Massive investments in AI hyperscalers are not the end game. They are laying foundational infrastructure, like the 19th-century electrical grid, which will enable a future explosion of derivative applications across all industries.
Large companies dismiss opportunities that aren't massive enough to impact their market cap (e.g., 'just a $2 billion opportunity'). This creates openings for startups to dominate valuable niches that incumbents ignore due to their own scale.
Series A investors have become fixated on unrealistic '10x year-over-year growth' metrics. This creates a difficult funding environment for fundamentally strong companies that are growing at a more sustainable but less hyped 3-4x rate.
The long-held Silicon Valley belief that 'the best tech always wins' is a dangerous myth. For the next decade, success will be determined by distribution strategy—the ability to reach customers at scale—not just technical prowess.
Deep tech is highly varied (space, robotics, bio). VCs accustomed to the homogenous SaaS playbook lack the expertise to underwrite these diverse areas, so they default to chasing a few consensus 'winners,' causing unhealthy capital concentration.
The common saying 'You'll be replaced by someone using AI' is a fallacy. Many core venture capital functions are susceptible to direct replacement by AI, and VCs who ignore this risk doing so at their own peril.
A simple heuristic to define deep tech: if you overhear a startup's pitch and think, 'I have no idea how to build that,' it's likely deep tech. This moves beyond jargon to a practical, intuitive understanding.
Limited Partners and VCs increasingly believe the SaaS investment thesis has 'run its course' for generating massive returns. This perception is driving capital flow into deep tech, now viewed as the next wave for outsized performance.