He sold his first 2 startups. His 3rd grew to $1M ARR in 3 months. | Chaz Englander, Founder of Model ML

Chaz Englander (00:00:00) :
No one should ever say they're raising money and so far they've raised zero.

Pablo Srugo (00:00:04) :
Yes.

Chaz Englander (00:00:05) :
It sounds obvious, but I would advise not to do that ever. No matter what, if you are raising, the round's pretty much already done. That's the narrative, another thing as well is product market fit is not necessarily static as well, I think, particularly now in the AI world. You might have PMF today, but you don't necessarily have it when you wake up. I say that, I mean, a year ago, Vibe Coding was great for prototyping. I mean, now I think it's great for production. In terms of MVPs, the concept of saying I don't have technical resources to build an MVP is just not true. We went from about $5K in monthly revenue to about $100K in three months. 

Pablo Srugo (00:00:43) :
Wow.

Chaz Englander (00:00:44) :
And then we kind of did that again in the next three months. 

Previous Guests (00:00:50) :
That's product market fit. Product market fit. Product market fit. I called it the product market fit question. Product market fit. Product market fit. Product market fit. Product market fit. I mean, the name of the show is Product market fit.

Pablo Srugo (00:01:03) :
Do you think the Product market fit show, has Product market fit? Because if you do, then there's something you just have to do. You have to take out your phone. You have to leave the show five stars. It lets us reach more founders and it lets us get better guests, thank you. Chaz, welcome to the show, man. It's great to have you on.

Chaz Englander (00:01:20) :
Awe, man. Thanks for having me.

Pablo Srugo (00:01:21) :
I'm excited for this one because, you know, one of the things about startups is regardless of how kind of big they get. You never know how much is skill, how much is luck. but, you know, you look at your background. You've got the first company you started was acquired for like over $40 million. The second company was acquired for much more than that and the third company, which is the one we're talking about today, Model ML. Is off to a start faster than those other two, just raised $75 million. So it's on the right track. So I think there's some magic, some serious skill set to be uncovered here today.

Chaz Englander (00:01:51) :
Yeah, I mean, I'm not sure but we'll see.

Pablo Srugo (00:01:54) :
I don't expect you to say anything other than humility after that, but I think anybody looking from the outside says, OK, there's got to be something going on here. So that's what we're going to try and pull out today. Maybe let's start with a little bit of background, right? But more than anything, tell us about, you know, the first company Fat Llama started in 2016. What was happening in 2015, just before? What was the origin story? And we'll get into that story and kind of go from there.

Chaz Englander (00:02:15) :
Yeah, so I suppose like a lot of founders, right? I was, you know, young. I was like obsessed with things, not YC. I was obsessed with the concept of building a company. I was definitely in that phase of just trying to figure out an idea in my head that I wanted to do, right? So that's kind of where it started, and I kind of stumbled across. We did this concept of lending out items to people nearby, and we just, jumped in with two feet. You know, self taught and just got cracking. And did everything wrong as well, I should say.

Pablo Srugo (00:02:49) :
Where was this by the way? Where we based?

Chaz Englander (00:02:50) :
In London. So at this point, I was in London. Anz, my brother, I built a company with as well, he was in London. We did end up, so that company, so we got on YC, which in many respects in 2016. That was very much the heyday, and that was a breakthrough for us really. You know, we were put on a map as people from England just wanting to build a software business, to be honest.

Pablo Srugo (00:03:12) :
Things have globalized a lot more lately, but, you know, the Bay Area obviously is still kind of the center of all things tech and for me. When I started Gymtrack in 2013, similar vintage, we got into 500 Startups, also in SF and it was, night and day, before and after being from Ottawa. Which is a, you know, small town, much smaller than, much less important globally than London, but still from the tech perspective. These are not first tier cities in either case, certainly not back then, at least and so I can imagine kind of what that would have done to you. How you look at yourself and how everybody else looked at you back home.

Chaz Englander (00:03:42) :
For sure, for sure and, we didn't take any of it for granted either. That definitely made our journey easier, for sure. I mean, for what we needed to do, we needed to raise a bit of money, you know, made a lot of those things easier. I'd say that one of the things that we don't talk about enough was, you know, between starting and getting on YC. We raised a million pounds and that was like straight scrappiness. I remember we actually raised two rounds, a hundred thousand pound round and then a million pound round. And that first hundred thousand pound round, I figured out that it was just like a numbers game. I was like, look, to go at this full time, I'm happy to. I was living off like, you know, thirteen hundred pounds a month. I was like, to go this full time, I'm just going to need to scrap and it's going to be a numbers game. So I kind of figured I was like, look, where is money in London? It's a lot of it is like financial services centric. You know, a lot of those companies are based in Canary Wharf down there. I'm just going to go down there and I'm just going to hit people up on LinkedIn. I mean, looking back on it. I was like pitching for like a grand at a time, genuinely.

Pablo Srugo (00:04:45) :
No way.

Chaz Englander (00:04:46) :
Two grand here and there. And I do like ten pitches of this, to everyone else is a ridiculous idea as well. I was like, yeah, you're going to lend out your items to people nearby, and you're going to be okay with that, strangers, you know? So I'd do ten pitches and pick up a couple of grand here and there but the numbers added up, and then we got to a hundred grand. And then before you know it, we were in a position where I could leave my other job and go out full time.

