Founders in Arms
00:41:13 · Rajat Suri, Immad Akhund, Jean-Denis Greze
[00:41:13] S1: Right. But how do you know if you're building the right product? [00:41:19] S0: I mean, there's a reason humans still have jobs. I do I do think that, like, if you think about the product development life cycle from, like, come up with an idea, you know, or maybe even before that, like, talk to talk to customers, figure out what's the idea, figure out, you know, how are you gonna build it, what's in scope. Yeah. The actual, like, engineering part was the expensive part previously. Right? Like, you've spent maybe 80% of your time on the actual, like, coding, and now that's maybe, you know, 20% of the time. So, yeah, I think the rest gets more important. There are things that help with AI. Well, AI helps with the rest of it. You know, you can look at all your support tickets and, like, summarize it better. Maybe you can plug that screen into kind of linear, and then, yeah, I can have a go at, like, trying to do a prototype or something like that. So there are, like, things that are speeding up our process, but it's definitely not uniform. And, yeah, what we think about it, I guess, everyone's thinking about it. So, you know, what is the next biggest thing that you can credit with these 90% of the new coupon? Kinda squeeze all the bottlenecks. But it's not... I don't... Like, there's a magic answer to it necessarily. I think one thing that I think is important is that engineers do more and more of those other tasks. So, like, previously, because coding did 80% of [00:42:42] S2: the time, you would want
00:42:42 · Jean-Denis Greze, Immad Akhund
[00:42:42] S2: the time, you would want [00:42:44] S0: an engineer to be kinda distracted by some of those other things. And now, like, you know, that's the small percentage you want
00:42:51 · Jean-Denis Greze
[00:42:51] S2: the engineer to be kind of full stack across the in the life cycle. Yeah. I think... By the way, another answer for... That we are seeing more and more is that it's difficult for users to discover features in these products because the products can do more and more and more. And whether the features are just like, hey, if you write the magic words in the box, it'll do this thing that you didn't think it could do before, Or the feature is, like, in a menu somewhere. And so, like, the the odd the odd thing for me is, like, hey, it might actually... You you may not want unlimited features. And even being better maybe listening and understanding the full range of features is not is not that helpful because humans that are clicking on things are still kind of more limited in what they can click on. So, like, my mental model is if it's a headless feature and I can use existing incantations and make sure they happen, then you kinda almost don't wanna ask the question if it's the right feature because it's headless. You wanna get it in your product, and you want to let the AI decide whether it's useful. And and if you think that way, and your heart is as good as discovering that there's a problem and this new feature solves the problem, it doesn't matter how sloppy or bad the feature is in a way because you're gonna recognize from product analytics that there's demand for it, and then you can iterate and make it better and better. And then for the rest, there are things that humans interact with directly. Then I think taste matters almost more because everyone's like slopifying left and right. You know? It like naturally slops because you can build more things. And so I think if you're very tasteful and thoughtful about what is your strategy that gives you competitive advantage, like what is what is the set of things that if you had, your your users would be super happy, and then you build those in a delightful way. It's all taste. Right? Because it's a human that's judging whether it's useful. There, I think it's not that different than it it was before.
00:44:47 · Rajat Suri
[00:44:47] S1: Yeah. I totally agree. I think, you know, we're building a next generation group chat app at Prive, and and we're we're primarily human driven product. So what I learned the most by talking to users, and and, you know, I I try to do regular calls with them and and hear their feedback, and then they always have something interesting to say about, you know... And and clearly developing just more features is not solving the problem in many cases. The bottleneck is the human brain. It's like, how much can a human brain absorb at any given time? And they can only absorb so much. Right? So you never wanna be too new in a consumer product. You have to have some precedence installed in your product so people know how to use some stuff. But humans like something new. They don't like everything the same. So you have to insert the newness in a way that's delightful and and gives them the feeling, hey. This is cool. This is something I haven't seen before. But if it's too new, they'll turn off as well. So, you know, getting that that balance right is always tough. And then, you know, you have to make sure you're solving a real problem for them as well. And and that, I think, only comes from... You know, in business, you can talk to the businesses, and they'll tell you the problems. And I do think, you know, we're so early on AI. Like, there's just so much... You know, we're probably... The whole world is, like, 1% penetrated or 2% in in how it's like... There's so much upside even in developing the same thing that's working, you know, here in Silicon Valley and and getting it out there and just having a good great go to market strategy and great brand and great services and great support. Alright.
00:46:18 · Immad Akhund, Jean-Denis Greze
[00:46:18] S0: Yeah. We should go to the next question. I have one other interesting thing to add. I think, like, good... Well, some good AI actually collapses the features that are required. So I'll walk you through an example. Right? Like, bill pay is, like, quite a complicated feature. Like, you you can use some create new... You know, upload an invoice, and then you can go through it and say, like, oh, this account number matches. This right number matches. Like, it's a really nice UI. You can imagine in the future, right, I just CC an agent, and I never even see the bill. Like, I just approve it right at the end. And, like, you've actually collapsed, like, a bunch of features that are, like, currently Bill Pay has. So I think, like, you can use AI to solve things like, like, an abstraction above Yeah. Which can simplify, like, features and [00:47:03] S2: remove software. We got... That... That's true today. Yeah. Like, this this week, I did a bunch of that, including signing NDAs. There was my agent taking my signature, putting it in. I took all my expenses. But I literally said, from my last three trips, find every expense and put them in in, you know, in my bank software and go with it. And it just it just does all that. You know, you're you're already... You're... This is already, like, the the normal. And it doesn't matter that in the app, was a 100 buttons or five buttons. The buttons were clicked. The expenses were filed. Right? The bank account and account routing number were added. [00:47:41] S0: Yeah. Alright. Let's go to that.
00:47:41 · Immad Akhund, Rajat Suri, Jean-Denis Greze
[00:47:41] S0: Yeah. Alright. Let's go to that. [00:47:44] S1: It feels worse than you've already seen. Mercury beats Silicon Valley Bank on software, disrupted that business. What company would you name today that you worry the most about doing the same to you, disrupting your business? Do you think your bank license will be a moat against disruption? [00:47:59] S0: Okay. So the question was, we beat SVB and, I guess, other banks by building amazing software. What am I most worried about and whether a banking license will be remote. I think the main thing I worry about is, like, you know, are we doing things good for customers? Are we still innovative? And, like, you know, have we built a good company culture and all that kind of stuff? I think as companies scale, like, those things tend to erode over time. I think if we can hold that bar, we obviously have all the advantages that we didn't have when we were tiny, and now we have a team of customers and and a product. So, yeah, I'm not, like, super worried about disruption. I'm I'm mostly worried about, like, making sure we're gonna still building a company that, like, I would enjoy working at. You know? And if that point got to the core of your question, but let's keep going. Yeah. I'm curious about [00:49:00] S1: the case. I wanna go back to it when you're, [00:49:02] S2: say, trying to find the right people who will hire, and everybody's using AI tools. But does... Can AI identify case? Like, how do you filter out the right people if AI is not good at case? Like