Tom and Vivek detail what they mean by “data-driven” formation ideas and how the super{set} startup studio has a reproducible process to gain conviction before writing a single line of code.

Good ideas are hard work.

Nobody plucks tech startup ideas out of the air like butterflies. Ideas actualize over time. It takes hard work and persistence to ideate a new formation opportunity that actually has the wherewithal to become a company.

Tom and Vivek make the distinction between ideas rooted in data versus software, and why super{set} pursues only these data-driven ideas.

Not all ideas are easily comprehensible from the get-go. Some ideas are straightforward and clear — like making kids’ boxed mac and cheese — and others take a bit more work to unfold — like a delicious, steamy, Michelin star soufflé. At super{set}, we discern one from the other through writing a detailed Solution Memo.

Similarly, not every idea makes it out of the kitchen and onto the dining table. At the ideation stage, Tom and Vivek think about market-message fit. Market-message fit is the proto product-market fit. It is estimating product-market fit before the product even exists

Learn more about how we at super{set} found and fund data-driven companies at superset.com

Transcript — Season 3 Episode 2

Speaker 1: Welcome to The Closed Session, How to Get Paid in Silicon Valley. With your hosts, Tom Chavez and Vivek Vaidya.

Tom Chavez: Welcome to Episode 2, Season 3 of The Closed Session. And here we are again. What’s amazing to me, Vivek, is that you chose to wear the same exact clothes to come back to record the second episode as you wore in the first one, for people who are now watching us on video.

Vivek Vaidya: I have 15 of these, Tom.

Tom: Oh, is that? Okay.

Vivek: I don’t, I don’t, I’m just joking.

Tom: Yeah. You just have the same… You’re officially a tech bro, now, because you take the same piece of clothing out.

Vivek: How long have you known me Tom?

Tom: You’ve got a lot of hoodies now.

Vivek: There are very few things that hurt my feelings, but calling me a tech bro?

Tom: Stinky, don’t even get like that. Come on. Come on, now. All right, so Episode 2. We talked about venture studios-

Vivek: We did.

Tom: Episode 1, and our understanding of the differences between what a venture studio does at formation versus what a venture capitalist does. A lot of people ask us, “Okay, but where do you guys get the ideas? Where do these things come from?”

Vivek: We did promise we’ll dig into it deeper in the last episode.

Tom: We did, so we should probably pay it off now and do that. Where do the ideas come from? How do we build these things from scratch at super{set}? At the last episode we said, VCs, and there are a lot of great VCs that we’ve worked with, but they’re one or two steps removed. They’re in the control tower. We’re flying the plane. We’re down here on the battlefield, shoulder to shoulder with our co-founders, and other entrepreneurs we’re lucky to work with. That still doesn’t answer the question of where do the ideas come from.

Software Versus Data

Vivek: Yeah, and we’ve said since software is eating the world, I think, yes, there’s a lot of software, a lot more software today than there was 25 years ago. But I think what’s even more impactful, or bigger, is data. The amount of data that we are producing as a civilization is just… I don’t remember these numbers ever, ever, but you probably do. Right? There’s-

Tom: No, don’t make me try to… I can’t remember them. It’s a lot.

Vivek: It’s the number of, in a single day-

Tom: Twenty times a library-

Vivek: Or single hour. Yeah, exactly.

Tom: It’s like 20 times the Library of Congress per hour.

Vivek: Per day, or hour. Something like that. Some ridiculous-

Tom: We can’t remember, but the point is it’s exponential.

Vivek: Yes. Yes.

Tom: And maybe somebody might accuse us of being a little school marmish with our concern about, well software versus data. But if you are in our space, it’s a very meaningful distinction because there’s an awful lot of software out there.

Vivek: Correct.

Tom: And if you think about the last 20 years of software development around these parts, there was a lot of focus in the prior regime around processes. Using software to automate, simplify, orchestrate, processes. That’s all well and good, but it’s hard to differentiate in the current context if you’re just doing that. So bringing this lens of data, what data is it that could be captured, that could be generated, data as an asset to be harnessed at the center of every kind of build out? That, we find, gives us a lot of power, a lot of differentiation.

Vivek: Correct.

Tom: And we’ve been doing it for a long time.

Vivek: It’s something that we-

Tom: It’s what we do. We’re good at it.

Vivek: We’re good at it and it’s also, not the only thing that we know, but we know it much better than say building a social media company.