Pablo Srugo (00:05:10) :
This is an interesting tangent to go down. Because obviously raising the first round is always a big deal, and, you know, once you have a track record and stuff. Frankly, it gets a lot easier but when you don't, like in that time, it is not easy at all. How did you even get those, you know, ten meetings a day? You got to get ten meetings a day. It's one thing to do them, it's hard work, but getting them is like a dark side sort of thing. How did you get those meetings every day and kind of have that volume?

Chaz Englander (00:05:31) :
Well, I should say, before explaining that as well, right? I do think the playbook in the context of AI has changed drastically. I'll park that a little bit, we can come back to that. But to answer your question, I really believe that first round, as a first time founder. If that's something you even need to do anymore, right? These really small rounds that used to happen a lot more, it's a numbers game. It's a pure numbers game and for a whole bunch of reasons, you need to learn how to pitch. The only way to learn is to fail and fail quickly. So I was, you know, hitting people up on LinkedIn and maxing my messages, and ads every single day, right? Every day and the thing is, the conversion rate would be tiny, right? You'd probably have to connect with a hundred and then maybe message all hundred and get ten responses to maybe get one meeting, but it compounds. So I think the thing that I thought, looking back on it, was really useful is although that overall, let's call it a million pounds if that's what it was, I can't remember exactly, probably only five to ten percent of that came direct from those LinkedIn messages I was sending. The other ninety percent was indirectly, almost entirely through that, right? Because at the end of the day, if you're meeting one person, you're not meeting just them. You're meeting everyone else that they know and I always said that to myself. And that's how I ended up compounding. We had one or two quite lucky intros. Well, I say lucky, it was a numbers game. So maybe it was just statistical significance. I don't know.

Pablo Srugo (00:06:55) :
Did you do the comment, especially that early on. Oh, I'm a student, wouldn't want your advice, et cetera, et cetera? Was it very direct, like, hey, I'm fundraising?

Chaz Englander (00:07:02) :
I was very direct, you know, I think in that first message. A big part of it is credibility. So I think like, how can you, in that first three or four words, get some level of credibility? Is it a name drop? Maybe it's where you studied, if you studied somewhere, great.

Pablo Srugo (00:07:18) :
Do you remember what you did? What was your kind of credibility tagline?

Chaz Englander (00:07:21) :
There was a couple of people that I approached, and I asked whether they would be advisors. So I was like, hey, can you just help me out? And they themselves were quite reputable. I think in the first line, I said something along the lines of like, hey, I've started this new company, already got advisors from, Airbnb and whatever, and Uber, you know, this is what we do. Keen to chat, you know. No one should ever, say they're raising money and so far they've raised zero.

Pablo Srugo (00:07:51) :
Yes.

Chaz Englander (00:07:53) :
It sounds obvious but like I would advise not to do that ever, right? In other words no matter what, if you are raising the rounds pretty much already done. That's the narrative.

Pablo Srugo (00:08:05) :
Yes, yes.

Chaz Englander (00:08:06) :
I'll explain the reality of this, but no one wants to be that first check. So that first check is going to come from an ally or someone that you know, right? And so they're the ones going to take the leap of faith. But yeah, you always want to be on the tail end.

Pablo Srugo (00:08:19) :
I actually did it by accident because we thought we needed only like $200k, and then we thought we needed only $500k. But the effect of it was we were almost done because it was like, oh, we got $100k out of $200, or fifty percent and then we're like, you know, we're going to need more money. Well, you know what? We got $300k out of $500k and so you always got that momentum going.

Chaz Englander (00:08:36) :
That's what people should do is whatever their first check is in the round, just say your total round is that plus like twenty percent.

Pablo Srugo (00:08:44) :
Yes and the other thing you mentioned there that I think is really important is, you know, bootstrapping is known as, you don't raise any money. But I think there's an element in bootstrapping, whether you go VC or not, which is how do you do the little thing. You have this goal of raising a million, and you're like, that seems insurmountable. OK, well, maybe raising a $100K is easier to this point. Maybe raising any money is too hard, but maybe getting an advisor is not that hard and then getting an advisor can lead to those meetings, can lead to the. So it's like boot, these little things that then get you to that big thing, right? You got to break it down.

Chaz Englander (00:09:13) :
Everything compounds, first of all. So everything seems like a really steep hill, right? But it's like anything, you know, to get to your first, I don't know, even $100k in ARR. When your first time might seem huge, but when you're there. To get to a million, maybe doesn't seem that far, you know? And I think like anything, it's these little concepts. I think the big thing is consistency and the second thing, we mentioned it. Anz and I, when we did this YC interview, that's on YouTube, around perseverance. So, I think there is a big difference between blind perseverance. But if something makes sense, and, you know, it makes sense, and you're not kidding yourself. I mean, you just got to go out there with all guns blazing.

Pablo Srugo (00:09:55) :
It's this weird balance because on the one hand, I've seen a lot of people spend a lot of time on something that's just probably never going to work, and then ultimately doesn't work. And they're like, wow, I wish I made a huge change way earlier. But on the other hand, even the ones that are successful had to go through a lot of shit until they saw that success. So you've got to figure out if the thing you're going after is real somehow. But even if it is, unless you get really lucky, it's not just going to be up and to the right. You're going to go eat a lot of shit to get there.

Chaz Englander (00:10:23) :
An easy sort of cheat code there is, again, slightly different now than AI but, if you have no competition, and you've never had any competition. It's like you still have no competition. You probably don't have anything that people want, right? And I think, it's astounding to me, but I say it's astounding. I mean, I was the same. It's like you have this inherent fear of competition, I think, particularly as a first time founder. It's like you see competition, big company or small company, by the way, building what you're building and there's just this anxiety that builds up inside you, right? You're like, it's over, right? I think that what you realize second and third time is, that is exactly what you need. Because there's just more and more folks validating your concept, right? And if you validated your concept, then all you need to do is execute better and it's way easier to execute better than it is to find a concept that works.

