Mercor's Brendan Foody accuses Sequoia of 'dual-pricing' valuation inflation

The Accusation

Brendan Foody, co-founder of AI talent platform Mercor (last valued at $10 billion), publicly called out Sequoia Capital on social media for what he characterized as systematic inflation of headline valuations. According to TechCrunch AI, Foody alleged that over a six-month period, he observed roughly half a dozen funding rounds where Sequoia deployed a split-tranche structure—investing a substantial portion of capital at a lower valuation in one tranche, then placing a much smaller amount at a significantly higher price in a second tranche—while allowing founders to misrepresent only the higher valuation to employees and other investors. “The ‘sequoia scam’ is worse than a single horror story,” Foody wrote on X, suggesting the practice masked the true cost basis of lead investors while creating inflated market perception.

How the Two-Tranche Mechanism Works

The structure Foody described operates as follows: a lead VC firm commits a meaningful capital allocation at a preferential, lower valuation in an initial funding extension or early tranche. Days or weeks later, a second closing occurs at a substantially higher headline price, with the VC contributing a nominal additional amount. The announced valuation reflects only the higher tier, manufacturing the impression of dominant market momentum. The lead investor’s blended entry price remains significantly lower than any external observer would infer from the public announcement.

TechCrunch documented concrete examples. Serval, an AI-driven IT helpdesk startup, announced a $75 million Series B at a $1 billion valuation led by Sequoia in June 2026. According to reporting from The Wall Street Journal cited by TechCrunch, Sequoia had valued Serval at less than $400 million just days earlier in a Series A extension—less than 40% of the headline figure. Similarly, at Aaru, a startup using AI for behavioral simulation in market research, lead investor Redpoint backed the company at a $450 million internal valuation while permitting announcement of a $1 billion headline price.

Sequoia’s Defense

Sequoia Capital partner Shaun Maguire responded directly to Foody on X, neither fully denying the practice nor accepting the framing of deliberate deception. Maguire acknowledged that “this has happened approximately five times during my seven years at Sequoia,” but recharacterized the mechanism as a market-driven response to competitive pressure. According to Maguire’s account, when other investors demand premium prices for high-demand AI startups—often at multiples Sequoia believes are unsustainable—Sequoia decouples its company-building partnership from its capital deployment. The firm invests less capital at the inflated price, preserving the founder relationship while avoiding overcommitment to inflated valuations. “I’m not aware of anything shady here,” Maguire wrote, framing the practice as a rational allocation strategy rather than deliberate misrepresentation. He also offered a qualified acknowledgment of Mercor’s success, noting it was a “miss” for Sequoia.

Why This Matters

The dispute surfaces a structural tension in late-stage venture funding: founders have incentives to publicize the highest valuation possible to attract talent and downstream investors, while lead VCs have incentives to minimize their blended cost basis to maximize returns and optionality. The two-tranche structure satisfies both by creating an information asymmetry—the headline valuation is real (other investors did pay it), but incomplete (it omits the lead investor’s preferential allocation at a lower price). As AI fundraising has accelerated through 2026, with competition for deal flow intensifying, this practice may become more common. The question for founders and downstream stakeholders is whether this structure should be disclosed explicitly in term sheets, side letters, or public announcements, or whether market norms and founder-investor trust suffice to prevent abuse. Foody’s public call-out suggests the practice is reaching a visibility threshold where normalization is meeting resistance.