A massive valuation for a "seed" round can be misleading. Often, insiders have participated in several unannounced, cheaper tranches. The headline number is just the final, most expensive tier, used to create FOMO and set a high watermark for new investors.

The VC landscape has split into two extremes. A few elite firms and sovereign wealth funds are funding mega-rounds for about 20-30 top AI companies, while the broader ecosystem of seed funds, Series A specialists, and new managers is getting crushed by a lack of capital and liquidity.

Y Combinator's model pushes companies to raise at high valuations, often bypassing traditional seed rounds. Simultaneously, mega-funds cherry-pick the most proven founders at prices seed funds cannot compete with. This leaves traditional seed funds fighting for a narrowing and less attractive middle ground.

Despite headline figures suggesting a venture capital rebound, the funding landscape is highly concentrated. A handful of mega-deals in AI are taking the vast majority of capital, making it harder for the average B2B SaaS startup to raise funds and creating a deceptive market perception.

Data shows companies with the highest seed valuations graduate to Series A only slightly more often than those in the 2nd and 3rd quartiles. The real danger lies at the bottom: companies with the lowest-quartile valuations are only half as likely to raise a Series A, suggesting raising too little capital is a critical failure point.

Venture rounds are compressing and conflating, with massive "seed" rounds of $30M+ essentially combining a seed and Series A. This sets a dangerous trap: the expectations for your next funding round will be equivalent to those of a traditional Series B company, dramatically raising the bar for growth.

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.

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.