Pablo Srugo (00:11:19) :
So going back to the storyline for Fat Llama. I mean, you get into YC, YC will make fundraising a lot easier, but it doesn't make finding product market fit easier. And this is not an easy path that you've chosen around lending, like lending marketplace. What's that story?

Chaz Englander (00:11:34) :
So interestingly, our first two companies were both consumer. Fat Llama took probably three years to find product market fit. Fancy that we sold to Gopuff, you know, was like day one, day zero, right? So very different stories, and we've seen them both from different lenses. And so come back to this point of perseverance. We knew deep down that what we were building, people wanted. What we didn't know was whether we could do that in a way where the unit economics adds up and I think that's hard, right? Because often as founders, you're like, well, yeah, but when we scale up, people will know who we are, and we won't have this cack or whatever it is. And there's always this in the future type thing. That's a really hard spot to be in but again, we kind of persevered on the basis that we knew people wanted this, and that was true, and we did scale, and we raised. We got on YC, raised a $12 million Series A pretty quickly after that. But it took us a good year or so after our Series A for the unit economics to add up, but we kind of knew we needed to persevere.

Pablo Srugo (00:12:36) :
How many like cities did you end up kind of scaling to?

Chaz Englander (00:12:39) :
So it was less so the geographical expansion for us. It was more the category expansion that was like a bit of a thing that we really needed to think about. So our product, it was very simple. You lend out a camera, some gardening equipment, a set of DJ decks, a guitar to someone nearby, and we take commission. It's a marketplace, that was it, you'd be insured. That was like the thing that we ended up somewhat mastering in a scrappy way to start with, for sure and so I think that what we didn't know was we knew how big it was in, say, film photography as a category. But we didn't know, A, how big it was and how we could get into other markets. Using the same way that we did before and so what happened was it was just very unpredictable in that sense. Because it wasn't like we had one thing that we just knew we could scale geographically. We had this concept of category scaling and geographical scaling. That was difficult.

Pablo Srugo (00:13:31) :
How big did it get, revenue-wise? More or less, by the time you sold it?

Chaz Englander (00:13:35) :
I think when we sold it, it was about, I might be speaking out of turn here. Just under a million a month in GMB, like there or thereabouts. So big as in like Series B big? Well, no. Series A big, yeah, it was good. But also it was kicking out cash. So another thing as well, we hit product market fit, and the business was cash flow positive. So that was fun, but we didn't really, it was harder to then grow from that. Another thing as well is like product market fit is not necessarily static as well. I think, particularly now in the AI world.

Pablo Srugo (00:14:07) :
Yes.

Chaz Englander (00:14:07) :
You might have PMF today, but you don't necessarily have it when you wake up.

Pablo Srugo (00:14:10) :
Well, and the easy answer to that. I mean, the market's always changing. So if the market changes, the PMF you might have had no longer is true.

Chaz Englander (00:14:17) :
Yeah, yeah, exactly, exactly.

Pablo Srugo (00:14:19) :
Tell me the story. I mean, selling companies is not ever easy and not linear. How did it happen for you at Fat Llama? Who bought it and why? Kind of what's that story?

Chaz Englander (00:14:27) :
So not many people know this, right? But we, pre acquisition, spent six to nine months exploring a SPAC. Where we were going to, with a bunch of other companies, take the company public. We were kind of the lead company in that, not because I think we were the biggest but more because we had a good brand.

Pablo Srugo (00:14:48) :
And this was the SPAC post COVID era, like late 2020-ish?

Chaz Englander (00:14:52) :
Yeah, earlier than that but this is when I think the news online is late, but it was pre that. But that was hard. I think, you know, we spent over half a million in legal fees and, nine months of work. Me in the middle of the night, all the time with my laptop on my knees, two, three weeks before Christmas. The whole thing just fell out of bed and, I think as a first time founder. What was the hardest then was picking up the phones, the shareholders, and being like, look, I made a call. We went in this direction, and I fucked it up. It wasn't that we made any mistakes. I think it was just that as founders, you know, and, shareholders back you to go in a certain direction. I found that tough.

Pablo Srugo (00:15:36) :
And was that harder for you. Especially at that age, than the money you probably assumed you would make if it happened? Was that top of mind for you, or even back then it wasn't?

Chaz Englander (00:15:46) :
No, honestly, no. I feel Arnie and I, in the grand scheme of things. Have never really been, to an extent, that motivated by money and even if you are, it really does get boring quick. And, you realize that having a purpose and kind of a sense of fulfillment every day is just. Is harder to find first of all and is way more important. It was really just that feeling of letting people down and, Oh, I, you know, worked my ass off, and we did everything correct, and everyone would have made the same decision even looking back on it. I think as a founder, particularly as a first time founder during that journey, you just put so much weight on your shoulders, right? And it's difficult to then be like, yeah, I fucked up.

Pablo Srugo (00:16:31) :
How did you go from there to exiting?

Chaz Englander (00:16:33) :
Well, that was almost maybe the perfect turnaround. I won't go into too many details of who called me and when in terms of mentioning them by name but I was in a seaside town in England. And I got this call from this Swedish number, and I ignored it, and they kept calling me and calling me and calling me. I think, looking back on it, what happened was they were interested in acquiring us and knew that this spark was going on. And so the second that they heard it fell through, my phone was blowing up. And it was a much, much better outcome. I mean, I don't want to talk financially and that sort of confidentiality to everyone involved. But it really was, for our customers, shareholders, us personally, it was a better outcome and, you know, the business now is in great hands, doing great things.

