A Product Market Fit Show | Startup Podcast for Founders
00:03:55 · Pablo Srugo
[00:03:55] S1: Referrals, I think, are one of the best signals of true product market fit. And everybody gets like some referrals. But if you're getting a lot of referrals and that becomes like a big channel for you and in the early days you see sparks of it, you just think about yourself. Like which kind of products do you organically tell other people about? Like it's a lot of social risk to tell someone, hey, you need to try this product. So you really only do it with the products you genuinely love. And you feel like this is such like whether it's a productivity so useful or it's just like an amazing experience type of product. But it's got to be in one of those categories. And so I think that's one of the clearest signs, early signs, I should say, of product market fit.
00:04:32 · Nick Fleisher, Pablo Srugo
[00:04:32] S0: Yeah. It has to be like a completely net new category and product of something that like you've really never experienced. Right. Like the first moment you had Claude or ChatGPT and you told your like your family and friends about it. Or it has to be like something that takes an existing market. Like we play kind of in this contract lifecycle management market and like throws everything that you know about it out the window. And it's like, here's what good could actually look like. Plus really good service and support. Right. Like to us, one of the most important parts of building in the AI era, and I'm sure others have talked about this in the show. Like if you want to roll out a successful AI implementation or tool at a Fortune 500, a huge component of it is like, are we helping you understand the tool and roll it out properly? Otherwise, there's no value in vertical enterprise SaaS or AI. And that's a rabbit hole we could go down for sure. [00:05:21] S1: One of the questions that I get a lot of founders like asking or at least thinking about is, how do you drive more referrals? How do you drive more word of mouth? Is there anything you can meaningfully do on that sense? Because you mentioned a lot of your business comes through there. Or is it just about, well, you got to have a great product that people love and you just organically get that?
00:05:36 · Nick Fleisher
[00:05:36] S0: I think great product that people love is like the lowest bar. But like then there's things that you kind of have to do on top of that. One is like, do you service your customers so well that like they build close relationships with your team? Like I was traveling this week in, you know, in the middle of the country. Five people on our team went and they all like had separate dinners and drinks and like social events with the client that they've just like built relationships with over time. Like not even about work and what we're doing. And so to me, that's like one way. And then the second is like we've hired and brought on people to our team really early who were stewards of the community. Like one of our first tactics when we launched was like we want to be like a place that the legal community feels comfortable going and like talking and spending time even if they're not users of Sandstone. Right. I think this is like one of the most critical ways to get word of mouth and referral is like you can't just be comfortable with the product and the service that it provides. But also like is this a community that's like actually net positive for legal or legal tech? And you can do that same thing in any vertical. So we've hired people who like have spent 20, 30 years building in this community and know the different areas of legal tech and GCs and legal ops. And I think that's like been a huge source for referrals and just building our network on the sales side.
00:06:50 · Pablo Srugo, Nick Fleisher
[00:06:50] S1: Well, we're going to talk at the end about kind of two tactical deep dives. And one of them is related to this because you're hosting like two to three dinners every single week with people that could be your customers. And you've got a whole kind of playbook for that. So we're going to talk about that. We're also going to talk about why you're hiring an AE so early. Most people do it well after a millionaire. You did much earlier. So we'll talk about that as well. But let's go through now the story. Right. So what was the first idea for Sandstone? When did that happen? [00:07:15] S0: Yeah. So I was at originally engineer, built mobile apps, ended up at McKinsey. At McKinsey, all of my work happened to be legal tech. It was just very random. My first client was the biggest legal tech and research company. [00:07:29] S1: When was this, by the way? What year?
00:07:30 · Nick Fleisher
[00:07:30] S0: This was five years ago. Okay. This is pre-Gen AI. But legal started to have this moment where there was a lot more automation. And people were starting to say, we need to get our data in order. So we took this work with legal tech companies. And we started going to law firms and in-house legal teams and saying, your data is a mess. It's all over the place. You don't have any tech people within the org. Let's just go figure that out. And it was very nicely timed because then Gen AI became a thing. And all these law firms and big, massive legal departments were like, hey, we want our AI to work better. But our data is a mess. And so we pivoted into becoming sort of like a Gen AI consultancy for big law firms and legal departments. That was most of my work. But another chunk of it was actually helping McKinsey's legal team. And so McKinsey's legal team is a couple hundred lawyers. We would work with them and think about what they were doing and how it could relate to what our clients are doing. At McKinsey, if I needed a statement of work for a new client, I would message my favorite lawyer that I knew very well on Slack. She would take a couple of days to respond because she's a busy person. She would then forward it to the right person, usually through Slack or through email. And then 10 days later, that person would come back to me with a bunch of questions. After I answered those questions, a couple of days later, they would draft the statement of work and send it over to me. And so it was like this multi-week process to create something that was like, to one, connect to the right person, to two, gather the right context, and three, like create a pretty simple work product. But what I realized in that was like, most of the work was not in creating the work product, right? Which is where you think of like all the J&I applications. It was just like all the stuff before it. And so that's where the first idea was born, which was my co-founder, Jared, who's also at McKinsey. He's a lawyer. And we sort of said, why can't we just build a tool on top of Slack and Teams and email that can do that first back and forth, connect you to the right person, gather the context, and then just put it on their plate with ready to go work on the work product. And so that was, you know, V1.
00:09:29 · Nick Fleisher, Pablo Srugo
It was centralizing intake across all these different sources, finding the right lawyer in the legal department to work on it, and asking questions using AI with the business user to gather all the context before it hits the lawyer's plate. And like, we realized that was quite an unmet need. Like there were some intake point solutions, but none that were using Gen AI like that. And so we started rolling that out, you know, on the side with some of our friends. [00:09:54] S1: This is what year at this point, like when you actually decide that you want to build a solution for this? [00:09:59] S0: This is early last year. So 2025, early 2025. And over the summer, we're still at McKinsey. So call this May, June into July of last year. We were testing it on the side with our friends. And McKinsey Legal can come at me and be mad about that. But we had a lot of friends who were lawyers. And so we would ask them, hey, could you like implement this on your smaller legal team within a broader legal department and just see how it goes? There were two really interesting things that happened. One, like people started using it to just track and manage work. And we realized like legal teams never really had their version of Jira or Linear. [00:10:37] S1: Crazy. Like they don't have a CRM?