Tom: We do quickly point out, if you want to build a cool consumer gizmo, I’m happy for you. That’s not my jam. I don’t have good sensibility for that stuff.

Why We’re Data-Driven

Vivek: That’s actually a good segue into how we view the world. We view it with these data-tinted flight goggles, if you will. What that means though, is that whenever we are exploring a new vertical, we talked about healthcare as a vertical in our last episode, we observed that we knew nothing about healthcare, but we ask these questions. How is data generated in this vertical? What is data used for? What kind of data exists? Who benefits from it? What value is there?

Tom: Can I tell a quick story?

Vivek: Yeah.

Tom: Let’s come back to the founding of Krux 10, 12 years ago. You and I were both obsessing over data. We’re talking to a prominent investor, enterprise investor, who has been in the space for a long time. I vividly remember, he looks at us in one of those conversations, cocks his head, squints his eyes like, “Guys, you understand, I’ve been doing enterprise software investment, don’t school me on data processing. That’s what I’ve been doing for a long time.” It took a while to get to that place where he started to understand data wasn’t just along for the ride, data… The lizard was now eating its own tail and data was the asset itself. It wasn’t just to be processed, it was to be harnessed and activated in a new way.

Vivek: I think the difference, at least the way I look at it, earlier, people used to make systems for movement of data, for processing of data, without really understanding how to harness it to generate value. The movie ended with, “Oh yeah, I moved data from place A to place B and look how efficiently I did it. Cheaper, faster, better, whatever.” But I think now, in the last 10-odd years, our evidence of this is this systems are coming up, software is being developed, companies are being created that not only move data or process data, but generate data as well.

Tom: That’s right.

Vivek: Then there’s a flywheel to your point about the lizard eating its own tail, the data that gets generated is put to work to provide better services, better automation to consumers, customers, what have you.

Tom: So that’s why we’re data-driven. We’ve talked about the torrents and terabytes of data being generated every single day, the opportunity that comes from taking this new lens on these problems. Why do we think we’re uniquely equipped to go and tackle this, based on the experiences we’ve had over the last many years? Rapt, and Krux, and so on?

Vivek: I think it’s a great question, actually, and as you know I’ve been doing a lot of recruiting for Markov, which is our MLOps company.

Tom: Here’s a plug for it, is that a cool name for an MLOps company?

Vivek: Markov ML.

Tom: Markov ML. It’s a dog whistle to geeks everywhere.

Vivek: I think credit where credit is due, Pankaj came up with a good name.

Tom: Guy nailed it.

Vivek: Yeah. But I mentioned Markov because I tell people the backstory of Markov and at Rapt, what we were doing at Rapt, in today’s day and age would be… Rapt would be an AI/ML company.

Tom: Absolutely.

Vivek: And it was all about processing data to generate value. It wasn’t just movement of data. We were actually harnessing the data that already existed in people’s order management systems, et cetera, to create valuable software that helped them in whatever business, whether it was supply chain or advertising, or what have you. This was what? Nineteen-ninety-nine, 2000? It was a long time ago. And so, we’ve been on this journey for a long time, and we’ve seen lots of movies in this category. And then Krux was the right next step, in that we built software that helped companies collect data and use it for improving their businesses. It’s a long way of saying that we have a lot of experience in doing this, which leads us to being intimately familiar with a lot of the problems and challenges that people face as they are building these systems, or products, or companies, or what have you.

Tom: That’s right. That’s right. Again, when you bring this lens to these problems, data is beautiful, and we’re big old geeks here, but let’s face it, it’s a law from information economics, data rarely gets sick, doesn’t complain, doesn’t suffer wear and tear.

Vivek: Doesn’t have feelings.

Tom: Doesn’t have feelings. Data is a very loyal steed.

Vivek: That’s right.

Tom: And the companies that are breaking through right now understand that premise. So the harnessing, the creation of a derivative asset… back to Rapt’s, right? Because we were seeing a lot of really valuable pricing procurement data. By the way, we understood how precious it was. We were still in the early innings of trying to figure out how to harness it.

Vivek: Oh, of course.

Tom: At the end, you remember, I was trying to staple the analytic inferences clause to all of our contracts, but it was too late because the concrete had been poured. That’s another topic. But the point here is that we were understanding, “Ah, I can create new insights, new results, new products from the use of this data. Can I get my contracts in line with customers to enable that?” We were checkmated and it was too late. We sure got it right at Krux and we-

Vivek: We did get it right at Krux.

