The traditional IPO exit is being replaced by a perpetual secondary market for elite private companies. This new paradigm provides liquidity for investors and employees without the high costs and regulatory burdens of going public. This shift fundamentally alters the venture capital lifecycle, enabling longer private holding periods.

With hundreds of unicorns and only about 20 tech IPOs per year, the market has a 30-year backlog. Consolidations between mid-size unicorns, like the potential Fivetran and dbt deal, are a necessary strategy for VCs to create IPO-ready companies and generate much-needed liquidity from their portfolios.

Top-tier private companies like Stripe and Databricks are actively choosing to delay IPOs, viewing the public market as an inferior "product." With access to cheaper private capital and freedom from quarterly scrutiny and activist investors, staying private offers a better environment to build long-term value.

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.

In the SaaS era, a 2-year head start created a defensible product moat. In the AI era, new entrants can leverage the latest foundation models to instantly create a product on par with, or better than, an incumbent's, erasing any first-mover advantage.

Aggregate venture capital investment figures are misleading. The market is becoming bimodal: a handful of elite AI companies absorb a disproportionate share of capital, while the vast majority of other startups, including 900+ unicorns, face a tougher fundraising and exit environment.

AI companies raise subsequent rounds so quickly that little is de-risked between seed and Series B, yet valuations skyrocket. This dynamic forces large funds, which traditionally wait for traction, to compete at the earliest inception stage to secure a stake before prices become untenable for the risk involved.

The ideal period for venture investment—after a company is known but before its success becomes obvious—has compressed drastically. VCs are now forced to choose between investing in acute uncertainty or paying massive, near-public valuations.

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.