Companies like Amazon (from books to cloud) and Intuitive Surgical (from one specific surgery to many) became massive winners by creating new markets, not just conquering existing ones. Investors should prioritize businesses with the innovative capacity to expand their TAM, as initial market sizes are often misleadingly small.
While a strong business model is necessary, it doesn't generate outsized returns. The key to successful growth investing is identifying a Total Addressable Market (TAM) that consensus views as small but which you believe will be massive. This contrarian take on market size is where the real alpha is found.
Startups often fail to displace incumbents because they become successful 'point solutions' and get acquired. The harder path to a much larger outcome is to build the entire integrated stack from the start, but initially serve a simpler, down-market customer segment before moving up.
The slow growth of public SaaS isn't just an execution failure; it's a structural problem. We created so many VC-backed companies that markets became saturated, blocking adjacent expansion opportunities and creating a 'Total Addressable Market (TAM) trap'.
Initial data suggested the market for design tools was too small to build a large business. Figma's founders bet on the trend that design was becoming a key business differentiator, which would force the market to expand. They focused on building for the trend, not the existing TAM.
The conversation around Ideal Customer Profile (ICP) has evolved beyond simple refinement. With newly accessible data, companies are fundamentally re-evaluating their Total Addressable Market (TAM), challenging long-held assumptions about who their potential customers are and how big the opportunity is.
For venture capitalists investing in AI, the primary success indicator is massive Total Addressable Market (TAM) expansion. Traditional concerns like entry price become secondary when a company is fundamentally redefining its market size. Without this expansion, the investment is not worthwhile in the current AI landscape.
This provides a simple but powerful framework for venture investing. For companies in markets with demonstrably huge TAMs (e.g., AI coding), valuation is secondary to backing the winner. For markets with a more uncertain or constrained TAM (e.g., vertical SaaS), traditional valuation discipline and entry price matter significantly.
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.
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.