While many investors hunt for pure monopolies, most tech markets naturally support a handful of large players in an oligopoly structure. Markets like payments (Stripe, Adyen, PayPal) demonstrate that multiple large, successful companies can coexist, a crucial distinction for market analysis and investment strategy.
Contrary to the belief that number two players can be viable, most tech markets are winner-take-all. The market leader captures the vast majority of economic value, making investments in second or third-place companies extremely risky.
The most lucrative exit for a startup is often not an IPO, but an M&A deal within an oligopolistic industry. When 3-4 major players exist, they can be forced into an irrational bidding war driven by the fear of a competitor acquiring the asset, leading to outcomes that are even better than going public.
Obsessing over creating a new market category is often a mistake. Data shows the vast majority of successful public tech companies compete within established categories. It's more effective to get "invited to the party" by using a known category label and then winning with a sharp, differentiated value proposition.
The AI industry is not a winner-take-all market. Instead, it's a dynamic "leapfrogging" race where competitors like OpenAI, Google, and Anthropic constantly surpass each other with new models. This prevents a single monopoly and encourages specialization, with different models excelling in areas like coding or current events.
AI favors incumbents more than startups. While everyone builds on similar models, true network effects come from proprietary data and consumer distribution, both of which incumbents own. Startups are left with narrow problems, but high-quality incumbents are moving fast enough to capture these opportunities.
The natural mechanics of network-based markets inherently lead to dominant players in search, social media, and browsers. This erodes the web's initial decentralized promise of "digital sovereignty" for individual users and creators.
The firm targets markets structured like the famous movie scene: first place wins big, second gets little, and third fails. They believe most tech markets, even B2B SaaS without network effects, concentrate value in the #1 player, making leadership essential for outsized returns.
Conventional venture capital wisdom of 'winner-take-all' may not apply to AI applications. The market is expanding so rapidly that it can sustain multiple, fast-growing, highly valuable companies, each capturing a significant niche. For VCs, this means huge returns don't necessarily require backing a monopoly.
Don't underestimate the size of AI opportunities. Verticals like "AI for code" or "AI for legal" are not niche markets that will be dominated by a few players. They are entire new industries that will support dozens of large, successful companies, much like the broader software industry.
New technology like AI doesn't automatically displace incumbents. Established players like DoorDash and Google successfully defend their turf by leveraging deep-rooted network effects (e.g., restaurant relationships, user habits). They can adopt or build competing tech, while challengers struggle to replicate the established ecosystem.