A market bifurcation is underway where investors prioritize AI startups with extreme growth rates over traditional SaaS companies. This creates a "changing of the guard," forcing established SaaS players to adopt AI aggressively or risk being devalued as legacy assets, while AI-native firms command premium valuations.

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.

Venture-backed private companies represent a massive, $5 trillion market cap, exceeding half the value of the 'Magnificent Seven' public tech stocks. This scale signifies that private markets are now a mature, institutional asset class, not a small corner of finance.

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.

The rapid evolution of AI means traditional private equity M&A timelines are too slow. PE firms and their portfolio companies must now behave more like venture capitalists, acquiring earlier-stage, riskier AI companies to secure necessary technology before it becomes unaffordable or obsolete.

Michael Burry's comparison of OpenAI to Netscape is apt regarding market share erosion due to intense competition. However, the AI market is expanding exponentially. Unlike the browser market of the 90s, OpenAI can lose market share percentage yet still see massive absolute revenue and usage growth.

The startup landscape now operates under two different sets of rules. Non-AI companies face intense scrutiny on traditional business fundamentals like profitability. In contrast, AI companies exist in a parallel reality of 'irrational exuberance,' where compelling narratives justify sky-high valuations.

Contrary to common belief, the earliest AI startups often command higher relative valuations than established growth-stage AI companies, whose revenue multiples are becoming more rational and comparable to public market comps.

As algorithms become more widespread, the key differentiator for leading AI labs is their exclusive access to vast, private data sets. XAI has Twitter, Google has YouTube, and OpenAI has user conversations, creating unique training advantages that are nearly impossible for others to replicate.