Forerunner's Kirsten Green makes the case for consumer AI — and why right now is the moment to build

Summary

Kirsten Green, founder of Forerunner Ventures, is making a deliberate bet that consumer AI is the most underinvested category in the current technology cycle, and she is moving to organize capital and founder attention around that thesis.

Green hosted a consumer AI conference that began six weeks ago as a casual themed happy hour and scaled to a standing-room-only event within weeks. Twenty seed and Series A companies each presented in four-minute slots, co-hosted by a coalition of VC firms Green declined to fully enumerate but described as representing a substantial pool of deployable capital, all explicitly open to consumer AI deals.

The core argument Green is pressing is structural and historical. Every major platform company of the past 25 years — Amazon, Google, Facebook, Apple — built its initial market position through consumer engagement before expanding into multi-dimensional enterprises. Consumer AI today is the analogous entry point, and the window for first-mover positioning is open now, not indefinitely.

The single biggest concern among founders in the room was platform risk from ChatGPT and frontier model operators expanding into adjacent use cases. Green opened the day with that question directly, directing it first at Reid Hoffman and closing with it to Mike Maples of Floodgate. Both independently concluded that large foundation model companies will not, and in some cases cannot, dominate every vertical. The analogy Green used: Google owned search but Zillow, Expedia, and Amazon built durable, large-scale businesses in specialty layers above it. No company, regardless of resources, can optimize every road map simultaneously.

Green pushed back on two investor-side objections. On winner-take-all dynamics, she acknowledged the historical pattern — search, social, and now arguably chat interfaces trend toward concentration — but argued that adjacent and specialty markets consistently produce $10 billion to $20 billion standalone businesses even when a category leader captures the dominant share. On competitive risk from incumbent consumer platforms, her view is that competition is universal across B2B and B2C, and that execution quality, cultural differentiation, and unique insight matter more than category selection.

The consumer AI cohort at YC was notably thin. A company called Text.ai, one of only four consumer companies in its YC batch, presented at Green's event. That ratio reinforced her thesis that capital and founder talent are concentrating in B2B and infrastructure at the expense of the consumer layer, creating an opening.

Timing is the explicit urgency driver. Green argued that the current moment resembles the early phases of the mobile and internet cycles, when category positions were being established before the market had consolidated. The analogy to ChatGPT's own rise is pointed: it was not the first chatbot, just as Google was not the first search engine, but early technical differentiation compounded into dominant distribution. Consumer AI founders building now face a similar dynamic.

On distribution, two case studies surfaced. Lensa, the AI avatar app, generated significant revenue quickly but failed to build durable retention and was subsequently displaced by ChatGPT's image capabilities. Caluude (referenced as "Cluey" in conversation, likely Claude adjacent or the founder Roy Lee's project) was cited as an example of a founder who broke through a noisy ecosystem through attention and distribution savvy, attracting more social conversation on a given day than a $2 billion raise by a competing firm. Green flagged that as a genuine skill set, and one of the hardest to replicate alongside product quality.