Pablo Srugo (00:17:22) :
Oh so it's still operating like, this lending marketplace still exists?

Chaz Englander (00:17:25) :
It's funny, it only just, as in the last couple weeks in the UK, which is where the bulk of the business was, got rebranded to this new business. But even today, I was in this, we did some photo shoot for something at the business and all the equipment the person was renting there was rented through Fat Llama. Which feels good and also the amazing thing about our business is like it's a really rewarding story, right? Because what it did to so many creatives was unlock their ability to have that passion full time. I mean, I genuinely, there's probably hundreds of thousands of people that that business changed people's lives for the better. Which I've never met them, right? And that's why it was such a great business, I think, in the end, to be involved with and still involved.

Pablo Srugo (00:18:09) :
When did you sell that and then when did you start your next company, Fancy?

Chaz Englander (00:18:14) :
So 2019, and then end of 2019, Anz and I. My brother and I, we kind of just thought it'd be cool if you called up groceries on your phone. I wouldn't necessarily say there was more to it than that. We were like, wanted to build something. We thought that would be cool and just polar opposite to the first business. We launched with, to call it an MVP was an overstatement. It was almost like a WhatsApp group. It was so bad of an app. So it was a native app.

Pablo Srugo (00:18:43) :
And what city did you choose to launch in?

Chaz Englander (00:18:46) :
Newcastle, again, a bit of a fluky part to the whole story. So Anz was CEO, and we decided to launch in Newcastle. One reason, Newcastle, for the listeners. Whether they know or not, is a tiny little town. Actually, people from Newcastle would probably get upset about that. It's a town in the far northeast of England. That is an amazing town or city, but quite small. It's a bit of a university town as well and yeah, we launched up there. So it was very much a case of coding during the day, and then would kind of open up mainly in the evening is, when the orders came in. So from six onwards, deliver orders until midnight.

Pablo Srugo (00:19:23) :
Did you guys do the first deliveries? Did you partner with someone right away?

Chaz Englander (00:19:27) :
The team, as in the founding team, did the first, fourteen hundred deliveries. We didn't know this at the time, but one of the things that Arnie always says is that was so amazing. Obviously, if you're doing the deliveries, you're getting the most real time user feedback that you can possibly get. Because you're literally meeting every single user every time they make an order in person. So it's almost like you have customer interviews for every order. Which helps us iterate and build so much quicker. But yeah, the model was originally, you know, obviously we're a vertically integrated, right? In other words, it was, we had the warehouse, we had the stock, etc., but we didn't have anything beyond the app. So we would get orders, we would go down to the corner shop, we were buying, cigarettes and vodka, and then delivering.

Pablo Srugo (00:20:22) :
And you would pay yourself, and then get paid later? You didn't have a partnership with the stores where you're buying stuff?

Chaz Englander (00:20:27) :
No way. Yeah, there was just, we had nothing. But this is the thing, right? We learned from the first business. We were like, we literally said to ourselves, and also I think it was Michael Seibel, as in YC. Michael Seibel, he said to me, a proper MVP is like, it is a WhatsApp group and that's the way that you should think about it. We applied this and we were like, look, we're not going to spend any money. We're not going to do anything. We're going to write code, right? We're going to stand outside the student halls or whatever. We're going to hand out some flyers. We're going to get an order. There's no back end, by the way, right? So there's a text message that we got the order, right? That we hooked up to Twilio and everybody's going to go to the shop. We're going to buy it, and we're going to take it to them. And if they order again, the unit economics add up, then great. But that's not how it started. But it just grew quickly. Pre-COVID, right? So we quickly got to, like, hundreds and then thousands of orders a day with no marketing, right? So it was purely a referral based thing and sticky and just so different to the first company.

Pablo Srugo (00:21:26) :
I'm going to ask you for a small favor, a tiny little favor. In fact, it's not even, now that I think about it. It's not even really a favor for me. I'm actually trying to help you do a favor for you. Just hit the follow button. You won't miss out on the next episode. You'll see everything that we release. If you don't want to listen to an episode, you just skip it. But at least you don't miss out. And you mentioned the competitive landscape earlier, was Gopuff already doing this in the US? Did you get inspired by others doing it in different cities, and you brought it to Newcastle?

Chaz Englander (00:21:56) :
So no, GoPuff already existed in the US. We didn't know them because they were in stealth mode, really. So there was no, press about them or anything. They were still in stealth mode at that point. They were doing pretty well in the US. We launched in Newcastle again for just a small town, easy to get around.

Pablo Srugo (00:22:11) :
So it wasn't like you saw somebody doing it in a different market and you brought it to the UK market?

Chaz Englander (00:22:15) :
No, and I think in that respect, it was just lucky. I think it was just like, hey, we think this is kind of cool. As a concept, would you want this? Yeah, okay, well, let's just build it and by the way. Now with AI as well, I said to someone the other day. Our MVP probably took a month to build. Again, no back end, it was just an app that you could choose from a selection of maybe thirty different items. Also, I remember we literally hooked up the items database to a Google Sheet and even the image of the item was being pulled from an image URL on the Google Sheet. So we weren't even hosting the images, it was just some random image online. It was a real piece of, you know what. I don't think we had payments in the beginning, people paying cash. It was just boom, you order, we got a text message, and that was it.

