Unpacking "A Crisis Moment In Seed"

AI infrastructure startups need $100 million in capital. Seed funds write $500,000 checks. The math doesn't work, and Rob Go from NextView Ventures thinks this mismatch is breaking the traditional seed investing playbook.

Go argues that seed investors face an existential challenge: the most exciting AI opportunities require capital commitments that dwarf typical seed fund capabilities. "Whether it's a company like Anthropic or OpenAI or any type of company that's really building fundamental infrastructure, those tend to be very capital intensive businesses," Go explains. "That's actually not a good product market fit between a founder going to a seed investor when they may need $100,000,000 fairly quickly."

This capital intensity problem pushes seed investors toward AI application companies instead of infrastructure plays. But that creates a second problem: application-layer startups now face unprecedented competition because development has become radically democratized. Go acknowledges this concern is real when pressed on whether coding tools have made it possible to "build something that is at parity with something that's already been funded" in just weeks rather than months.

The result is a squeeze play. Seed investors can't compete for the big infrastructure deals that define AI's future, but they're crowding into application markets where barriers to entry have collapsed. Meanwhile, mega funds and accelerators like Y Combinator are extending their reach downward, competing more aggressively for early-stage deals because "people believe in the power a lot even more because of how disruptive AI is gonna be."

Go's analysis suggests this isn't just a temporary market dislocation. The AI wave has created "extreme disruption in how mega funds prosecute seed markets" precisely because there's broad consensus about AI's transformative potential. When everyone agrees that artificial intelligence will reshape entire industries, larger funds naturally become more willing to take early-stage risks they previously avoided.

This consensus effect amplifies the capital mismatch problem. Infrastructure companies need massive upfront investment to train models and build competitive moats. Application companies can launch quickly but face immediate copying risk from well-funded competitors. Seed investors find themselves caught between deals too big to finance and markets too crowded to dominate.

The commodity development tools that enable rapid copying represent a fundamental shift from previous technology cycles. In traditional enterprise software, building a competitive product required months of development time and specialized engineering talent. Now, according to Go's observation, funded startups can be replicated "over a course of two to four weeks" by competitors with access to the same AI coding tools.

This dynamic creates a particular challenge for seed investors who rely on early-mover advantages and development speed as competitive moats. If any funded startup can be quickly copied by better-funded competitors, seed investors must identify different sources of defensibility. Product market fit alone may no longer provide sufficient protection during the vulnerable early scaling phase.

Rob Go's framework suggests seed investors need to completely rethink their value proposition. They can't win on capital size against mega funds moving downstream. They can't win on development speed in markets where coding has been commoditized. The traditional seed investing model assumed that small checks, early relationships, and development time would create sustainable competitive advantages.

The solution requires focusing on opportunities where seed-scale capital still creates meaningful advantages. This might mean targeting vertical applications where domain expertise matters more than development speed, or finding founders who can build network effects and data moats that resist easy replication. Seed investors may need to become more selective about which AI trends they chase and more creative about the types of defensibility they help portfolio companies build.

Watch for seed funds that start specializing in specific AI application verticals rather than taking broad technology bets. The funds that thrive will likely be those that develop deep expertise in particular domains where their smaller size becomes an advantage rather than a constraint. The crisis Go identifies is real, but it's also an opportunity for seed investors willing to adapt their strategies to AI's unique capital and competitive dynamics.