The most significant companies are often founded long before their sector becomes a "hot" investment theme. For example, OpenAI was founded in 2015, years before AI became a dominant VC trend. Early-stage investors should actively resist popular memes and cycles, as they are typically trailing indicators of innovation.
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When evaluating AI startups, don't just consider the current product landscape. Instead, visualize the future state of giants like OpenAI as multi-trillion dollar companies. Their "sphere of influence" will be vast. The best opportunities are "second-order" companies operating in niches these giants are unlikely to touch.
Arif Hilali of Bain Capital Ventures warns investors against mistaking Silicon Valley hype for mainstream adoption. He uses cloud computing's slow, multi-decade rollout as a parallel for AI, suggesting that even when a trend seems obvious inside the tech bubble, its true market penetration takes much longer than anticipated.
During a fundamental technology shift like the current AI wave, traditional market size analysis is pointless because new markets and behaviors are being created. Investors should de-emphasize TAM and instead bet on founders who have a clear, convicted vision for how the world will change.
AI should be viewed not as a new technological wave, but as the final, mature stage of the 60-year computer revolution. This reframes investment strategy away from betting on a new paradigm and towards finding incumbents who can leverage the mature technology, much like containerization capped the mass production era.
The traditional, long-term venture capital cycle may be accelerating. As both macro and technology cycles shorten, venture could start mirroring the more frequent 4-5 year boom-and-bust patterns seen in crypto. This shift would force founders, VCs, and LPs to become more adept at identifying where they are in a much shorter cycle.
The true economic revolution from AI won't come from legacy companies using it as an "add-on." Instead, it will emerge over the next 20 years from new startups whose entire organizational structure and business model are built from the ground up around AI.
The focus on AI among institutional investors is so absolute that promising non-AI companies risk "dying of neglect" and being unable to secure follow-on funding. This creates a potential opportunity gap for angel investors to fund valuable businesses in overlooked sectors.
Analysis shows that the themes venture capitalists and media hype in any given year are significantly delayed. Breakout companies like OpenAI were founded years before their sector became a dominant trend, suggesting that investing in the current "hot" theme is a strategy for being late.
When evaluating revolutionary ideas, traditional Total Addressable Market (TAM) analysis is useless. VCs should instead bet on founders with a "world-bending vision" capable of inducing a new market, not just capturing an existing one. Have the humility to admit you can't predict market size and instead back the visionary founder.
During major tech shifts like AI, founder-led growth-stage companies hold a unique advantage. They possess the resources, customer relationships, and product-market fit that new startups lack, while retaining the agility and founder-driven vision that large incumbents have often lost. This combination makes them the most likely winners in emerging AI-native markets.
