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.
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The firm's thesis focuses on a rare founder type: a technical expert who also deeply understands how new technologies shift human behavior. This avoids the common pitfall of building technology in search of a problem, leading to products with innate market pull.
The current fundraising environment is the most binary in recent memory. Startups with the "right" narrative—AI-native, elite incubator pedigree, explosive growth—get funded easily. Companies with solid but non-hype metrics, like classic SaaS growers, are finding it nearly impossible to raise capital. The middle market has vanished.
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.
Top growth investors deliberately allocate more of their diligence effort to understanding and underwriting massive upside scenarios (10x+ returns) rather than concentrating on mitigating potential downside. The power-law nature of venture returns makes this a rational focus for generating exceptional performance.
Beyond product-market fit, there is "Founder-Capital Fit." Some founders thrive with infinite capital, while for others it creates a moral hazard, leading to a loss of focus and an inability to make hard choices. An investor's job is to discern which type of founder they're backing before deploying capital that could inadvertently ruin the company.
A successful early-stage strategy involves actively maximizing specific risks—product, market, and timing—to pursue transformative ideas. Conversely, risks related to capital efficiency and team quality should be minimized. This framework pushes a firm to take big, non-obvious swings instead of settling for safer, incremental bets.
Unlike SaaS, deep tech companies have a unique valuation trajectory: a sharp seed-to-Series A increase, a long plateau during R&D, and then massive step-ups post-production. This requires a bimodal investment strategy focusing on early stage and the final private round before inflection.
In capital-intensive sectors, the idea is secondary to the founder's ability to act as a magnet. Their primary function is to relentlessly attract elite talent and secure continuous funding to survive long development timelines before revenue.
Unlike SaaS startups focused on finding product-market fit (market risk), deep tech ventures tackle immense technical challenges. If they succeed, they enter massive, pre-existing trillion-dollar markets like energy or shipping where demand is virtually guaranteed, eliminating market risk entirely.
For deep tech startups lacking traditional revenue metrics, the fundraising pitch should frame the market as inevitable if the technology works. This shifts the investor's bet from market validation to the team's ability to execute on a clear technical challenge, a more comfortable risk for specialized investors.