Pablo Srugo (00:23:00) :
It's the ultimate test of product market fit and it's not so much if you can give them a shitty product, they'll still use it. It's just like, do they care about the optimization piece and the bells, and whistles. Or do they just want the thing, right? In that case, they just want deliver, like, groceries delivered and, yeah, if the thing doesn't look that good and it doesn't work perfectly. That's fine, because I'm still getting my groceries delivered and that proves the core thing.

Chaz Englander (00:23:22) :
Exactly but sorry, the point I was going to make there was that MVP in today's world would take a day.

Pablo Srugo (00:23:27) :
Right.

Chaz Englander (00:23:28) :
And so I think that says to a couple of things. I think it's like that thing I mentioned around competition. So, you know, ultimately, if there is no competition, and there's no competition for a while, you probably don't have a market. And the other thing is just, you should be able to validate concepts far quicker. Yeah, I mean, a year ago, vibe coding was great for prototyping. I mean, now I think it's great for production. So in terms of MVP, the concept of saying I don't have technical resources to build an MVP is just not true.

Pablo Srugo (00:23:58) :
Yeah, no, it's a hundred percent gone. It makes that experimentation piece so much faster and it's interesting. Because I think a lot of the, especially for the technical founders out there, like a lot of the building. I was just talking to one the other week, is almost a defense mechanism. They're comfortable, they're building, and so, they don't launch it. That excuse is gone. You know, you can't even say that to yourself. It's like, you got to go out and launch, and see what happens.

Chaz Englander (00:24:23) :
Yeah and also, when you're in production these days. Anything that was on, kind of, if you rewind back, if you take the business day, you put it back three years. That nice to have product list now becomes a need to have. There's a concept of the speed that you need to ship. You know, obviously, as the barriers to entry get lower, that means there's more competition. It means, you know, there's going to be more products in the market. You just need to ship so much faster. Come back to that point of product market fit in the AI world. Well, it's just like, it's just not static. You might not have it in the morning.

Pablo Srugo (00:24:51) :
So just to wrap up the Fancy story that ultimately acquired by Gopuff, did they come to you? Did you go to them? And same kind of idea, where was the business at more or less by the time that happened?

Chaz Englander (00:25:01) :
We were out raising $100 million, so the business in twelve months was flying.

Pablo Srugo (00:25:06) :
That's crazy.

Chaz Englander (00:25:08) :
We went from zero cities to I think fifteen cities in about six months, and even if you just think about the operationally, right?

Pablo Srugo (00:25:17) :
I was going to ask, how many people?

Chaz Englander (00:25:19) :
This is a business where you needed a warehouse to operate, right? So that's fifteen warehouse leases signed and negotiated. You need to stock the warehouse. So every city had to have the appropriate local suppliers. But the demand was there and I think at acquisition, I would guess about seventy or eighty people. I think, but I'm not one hundred percent sure, around that sort of number. In the head office, obviously, if you include drivers and warehouse staff. It would have been maybe even, I don't know, five hundred people, maybe more, including drivers. I don't know, but a big number comparatively speaking. Yes, we were raising around, and Arnie, he got introduced to the founders of Gopuff, and they were great. And I think the timing for them was great. The nature, obviously, of our business as well, because for those that remember that market, it was very, very competitive. Obviously, COVID compounded it, and, you know, people were going out and raising like $20 million seed rounds. But they were all focusing on the biggest cities. What we did by fluke was we were, A, before anyone else, which was lucky. But we also, again, another fluke that happened was we were focusing on these smaller tier two cities where there was no competition. So I think, look, if I was playing it back, you know, and I was in their shoes and Gopuff's shoes. I assume they were looking for a European or UK based company, and we had the best numbers by way of size, but also by way of kind of unique economics and retention. Because we were focusing on cities with far, far, far less competition and look, I mean, they came along, and I said everyone did very well. I think them as well, I'd hope that if they look back on it, it was really a great decision from them. They won the UK market because of it. They're the biggest, if not the only, player in the UK market but it was stressful. I mean, the thing is with that is we're raising a round, the burn rate of that business was huge just because you had to really subsidize riders, it was called in that market. You know, you're literally running out of money. I mean, there's no two ways. If you're going out to raise a round and you ditch that, that explodes, and you're raising, or you're doing an acquisition. You're running out of money, and you're running out of money fast. And so it was super stressful but looking back on it though. It was like, I remember this call that we had with the legal team at like 2, 3 a.m. You know, all the signatures are landed, and the signatures have been released. And it's like you're there with the closest group of, because everyone in the company, you know, we're like, we're only friends because we've only hung out with each other for twelve months. That feeling is just like, you know, you do that two or three months all over again. Because you're there, you're looking around, you know, everyone's made a bit of money. Yeah, it's just shattered as well, I think, like as the adrenaline is coming down. It was awesome.

Pablo Srugo (00:28:00) :
Yeah, and did you go work at Gopuff or was it like a clean ending? You sign and you're kind of done?

Chaz Englander (00:28:05) :
So my brother Arnie, he was in engineering there. So he stayed on for three years. He wanted to, enjoyed it, learned a lot, great business. He made some great friends and stuff. I then stepped out. I want entirely. I was doing a lot, well, off the back of the acquisitions. We started to invest a bit, and that's kind of how the next business ended up being started.

Pablo Srugo (00:28:25) :
Yeah so now we can dive into kind of what you're doing today which is ModelML. What's the origin story there?

