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.

Historically, private equity was pursued for its potential outperformance (alpha). Today, with shrinking public markets, its main value is providing diversification and access to a growing universe of private companies that are no longer available on public exchanges. This makes it a core portfolio completion tool.

WCM realized their portfolio became too correlated because their research pipeline itself was the root cause, with analysts naturally chasing what was working. To fix this, they built custom company categorization tools to force diversification at the idea generation stage, ensuring a broader set of opportunities is always available.

The current AI boom isn't just another tech bubble; it's a "bubble with bigger variance." The potential for massive upswings is matched by the risk of equally significant downswings. Investors and founders must have an unusually high tolerance for risk and volatility to succeed.

The leadership change at Sequoia, arguably the world's top venture firm, is a strong indicator of the intense pressure the entire VC industry faces. It reflects a fear of falling behind in the AI race and the brutal reality that even the best are struggling to adapt to the new competitive landscape.

The dominant VC narrative demands founders focus on a single venture. However, successful entrepreneurs demonstrate that running multiple projects—a portfolio approach mirrored by VCs themselves—is a viable path, contrary to the "focus on one thing" dogma.

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.

AI drastically accelerates the ability of incumbents and competitors to clone new products, making early traction and features less defensible. For seed investors, this means the traditional "first-mover advantage" is fragile, shifting the investment thesis heavily towards the quality and adaptability of the founding team.

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.