The Exchanges

Q So share a little bit more. You get on a Zoom where you meet one of the 40 founders you were sort of hashing this out with, and you said, I have three different directions, and you Pitch them. What did you actually do? It sounds like the sort of general concept for Crossbeam bubbled significantly to the top. What did that actually sound like?

A Yeah, it sounded like there was always a next step. With a lot of these, you know, the Escape Room one, people loved it, and they're like, oh man, that'd be so cool. They'd probably have a lot of fun playing that. Oh, well, see you later. Uh, with the Crossbeam one, it was like, you know who you should really talk to about this? Because I know they've run into this problem is so and so. Or do a field or something where you can put me on your mailing list so I get updates on like when you've actually started building this thing. I felt like coming out of the conversations where I talked about Crossbeam, I was actually cultivating a waitlist or like some sense of pent up demand. And this is why Crossbeam is so cool as a business. The business itself is intrinsically viral. We're like LinkedIn for data. Like you can't use Crossbeam unless all your partners are also on it, or at least your most important ones are. So you are Intrinsically motivated to invite your partners on and talk them into joining, even independent of us doing anything at Crossbeam. And I started seeing that virality kick in before the product even existed and we could build viral loops into the product. It just happened by a telephone chain. I would get text messages like, you know, the partner manager at our biggest partner was interested in talking to you about this idea because they desperately need some ki…

AI assessment note: “it sounded like there was always a next step. With a lot of these”

Q left off, you went to 20 or 30 founders and kind of workshopped a few different directions. Crossbeam was resonant, at least in the sort of forward momentum. You intersected somebody and they would say, oh, you need to talk to Jane or Sally or this person or that person about it. In sort of as a detailed way as you can, what was then the following six months like?

A This is where the repeat founder thing gets really interesting because After talking with a lot of founders and getting some conviction around the idea, I did a couple of things in parallel. One of them was that I initially funded the company. Like I wrote a check into a bank account, created the C Corp, like basically issued a safe note to myself to initially stake the company. And one of my close coworkers from the RJ Metrics Magento days had, had left Magento and started his own development shop. His name was Buck Ryan. His company is called the Buck Codes here. And I hired Buck at the Buck Codes here to build an initial prototype of this product that I wanted to use to then, A, understand, like, the materiality of the technical challenges that existed, and, like, I wanted to pick something that was, like, actually going to be hard enough to create a defensibility moat in the technology itself, and I knew Buck was, like, the guy to really, really rapidly do that, so I went into a fairly technical mode, really for just, like, an initial month or six weeks, And then when we had like the most bare bones version of a prototype, so this is immediately next, right after this six week period is when we started meeting with the personas that we thought were going to be the buyers. It started out with RevOps people and then RevOps people led us to partnership teams. This is where I a…

AI assessment note: “I did a couple of things in parallel. One of them was that I initially funded”

Q You mentioned you were, you were kind of dual tracking these, you're basically gathering data on the three potential directions to go, and part of it was the pipeline product and doing product marketing and bringing it to market. In that process, did you get really strong customer resonance?

A That's a great point. That's a really great point. Yes, we did. And in fact, what was interesting is the form that it took, because we certainly started selling the product directly, like as new business and kind of finding These traction points where we were having a lot of conversations in the sales pipeline that were getting closed out as closed loss because people ended up buying Looker or ended up buying some other thing. And what we were able to do is basically pivot all those conversations, even ones that we had lost in the past into sales opportunities for the Argyometrics pipeline product. Because if you are using Looker sitting on top of Redshift at the time and you were like, oh crap, I really need to get my MailChimp data in here. There was no good way to do that in an automated kind of Cloud-based fashion without your engineering team writing a bunch of scripts to pull the data out of the APIs and drop it into Redshift. We were that middleware glue. So we actually made the Looker installs more valuable. We made the Redshift usage go up and the storage and compute that happened there go up by just kind of making the amount of data that was available more robust. You know, Looker, who used to be our biggest competitor over at RJ, started becoming our biggest refer of business at Stitch because the Looker sales reps knew if they were going to close a deal, Their clien…

AI assessment note: “Yes, we did. And in fact, what was interesting is the form that it took”

Q What surprised you now that it's, it's closed?

