hard tech involves long scale-up timelines and high capital costs. Founders must specifically seek the small subset of investors and partners who understand the market context and have the risk appetite for massive, world-changing opportunities, rather than trying to appeal to all VCs.

Unlike software distributed instantly through browsers, physical AI diffuses slowly across varied industries, geographies, and machines. This makes time and longevity critical factors. Customers need a stable, long-term partner, making it difficult for new, less-established startups to compete.

As AI commoditizes software, hardware is re-emerging as a key defensibility layer for startups. A decade ago, VCs avoided hardware, but now a physical device tied to a software subscription creates powerful stickiness and justifies high valuations, representing a major shift in investment strategy.

Applied AI startups must solve immediate customer problems by building proprietary technology, even if they know it will be commoditized by foundation models in a few years. The strategy is to win customers now with superior tech, building a product and market position that will endure after the technology becomes table stakes.

In an era where AI makes building products easier for everyone, technical execution is no longer a defensible moat. The new determinant of startup success is founder resiliency and a deep passion for their vertical. Victory belongs to those who will relentlessly refine their product for a decade, not just build the first version.

The competitive AI landscape has forced founders from pure research backgrounds to adopt a strong focus on financial returns. This shift from idealistic AGI pursuits to "hard capitalism" means they make rational R&D spending decisions, de-risking investor concerns.

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.