"Taste is learnable through exposure and practice, and in the age of AI slop it will be the primary differentiator between companies — which is exactly why you can't afford to treat it as innate."
"AI pricing is an unsolved problem — it doesn't neatly fit SaaS, seat, or usage models"
Evidence from the Archive
OpenAI / Stripe / Retool
OpenAI's pricing journey from 'we'll ask ChatGPT how to make money' to a working subscription model
ChatGPT's monthly subscription that 'just works' despite not fitting traditional SaaS pricing theory
First marketing hire at both OpenAI and Stripe (sole marketer at Stripe for three years), early marketing leader at Retool and Dropbox, now Executive in Residence at Thrive Capital -- has watched pricing models evolve across multiple paradigm-defining companies. Their core argument: AI pricing is genuinely unsolved -- it will be a 'Wild, Wild West' before the market internalizes a standard the way it did seat-based pricing.
The evidence is specific: OpenAI's pricing journey from 'we'll ask ChatGPT how to make money' to a working subscription model. Furthermore, chatGPT's monthly subscription that 'just works' despite not fitting traditional SaaS pricing theory. Retool's experimentation with self-hosted pricing tiers as an example of iterating toward the right model.
In Krithika Shankarraman's own words: "The reality is it's not a solved problem. And a lot of folks, a lot of companies in the AI domain are trying to figure out the right pricing model. There is a value creation aspect to using AI that doesn't kind of neatly fit the mold of SaaS-based pricing or seed-based pricing, or even usage-based pricing." (On the pricing frontier for AI products.)
Thrive Capital
Thrive runs an internal 'share' Slack channel — things the team has seen in the world that resonated, independent of deal flow — as a live exposure-hours exercise
Krithika Shankarraman, first marketer at Stripe and OpenAI, argues AI-saturated markets make taste more valuable, and that you build it through idiosyncratic inputs
Krithika's view is teachable-side with a distinctive twist: the era of cheap generation makes taste more valuable, which raises the stakes on developing it deliberately. Her frame is that AI will flood every category with drivel, so the companies that distinguish themselves will be the ones that show craft and real understanding of the customer.
She does not treat her own taste as innate. When asked how she developed it, she names practices: pottery, voracious reading, wide exposure to great work, and Thrive's internal 'share' Slack channel where the team posts things they've seen that resonated — independent of deal flow or competitive news. She explicitly endorses Rauch's exposure-hours concept and is trying to operationalize it inside the firm.
In Krithika's own words: "If anything, taste is going to become a distinguishing factor in the age of AI because there's going to be so much drivel that is generated by AI, can be generated by AI, that power is at anyone's fingertips. But truly, the companies that are going to distinguish themselves are the ones that show their craft." (Framing taste as the primary differentiator in an AI-saturated market.)