Chaz Englander (00:28:31) :
Well, for those three years. So, we set up a small family office type setup. Where, given Arnie was only twenty one and I was probably twenty seven. We were like, well, we don't want to just give our money to a wealth manager and do nothing with our day. What are we going to do with our day? Why don't we invest our own money? Which was a great decision in hindsight in the sense that you learn so much. right? Although there were advisors, investment banks, and even one private equity, and obviously we had that thing with Fat Llama where we looked to SPAC the business. We learned a lot about investing and the world of finance, basically. I mean, it helped I study accounting, but I didn't really know much prior to any of that. So we did that and we hired people to run our own money. So that's what we were doing, and we were investing across. I always say when I speak to a variety of strategies, but the actual thing looking back on, is we were just investing in anything. Anything we thought was cool, we would make money, and we wanted to allocate risk proportionally. We were kind of just doing anything, right?

Pablo Srugo (00:29:31) :
Do you think, was it smart? Do you think, looking back, or was it naive. Where you thought, because getting alpha in any asset class is very hard to do. You need edge, and you need all this stuff, assuming you assume a rational market and all that stuff. Were you just diving into stuff and looking back, you're like, Fuck, I can't believe it worked or what's the?

Chaz Englander (00:29:49) :
Put it like this, if you're asking whether we made money doing it, no. On balance, no but we didn't lose money. But we did make some money on some things and then we did do some great investments in a couple of things. But generally speaking, we weren't making any money, right? So why are we doing it? We were spending a lot of our day writing software to make that process better in one way or another. So either more efficient, or we were trying to get to a level of insight quicker, and I spent so much of my time just thinking of things that we could work on next, like as brothers, right? So Arnie must have got so fed up with me. I mean, he had a full time job, and every two minutes I'm like pitching him on this new idea.

Pablo Srugo (00:30:36) :
So you wanted to start, you actually wanted to start another startup with him.

Chaz Englander (00:30:39) :
Yeah, hell yeah. This is so boring. So we were kind of writing software a bit as a day job, and then there were all sorts of different ideas, and we'd invest in things, and we were learning as we go. And then we noticed that the idea we should be working on full time was literally staring us in the face. Which was the software that we were writing for ourselves to improve our own investment decision making process, was great and people wanted that, right? So that's how it started, and then we met a few people that, you know, who are very senior in finance. A bunch of CEOs of the largest banks in the world, and a bunch of really well known private equity investors, and so on. And they were like, hey, yeah, what's that? This is pretty cool. Can we use that, or how do I get hold of that? And then one thing led to another, and then we were like, hey, we obviously have to go at this full time. The more time we spent thinking about the value that we would bring to an actual customer. Particularly when AI started to explode, because then LLMs really took the software from being, frankly, not intelligent to intelligent, it was a no-brainer. So the truth of the matter is it got to maybe the end of '24, or '24 time. We were kind of pushed out the door just based on customers wanting to use the product and yeah, that's how I started.

Pablo Srugo (00:32:02) :
It's, you know, very similar to the kind of Toby Shopify story, right? Where he builds this e-commerce store so he can sell snowboards, and the snowboards are okay, but the store everybody wants.

Chaz Englander (00:32:14) :
Exactly, because the thing is, as well, is where it was and to some extent where it is, it's a productivity tool. So it wasn't necessarily making us better investors, but it was making us more productive.

Pablo Srugo (00:32:25) :
What did it do? That was my main question. Yeah, what exactly was the product?

Chaz Englander (00:32:29) :
It was basically we would receive an opportunity. So when I say an opportunity, anything. It could be to invest in a startup. It could be to invest in a fund. It could be some random co-investment. It could be a bunch of stocks. It could be anything, right? We'd get these opportunities through a whole variety of different avenues. We'd get them by email and there are a bunch of things that you do really, really quickly as a human to validate those things. Now, almost all of that information that you use to validate is not in the materials you received, because what you've received is a sales pitch. Sales materials. They're not going to tell you the bad things or the things that might quickly get you to an answer early on, right? They're just trying to get you to pick up the phone, get on a call, or potentially be interested. So we basically set up this, well, then we were just referring to it as automatically calling functions. Now you would call an agent, but it would receive an email, look at the opportunity, and then go and do a bunch of things. So, for example, and maybe relatable to this audience, if you receive an opportunity to invest in a startup, right? One of the very first things that you do is you look at who is running the startup, and you might see whether you've got any connections in common with that individual on something like LinkedIn, right? And you can get to the answer programmatically. So an example might be I receive a deck, and if that's one of the first things I do. I don't want to look at the deck. I just want to ping Joe Bloggs on WhatsApp, "Hey, just got this opportunity, what do you think of James Smith, right?" or whatever it is and so it was just building automations off the back of what you'd receive. That could enrich the data that you'd ultimately got via email. So either via different data points, the example of connections in common, things in the news. Now, if it was a consumer company, you may have loads of bad reviews on Trustpilot or equivalent. Or if it's a fund or a new GP, are they posting strong political views on Twitter? I don't know, there were a lot of things that you could do. So that's where it started, and it just got more sophisticated. So it wouldn't just give you the bullet points, it would actually create a Word doc or a PowerPoint presentation of the opportunity that you could really quickly get ramped up on and then quickly roll in or out. So that's where it started, and for better or for worse. I mean, that's kind of what the product does today. We call it a workflow automation product for finance, but basically it's doing that. Predominantly being used for the automation of the creation of materials, Word, PowerPoint, Excel, etc., particularly things that folks in finance are doing on a repetitive basis.

