A Product Market Fit Show | Startup Podcast for Founders
00:38:41 · Chaz Englander, Pablo Srugo
[00:38:41] S0: it? A small adviser. It's a small investment bank. They came on as a design partner along with another firm quite quickly, and I think that's the way to go. So I would say as a playbook for b to b companies, you almost can't overestimate what a good design partner can do to speed up your iteration cycle. And I think, you know, something that Arne and I have learned, if I would say there's like a couple of things that are in the founder playbook in our head is like perseverance is definitely one, but another thing is just the speed at which you can learn. Like I don't just mean as an individual, I actually kind of mean about your customers, right? And how you can translate that to the product. So you know, when I speak to people, if you've got a design partner that you're speaking to once a week, you're almost certainly gonna fail. Right? If you've got a design partner that you are working from their office and ideally sat next to them, you're almost certainly going to succeed. In in a in a world, by the way, where there's no kind of barrier to entry when it comes to like writing code or or technology in general. [00:39:43] S1: It's funny you mentioned that, like, Legora, which we just had on, you know, became, I think, took a 1,800,000,000 company in in two years. Exactly like that. Right? Like, was in the office with the law firm for the design partner phase. And a huge change in that speed of put something out, get some feedback, the nuances, the qualitative stuff, like you just...
00:39:43 · Pablo Srugo, Chaz Englander
[00:39:43] S1: It's funny you mentioned that, like, Legora, which we just had on, you know, became, I think, took a 1,800,000,000 company in in two years. Exactly like that. Right? Like, was in the office with the law firm for the design partner phase. And a huge change in that speed of put something out, get some feedback, the nuances, the qualitative stuff, like you just... [00:40:00] S0: Yeah. If people hadn't... I I assume... I don't know who that was, but if it was Max, Max is a... Yes. Max is an absolute genius. [00:40:07] S1: Yeah he's a G. He's an absolute G. [00:40:09] S0: I think the way, and again Max, you know I think the way that a lot of these AI application companies, their themes as to how they've gone from you know zero to one and beyond, they are very very similar. You know, I think the design partnership phase is is mission critical, the speed of iteration is mission critical, I think the work ethic is also super important, particularly when the market gets validated. You know, if you think about that really your only tools, the speed at which you share product and the speed at which you iterate, you know, that's really it. That's like kind of the... Your only competitive advantage, be honest. [00:40:45] S1: So I'm assuming you worked from the office of this design partner? Yeah. And were they a paid partner? Like, how did you structure that, and how did you... Did you make sure that they were gonna give you x amount of time a day, or was it just like a friendly relationship? Like, what's the structure?
00:40:59 · Chaz Englander
[00:40:59] S0: So really good question. I would say as well, I don't think there's like a right or a wrong and I also appreciate that everything I'm about to say is in an idle world and founders ultimately just have to play the cards that they have in front of them, but if they could choose, I think that paying is nice, but it's only a way to validate one very important thing which is how serious they are about what it is that you are doing. Now the reason I said that kind of caveat beforehand is that ultimately, if you're just doing anything to get a design partner, you'll take anything. And learning something is better than learning nothing. But in an idle world, you would get that individual or company invested in the company. And we did that by the way. So this company invested in the company. And the reason is because you get that additional level of buying. Now given some verticals that may not be possible, but you definitely wanna make sure that from the very very top, the person that's actually making the decisions of the firm, they are 100% bought in. You've also gotta be mindful of like a lot of people, lot of CEOs, particularly, you know, particularly if they've made money, they can be quite flighty, in other words they get excited about all sorts of things. And so really test whether this is like absolute buy in, but you can also make a mistake. You might choose one, it might not work, it can move on to another, but it's just the speed that you go through that. But when you find one that's willing to give you really, really, really good feedback and that can help you iterate and enable you to focus in the way that you want to, yeah, you just build, build, build as quickly as you can.
00:42:36 · Pablo Srugo
[00:42:36] S1: It's hard to know and appreciate the difference between having that qualitative advice all the time and what that could do to product before and after you've actually done it. But can you share, do you remember anything specific that they said or even just an outcome of the fact that you had this where it's like, we would not have built this thing this way if it wasn't for them. And as a result, you know, the the product market fit was so much stronger. Like, do you have any of those kind of examples you could share?
00:43:01 · Chaz Englander, Pablo Srugo
[00:43:01] S0: I don't exactly, but what I do remember is, particularly in the AI world because these demos can be so good, so... A demo kinda counts for nothing. Like, real feedback is not when you are showing the user the product or what they can do. Real feedback is where they are using it and ideally by themselves. Right? You know, because people naturally in front of people, they smile particularly I think in Europe, like there's this culture of like everyone says everything is great when in fact it might be awful. I think in The US they're way better for just saying how it is a long time. So that's what you wanna monitor. And by the way, that may also not be in what they say, it may be in the data as well. Right? So like, you know, I would say that really really pay attention to actually how much they're using the product because like usage just doesn't lie. It's... You know, how amount of times you would hear a user say this is great, you know, having to ask for the first like three months but they're not using it. Well, clearly not great if they're not [00:44:03] S1: using it. You know what I mean? Like what were you waiting for? When did you know when it was ready to launch? Like what was that trigger? And then how did you structure the actual like launch beyond design partners?
00:44:13 · Chaz Englander
[00:44:13] S0: In true kind of Y Combinator fashion, we just like, soon as we even had close to a product, we were like launched and we were going out and doing as much as we could. I think we made a bet with you know, in the way that we were thinking about it, that was given the procurement cycles of our industry, know, six, nine, twelve months at a minimum type numbers, We knew how quickly the product was gonna evolve, so we almost had to sell like three, six months in advance. Because if we were selling what we had today, you know, we were never gonna get ahead. But there was this point where it's so hard to describe it as that tipping point of product market fit. People start using the product by themselves, you know, getting people to pay was less of a pain, know, people would pay and then you would never really speak to them and they would just continue using the product and it starts to happen. But when that happens, you gotta turn the tap on. You gotta put the running spikes on and you gotta be prepared for almost no sleep. Mean, as I mentioned, you know, before like first year we were nine ninety seven, whole year, every waking hour frankly. Because it was a it was a big TAM, we knew that, and we knew it was gonna be competitive, and we also knew, and I think the League of AI space is a great example of this, you know, you mentioned Legora, is that once you hit escape velocity in a market like this, it's very, very, very difficult for anyone else to then join that group. Right? And basically I use escape velocity with a very clear definite... Definition. You know, escape velocity is where, you know, twelve months or so ago, it was a risk to use ModelML. I now think in some markets, it's a risk to not use Model ML. That's escape velocity. And and I think, like, when you get in that pack, you know, it's very difficult now for other folks to join, and it's exactly what happened in the lead AI market just by the fact that you're compounding, You raise more money, you can build more product.