VCs who missed the 2020–2025 frontier AI cohort are now being questioned by LPs and founders
Sep 12, 2025
Key Points
- Venture firms that missed foundation model bets from 2020–2025 face credibility pressure from LPs and founders questioning their absence from OpenAI, Anthropic, Eleven Labs, and Midjourney.
- Generalist VCs distracted by portfolio damage in fintech and crypto failed to recognize the 2022 AI inflection point, then faced closed entry windows and prohibitive valuations by the time frontier models' strategic importance became obvious.
- Founders now use VC frontier AI exposure as a signaling filter, viewing investors without positions in foundation models or application-layer companies as either late-stage capital or lacking conviction.
Summary
A cohort of traditional venture capital firms faces pressure from limited partners and next-generation founders for missing the 2020–2025 frontier AI wave entirely. VCs who didn't position themselves in companies like OpenAI, Anthropic, Eleven Labs, and Midjourney are now scrambling to explain their absence to stakeholders.
The miss traces to 2022, when many leading AI companies were founded while most generalist VCs were managing portfolio damage from the previous era. Distracted by bets in fintech and crypto that had dominated 2020–2021, they failed to recognize the inflection point in AI. Some actively pivoted away. By the time the strategic importance of frontier models became obvious, entry points had closed or valuations had become prohibitive.
Investors who did capitalize moved early and across multiple stages. Elad Gil at Also Capital and Andreessen Horowitz's Anjani Mandyam positioned themselves in winning foundation models and application-layer companies. For multistage platforms, missing seed or Series A rounds mattered less because they could still catch companies in growth rounds. But for pure-play seed and early-stage VCs, the damage is real. Those who didn't invest in at least one winning foundation model, or lack meaningful positions in application-layer companies that leveraged those models, face credibility questions.
The structural irony cuts both ways. VCs had ample warning. The meme that foundation models would commoditize proved wrong. So did the claim that application layers held no value. Yet some investors fell for both narratives simultaneously, avoiding foundation model bets on commoditization fears while also avoiding application bets because they couldn't afford the compute costs or feared fast followers. The result is a portfolio with no frontier AI exposure at any layer.
This creates a signaling problem for the next wave. Founders now scrutinize whether a VC has skin in the game. An investor without OpenAI, Anthropic, Eleven Labs, or comparable positions signals either late-stage capital or absent conviction. The generalist playbook of diversifying across sectors backfired precisely when concentration in one sector mattered most.