Pablo Srugo (00:35:08) :
So it's kind of like data enrichment, I guess, is the primary piece. When you mentioned the WhatsApp part of it, does it actually go out and reach out to people for you? Or just tell you, hey, you know these people, maybe you want to reach out and then you can do it on your own?

Chaz Englander (00:35:21) :
I think it's heading that way. So being quite clear about how the product has evolved and what it is we do. We describe ourselves as an AI workflow product for financial services. In other words, an AI workflow builder specifically for financial services. Now what that actually means in practice is, number one, what is financial services customers are predominantly, you know, banks, very large consultancies. Including the Big Four in that, and then asset managers.

Pablo Srugo (00:35:48) :
But it's very much an enterprise product.

Chaz Englander (00:35:50) :
Enterprise, I mean, all the way to the extent now, we partly due to the demand and partly to the way that our business model is evolving. We don't really look at customers that are going to be spending any less than maybe a quarter of a million dollars a year with us.

Pablo Srugo (00:36:04) :
Gotcha.

Chaz Englander (00:36:05) :
Just based on what we do. Now, again, when we say what we're good at, it's really material creation and verification. The verification one is interesting. So it's, you know, if you already have an output, you would go and verify that before sending it to someone. You can use really, really clever AI systems to do that in an incredibly sophisticated way.

Pablo Srugo (00:36:24) :
Walk me through that a little bit more, verifying what exactly?

Chaz Englander (00:36:27) :
So under the hood, and this is going a little bit technical. There are three different AI systems. One that goes and gathers all the information that you would need in order to create some kind of output. When I say output, I just think an email, a Slack message, all the way through to PowerPoint, Word, Excel outputs. Think very complicated. So don't think two pager, think like a two hundred page PowerPoint presentation, graphs, tables, charts, logos, with all the Excel backup files, and then verification. Now, the reason, interestingly, the AI systems are built in that way is that's exactly the same way that humans go through their, so we call it the cognitive flow, right? So as a human, when you initiate a task in your head, you gather data either already in your head or you would go to the different things that you can access on your laptop or phone. You would put that together into something, and then you would check it, and then you would go to the next thing. In some cases, send things out. As an example, that's what the AI systems do, right? Where that's being used a lot is in the automation of the creation of the material and the verification of the material. So on the creation, if you think about a lot of where the time goes, particularly for more junior members of the team at these sorts of companies. Is they are spending, you know, fourteen, fifteen, sixteen hour days quite often at these types of firms and if you study where the time is going, it's not going into what we would think is strategy or critical thinking or analysis or anything like that. It's literally going into creating a PowerPoint presentation or writing an email. In other words, you already have the information. You're just putting it together, repackaging it, and sending it out. And so that has been very popular. And I think the timing of us coming to market in terms of sophistication of the models and everything else was, again, I think quite lucky.

Pablo Srugo (00:38:22) :
Tell me about getting that first customer. I mean, you mentioned it got pulled out of you. Walk me through that story. How did that all come about?

Chaz Englander (00:38:30) :
So that was of one of those customers that were like, hey, you should do this full time. They came on as a design partner.

Pablo Srugo (00:38:38) :
And this was a what by the way? I don't need the name necessarily, but is it a bank? It's a, what is it?

Chaz Englander (00:38:42) :
A small advisor, 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 B2B 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 Arnie and I have learned, if I would say, there's a couple of things that are in the founder playbook in our head. Is perseverance is definitely one, but another thing is just the speed at which you can learn. 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 have a design partner that you're speaking to once a week. You're almost certainly going to 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 a world, by the way, where there's no kind of barrier to entry when it comes to writing code or technology in general.

Pablo Srugo (00:39:43) :
It's funny you mention that, like Legora. Which we just had on, became, I think, a $1.8 billion company in two years. Exactly like that, right? Was in the office with the law firm for the design partner phase. A huge change in that speed of putting something out, getting some feedback, the nuances, the qualitative stuff, like it just.

Chaz Englander (00:40:00) :
Yeah, if people hadn't. I assume, I don't know who that was but if it was Max. Max is a.

Pablo Srugo (00:40:05) :
Yes.

Chaz Englander (00:40:06) :
Max is an absolute genius.

Pablo Srugo (00:40:07) :
Yeah, he's a G. He's an absolute G.

Chaz Englander (00:40:09) :
I think the way, and again Max. I think the way that a lot of these AI application companies, their themes as to how they've gone from zero to one and beyond, they are very, very similar. I think the design partnership phase is mission critical. The speed of iteration is mission critical. I think the work ethic is super important. Particularly when the market gets validated, you know, if you think about that. Really your only tools are the speed at which you ship product and the speed at which you iterate. You know, that's really it. That's kind of your only competitive advantage, to be honest.

Pablo Srugo (00:40:45) :
So I'm assuming you worked from the office of this design partner?

Chaz Englander (00:40:48) :
Yeah.

Pablo Srugo (00:40:49) :
And were they a paid partner? How did you structure that, and how did you? Did you make sure that they were going to give you X amount of time a day, or was it just like a friendly relationship? What's the structure?

Chaz Englander (00:40:59) :
So really good question. I would say as well, I don't think there's a right or wrong, and I also appreciate that everything I'm about to say is in an ideal 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 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 ideal 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 buy in. Now, given some verticals, that may not be possible, but you definitely want to make sure that from the very, very top, the person that's actually making the decisions at the firm. They are a hundred percent bought in. You've also got to be mindful that a lot of people, a lot of CEOs, particularly if they've made money, can be quite flighty. In other words, they get excited about all sorts of things and so you really test whether this is absolute buy in. But you can also make a mistake. You might choose one; it might not work. It can be one or another, but it's just the speed at which 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.