A You know, this is a funny answer that I hope is not, uh, that no one takes the wrong way. When you talk to Americans about merging with like a French company, you, you kind of get this reaction that's like, oh boy, oh boy, better get ready. They're all going to be smoking cigarettes and, uh, you know, uh, sitting on the roof at two PM and taking their a month long vacations in August. And, uh, it's impossible to part ways with anybody. They're all, you're obligated to employ them forever. And some of those things may have some like partial truths to them, but us Americans aren't perfect either. The thing that surprised me the most is the incredible work ethic. Of the people from the reveal team. This team works hard and is extremely smart and like absolutely goes toe to toe with anybody that I've employed at any company that I've built along the way. Like they have built an incredible company there. And I think, and I spent a good amount of time in Paris and increasingly in the Paris startup scene in the last year or so. Paris in general has this incredible energy to it from a startup perspective in general. There is a very real I think there was a generation of knowledge workers and technical workers in Paris, a huge amount of them working on AI stuff, by the way, like the AI ecosystem in France is really strong. And Matt Turk, one of our investors from Firstmark, you know, is…

AI assessment note: “The thing that surprised me the most is the incredible work ethic.”

Q Why did you choose specifically to talk to founders versus sales leaders, product leaders, pick any other potential end user or buyer?

A This may be a bias that doesn't actually You know, prove true in the real world, but it's a bias that I have, which is that I trust them more. Certainly, it's one thing to talk to your end buyer or user persona to try and identify like a strength of product market fit for a particular product idea. But to me, at this extremely baseline atomic level of a startup, while product market fit is really the whole ballgame as to whether it goes anywhere, there's more to life than just product market fit. The level to which I can build and rally a team and a level of personal conviction and a belief in long-term sustainable product market fit due to the legitimacy of the problem we're solving on a bigger scale, on a bigger context. Like if you're at zero, stage zero or stage negative one, and you're just a heat seeking missile for product market fit without regard to those other things, the problem is product market fit is extremely ephemeral. We, we experienced this at RJ and at Stitch in good ways and bad. You can build a product and the market can move and you fall out of product market fit. You can build a product and the product can move, right? And you saturate your market. You get to a couple million in ARR and realize that's where the ceiling was. Then you try to build that next feature on top of it to 10 X again, and you've completely pushed yourself out of product market fit b…

AI assessment note: “it's a bias that I have, which is that I trust them more.”

Q You touched on this a little bit, but what was the first version of the product? How did you figure out how minimum it could actually be?

A One of the things I learned really quickly was that people actually already do this at almost all companies, and I had no idea. The process of like cross-beaming back in the day before cross-beam was called account mapping, and the account mapping process is an exercise by which two companies who are collaborating with each other basically Email a bunch of spreadsheets back and forth to one another. And those spreadsheets are typically sent either by partner teams or by individual sales reps or by partner managers to sales reps, and they contain lists of accounts. And those accounts, depending on your situation, they could be customers, they could be prospects, they could be open opportunities, but they're very often like, it's not like every open opportunity in your Salesforce instance. It's like whittled down to a very, very small specific target list. And what you're basically doing with your partners is like playing battleship. It's like, all right, I've got 500 open opportunities right now. I'm going to pick 17 of them and I'm going to, cause I think maybe they're in the same market and I'm going to send them over to this partner. Cause I don't want to send all 500. I'd be like, you know, giving up the Glen Gary leads here. I love my partner, but not that much. So I think I'm going to take a shot at these 17. You send them over and they say, oh yeah, there's actually four …

AI assessment note: “One of the things I learned really quickly was that people actually already do this”