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.

As Bitcoin matures, its risk-return profile is changing. The era of doubling in value every couple of years may be over. Instead, it could transition into a high-performing asset that reliably generates 15-25% annualized returns, outperforming traditional assets but no longer offering the explosive, "get rich quick" upside of its early days.

Today's massive AI company valuations are based on market sentiment ("vibes") and debt-fueled speculation, not fundamentals, just like the 1999 internet bubble. The market will likely crash when confidence breaks, long before AI's full potential is realized, wiping out many companies but creating immense wealth for those holding the survivors.

Current AI investment patterns mirror the "round-tripping" seen in the late '90s tech bubble. For example, NVIDIA invests billions in a startup like OpenAI, which then uses that capital to purchase NVIDIA chips. This creates an illusion of demand and inflated valuations, masking the lack of real, external customer revenue.

In the current market, AI companies see explosive growth through two primary vectors: attaching to the massive AI compute spend or directly replacing human labor. Companies merely using AI to improve an existing product without hitting one of these drivers risk being discounted as they lack a clear, exponential growth narrative.

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 massive demand for GPUs from the crypto market provided a critical revenue stream for companies like NVIDIA during a slow period. This accelerated the development of the powerful parallel processing hardware that now underpins modern AI models.

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.

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.