Lenny's Podcast: Product | Career | Growth
00:14:11 · Amol Avasare, Lenny Rachitsky
[00:14:11] S1: We're just thinking about what can we do to improve the cold start problem and improve the new user experience. I think that activation is a really big challenge in AI. And so that's one example of something that we shipped that was very specific to a moment in time. But ultimately that you zoom out, it's like, okay, how do you really make it easier for people who are signing up to have Claude understand who they are and understand how Claude can help them and get them to the right place? [00:14:43] S0: I want to follow that thread, activation. That's something that comes up a ton when I talk to people leading, driving growth on AI products. It's just there are so much stuff trying to get your attention these days for people to get to a place where they, okay, wow, this is really going to be something I want to keep using. It proves to be really hard. And it's also just unreliable sometimes, it's not going to be magical. It's AI, it's non-deterministic. I guess, one, is just how important is focusing on activation, getting people to that aha moment with AI products? And two, what are some things you've learned about how to do that well with Claude or AI in general?
00:15:19 · Amol Avasare
[00:15:19] S1: Yeah, it's a good question. I think that activation, it's critical and defining that as early activation, call it day zero, day one product experience. I think that historically anyone who's been in growth or been in product understands that that's usually one of the highest levers that you have to actually even increase longer term retention. And I think that the importance of that has just gotten exponentially higher. Now, zooming out, I feel like one of the biggest problems in the industry is capability overhang where the models are just getting better so quickly. And the real challenge is on the product side of how do we start to diffuse those benefits to people where even internally, there's new models coming internally and you're sitting there, you're so busy. And when a new model's available, you need to really carve out time to be like, "What can this do? How do I need to update my priors?" And if you think about more broadly for most people, you may have a model that is like, you may have AGI or some model that can do all sorts of crazy things, but if people's instinct is to come there and be like, "Hey, what's the weather in SF?" Then they're not going to get the most out of the product. And so I think that it's tough because the model capabilities are rising so much. So if I think about, okay, back when we had, I don't know, I want to say Opus 4, there's a series of things the model can do at that point, and Opus 4.5 unlocked a whole bunch of new things. You think about, okay, we sit there, we've got this new model, Opus 4. The time to then go and run a bunch of tests, figure out, okay, there's the capabilities from this new model, what are the right on ramps to guide people to those features? You run tests, you get the learnings, you then ship a new flow. By then, you may already have the next model, which unlocks newer capabilities that makes all these learnings irrelevant. So it's actually just a really difficult problem to stay on top of. I think that many of the same things, same old trends in growth and activation remain, I think, accurate where to me it's like ultimately some of the highest leverages from finding the right product or the right feature for the right user.
00:17:32 · Amol Avasare, Lenny Rachitsky
And I think that one learning, seeing this time and time again across companies, actually the right friction helps and adding more friction usually works if you do it the right way. I think that's something I've consistently seen that we've seen here as well. So to me, I think it's really being able to identify what are the characteristics of a user that allows you to then recommend them to the right feature or product and not being shy about adding friction to do that, I think is probably the single biggest thing that's important here. [00:18:05] S0: When I asked Ben Mann, one of the co-founders, former podcast guest, what to ask you about, and this is what he highlighted, is your experience, especially at Mercury redoing onboarding and making it magical. And basically he's in the same place as you of just how important it is for people to understand what the AI tool is capable of to help people decide to use it and stick with it. Is there an example of something you changed in onboarding that helped significantly improve activation? [00:18:33] S1: Yeah, it's a great question. And I like that it brings up Mercury. I talk about their product a lot. So worked on the growth team at Mercury, I think it's a fantastic product. It's something many people use, and the reason they use it is because the better banking experience than its- [00:18:47] S0: Yeah, I'm a very happy customer just to put that out there. I love it. [00:18:50] S1: It's a great product. Highly recommend it. They have personal banking. Everyone should go and use it.
00:18:50 · Amol Avasare, Lenny Rachitsky
[00:18:50] S1: It's a great product. Highly recommend it. They have personal banking. Everyone should go and use it. [00:18:54] S0: Right. They just launched that.
00:18:57 · Amol Avasare
[00:18:57] S1: And so I think that the interesting thing about Mercury is the core value is that it's a better experience. That's the reason you use it. You're not getting better other things, just it's a better product experience. And so that ethos is very, very deeply held within the company. It comes from a number of the founders. And I think that we had a big push one quarter when I was there on the onboarding flow. So onboarding flows for banking institutions and regulated entities are extremely complex. The amount of time I've spent on the difference between a registered agent address and a legal address and a physical address, these things are very, very complex. And we basically looked at the onboarding flow and we were like, okay, we've invested so much in quality and the rest of the product, but we haven't really done it here. And this is the first experience that people have. And so we said, forget metrics, forget growth, forget everything else. As the growth team on conversion, we're going to spend a whole quarter fixing quality in this flow. And so that's all we did. Forget the metrics. We're just going to make this as good of an experience as we can and fix all these. You go back from one field to the other field and adding in your beneficial ownership details. And it actually ended up being, and probably until I joined here, the single most impactful quarter that I've ever had as a growth PM in terms of the impact that it had. And so we saw a significant uplift on basically our onboarding started to completion from just focusing on quality. And so that to me is a broader learning around quality drives growth that I think I've tried to bring to Anthropic. I think for us at Anthropic, some of the things that we've done in the onboarding flow is basically we ask users questions around who they are, what their interest areas are. And we then use that to recommend different products and features. And number of people look at the flow and they're like, "You have so much friction. It's such a long flow." And I'm like, "We have the data. We're kind of happy with how that's performing."
00:20:57 · Lenny Rachitsky
[00:20:57] S0: What is your kind of philosophy on good friction versus bad friction?