Elena Verna: belief

Transcript context

…I'll first start with what I've felt at least before when people were talking about product-market fit, that yeah, obviously always product-market fit is an evolving thing, but the rate of that evolution was measured in years. What is it that you need the next product-market fit step function change, which often was called second horizon or third horizon. Sometimes five, 10 years, sometimes even longer that you'd need, depending on how good and hard your initial product-market fit was, but you'd spend years scaling the original product-market fit. It was like blitz growth stage. Marketing, sales, growth was very important that you just try to get it to as many people as possible. And then once you have saturation or the cost to getting to the marginal people becomes too high, you start thinking, "Okay, what else can I offer to help me reach additional people or sell more to existing users that I already have?" And again, the main point here is it would take years to get to that stage where it became a question that you had to face really hard face-to-face. Now, it's three months, and all of a sudden you have to face that question again. And it's happening because of two things, in my opinion. Number one, in AI technology of what LLM is capable of doing changes still very rapidly with new model release, with each new model release. I think we'll stabilize at some point and then it's going to become more marginal, but we're not there yet. So every three months or so, every single AI LLM provider creates a step function change in what is possible with that LLM. And when you have this new possibility in just an underlying technology that opens up in front of you, then it creates another ceiling of what is possible to build on top of it. The tricky piece here is that it's not enough to just wait for that technology to get better and then start building on top. You have to build beforehand to make a bet and then it's the LLM to catch up because when that model releases, you already need to have that functionality available. That piece is, I've never been in a company where the fundamental capabilities are still changing so rapidly, and that's the product part. The product can leap to the new expectations, but let's not talk about the market part as well. Consumer expectations have never changed this fast before. What we expected ChatGPT to be able to do and answer and how we wanted it to talk to us eight months ago versus now is night and day and the deep thinking mode, and how deeply you can go into answering questions and what is capable of building on top of it. Consumer perception has never changed this fast too. It's this unprecedented time of consumers all of a sudden in a month saying, "Oh, it's not doing this yet. I'm bouncing." Before, again, consumer perceptions would be years to take. It's actually technology would sometimes be able to already address it, but consumer perception has not been changed yet so it would take a long time. ain, consumer perceptions would be years to take. It's actually technology would sometimes be able to already address it, but consumer perception has not been changed yet so it would take a long time. We're in this really weird part where both product and market is shifting so rapidly that every three months, I feel like we have to recapture our product-market fit and not just recapture on the same technology and with same customers. It's both of those pieces of the equation change every three months, and it's terrifying in a way. It's also very confusing in a way because we're $200 million company, and we're not solely focused on marketing and sales because we still have to recapture our product-market fit. You know that the team that finds your product-market fit is very different than the team that usually scales your company, yet we have to find the team that is capable of doing both on ongoing basis. Now, I think every AI company is on this product-market fit treadmill. Hopefully that treadmill speed slows down. If not, I think we're going to come up with crazy things of what this LLM and AI will be able to do if it's going to continue at this cusp, but it's a weird place to be in because every three months we have to throttle on our scaling efforts and just reinvent and then scale again. But it's like short blitz of growth, not these long year long commitments. What makes this very real is just this week, apparently OpenAI had this whole code red moment where even though OpenAI by far the leading AI assistant over almost a billion, I think monthly active users, basically synonymous with AI around the world, with Gemini 3 launching, their market share just started to dip really quickly. I think they lost six something percent in a week. And so even OpenAI, ChatGPT, the original, the one that everyone uses constantly is in danger.…

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