Pablo Srugo (00:42:36) :
It's hard to know and appreciate the difference between having that qualitative advice all the time. And what that could do to the 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, we would not have built this thing this way if it wasn't for them? And as a result, you know, the product market fit was so much stronger. Do you have any of those kind of examples you could share?

Chaz Englander (00:43:01) :
I don't exactly, but what I do remember is particularly in the AI world. Because these demos can be so good, so cool. A demo kind of counts for nothing. 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 this culture of everyone says everything is great when, in fact, it might be awful. I think in the US, they're way better at just saying how it is a long time. So that's what you want to monitor and by the way, that may also not be in what they say, it may be in the data as well, right? So, you know, I would say that really, really pay attention to actually how much they're using the product. Because usage just doesn't lie. It's, you know, how many times you would hear a user say this is great. You know, having to ask for the first three months, but they're not using it. Well, it's clearly not great if they're not using it. You know what I mean?

Pablo Srugo (00:44:05) :
What were you waiting for? When did you know when it was ready to launch? What was that trigger? And then how did you structure the actual launch beyond design partners?

Chaz Englander (00:44:13) :
In true kind of Y Combinator fashion, we just, as soon as we even had close to a product. We were launched and we were going out, and doing as much as we could. I think we made a bet, which you know, in the way that we think about it. That was given the procurement cycles of our industry, you know, six, nine, twelve months at a minimum type numbers. We knew how quickly the product was going to 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 going to get ahead. But there was this point where it's so hard to describe, it's that tipping point product market. That people start using the product by themselves. You know, getting people to pay was less of a pain. You 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've got to turn the tap off. You've got to put the running spikes on and you've got to be prepared for almost no sleep. I mean, as I mentioned before, first year we were nine to seven. Whole year, every waking hour, frankly. Because it was a big TAM, we knew that, and we knew it was going to be competitive. And we also knew, and I think Legal AI space is a great example of this, 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 definition. Escape velocity is where twelve months ago it was a risk to use ModelML, I now think in some markets it's a risk to not use ModelML. That's escape velocity, and I think 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 legal market just by the fact that you're compounding, right? You raise more money, you can build more product.

Pablo Srugo (00:46:10) :
How fast did you get to like millionaire ARR?

Chaz Englander (00:46:13) :
We went from about $5k in monthly revenue to about $100k in three months.

Pablo Srugo (00:46:23) :
Wow.

Chaz Englander (00:46:25) :
And then we kind of did that again, in the next three months. Things moved fast. Also, when you've got contracts that are scaling, given the types of organizations like us. A big part is as soon as you land them, you know you're just going to build from there.

Pablo Srugo (00:46:40) :
What would you say is, when you think about go to market for enterprise. What's worked best for you? Whether it was around launch or whether it's about today, what is the thing that from a sales playbook go to market perspective comes top of mind?

Chaz Englander (00:46:52) :
The thing about it is you have to go into things. In my view, of your product is not unique. In other words, the person that you are pitching has probably seen ten other products that look like your products. I mean, this is very relevant, zero to one. I think beyond that it becomes quite different. So where do you differentiate or how do you differentiate? I think a big thing, admittedly I think this is very important in our market, is trust and credibility. Because if you think about the buyer, they have to latch on to something that sets you aside from the other fifty AI tools that they've now seen, right? And in our market that was trust and credibility. We ended up bringing on a bunch of really, really senior advisors to the business that became also close friends to myself personally and the business. That was really, really helpful. That was a way to differentiate. I think, now though that, the way I look at businesses once you got past that point. I think this is super important in the context of product market fit not being static. What I mean by that is if you look at our risk this year, right? I won't mention the number we have in the bank, but we've just raised a big round of 17, we've raised 15 before, and we've basically spent no money, right? So what is our risk? Well, there's kind of two elements of risk in any business of this stage. Do you have product market fit, and are you one of those companies that escape velocity? I think that we are definitely one of those companies that escape velocity, and today we have product market fit, so what is our risk? Well, our risk is, as I mentioned just then, we may not have product market fit tomorrow morning, right? And that's not based on OpenAI or Anthropic or these guys. It's just based on the speed that verifies application is shipping great products. So really our only risk now is the speed at which we can ship products. That is it and that comes from the speed that we learn and the speed that we can ultimately write code. So stay very close to the customer. Ideally, you want the code and the customer to be as close together as possible.

Pablo Srugo (00:48:52) :
Love it. Well, listen, we'll stop it there. Let me ask just two questions with kind of rapid fire. When was the moment when you personally felt like you found true product market fit?

Chaz Englander (00:48:59) :
When we were having to push customers start dates back and they were getting upset.

Pablo Srugo (00:49:05) :
And what would be your top advice having gone through three startups for a founder in that early stage looking for product market fit?

Chaz Englander (00:49:11) :
Perseverance, for sure. Not blind perseverance, but perseverance.

Pablo Srugo (00:49:16) :
Chaz, thanks so much for sharing the story, man. It's been great.

Chaz Englander (00:49:18) :
Amazing. Thanks so much, buddy.

Pablo Srugo (00:49:20) :
Wow, what an episode. You're probably in awe. You're in absolute shock. You're like, that helped me so much. So guess what? Now it's your turn to help someone else. Share the episode in the WhatsApp group you have with founders. Share it on that Slack channel. Send it to your founder friends and help them out. Trust me, they will love you for it.