Tom: …and we do it everywhere else now.

Vivek: And now we do it everywhere else. As you were saying, that thing about the narrating anecdote about Rapt, I was just thinking. The term “network effect,” it didn’t exist back then. Everybody’s talking about network effects these days.

Tom: Especially social network effects. You want to talk about data network effects for a minute. Tell us what that’s about.

Vivek: The idea behind a data network effect is, when you have data that is being generated or produced by the system that is being used, that data can be leveraged to create services and products that result in, A, more data being generated and more people coming in to generate more data.

Tom: There you go.

Vivek: So it’s a two… It’s a second-degree effective if you will. That’s what I think we mean by the data network effect.

Tom: It’s harnessing data from the collective to generate ever-increasing value for the individual customers on our platforms.

Vivek: Correct. And, the value that the collective gets results in more people being added to the collective itself. So, as it grows, the value grows exponentially, I think.

Tom: It’s important to note in this context, because we are product software guys, you can nail the technology component, but one of our big lessons learned, and for anybody listening here, it’s not just a technical problem, it’s a contracts, customer, go to market issue as well. Because if you don’t nail these conditions at design time, the way we failed-

Vivek: At Rapt.

Tom: …to do so at Rapt, you can’t get the toothpaste back in the tube. So designing these contracts… and it’s important because a lot of customers, we saw this before and we still see it today, customers say, “Oh yeah, yeah, yeah, yeah. Give me all of that. Give me all of the goodies. But you’re not going to use my data to feed the collective.” And that’s where we get to what we call the no free riders. “No man, you’ve got to give to get,” and we have held steady.

Vivek: We did.

Tom: With big angry customers with millions of dollars that they wanted to invest in SAS licenses with us. You got to hold your ground.

Vivek: Yeah. We stand firm in our belief that the value of what we’re providing to the collective trumps everything.

Mac-and-Cheese versus Souffle

Tom: Okay. So we’re spending all this time talking about these philosophical matters because this is the grounding, this is the foundation from which new ideas for companies at super{set} comes. Let’s start digging in-

Vivek: Yeah, let’s do that.

Tom: …on the ideas themselves. And, by the way, it’s two and a half years in, so we still have a lot to learn and we’re going to evolve this as we go, but let’s give our best articulation of how the ideas-

Vivek: Kind of come out?

Tom: Come into existence and take root.

Vivek: Yeah. I think this is a breakthrough that we’ve had recently. If people listen to our first episode, they were introduced to this idea of thingifying, or naming things. So we’ve given names to at least two approaches that we use as a source of ideas. One is Mac and Cheese, and we’ll get into what that means. The other is Souffle. We delved into the Souffle source a little bit in our last episode when we were talking about healthcare. Souffle, from our perspective at least, is something that it’s complex. We don’t understand it. So we have to go and talk to people in the industry to figure out what the problems are, what the taxonomies are, how to talk about the various entities that exist in that industry, et cetera. Mac and Cheese, on the other hand, is a category of companies that we’ve created where we know quite a few things. Take Ketch, for example. Ketch is a company where Tom is CEO, I’m CTO. It directly came from the pain that we experienced when we were going through the process of GDPR compliance at Krux-slash-Salesforce.

Tom: That’s right.

Vivek: We knew exactly what we did over there. We wished we had Ketch. That’s how we thought about it. What can we build that will help our prior lives?

Tom: That’s right. And there was that moment where we were trying to sharpen the distinction between these two companies, we call it Mac and Cheese because everybody loves mac and cheese. I love mac and cheese. You love mac and cheese. You got to let me get some mac and cheese up in here. So, those kinds of companies, we show up with a lot of context, and they’re almost companies where, “You just got to let me do it.” Like please, [inaudible], we’ve been in the boiler room, we have the context.” And so, they’re not getting cocky because we’ve discussed in our last podcast you can’t get cocky. You can’t get too certain. Revision can strike at any time. But, hey, we can leap ahead a little bit here with our mac and cheese because it’s been personal for us in some way.

Vivek: That happened at Ketch as well. Yes, it was mac and cheese. Yes, we knew a lot of things and we’ve had to revise and, I wouldn’t say revise, but evolve our thinking. Because we said earlier on that, “Yeah, we don’t care about things like record of processing activities, and data protection, and data privacy impact assessment,” but we’ve changed our point of view over that.

Tom: That’s right. That’s right. That’s right. Complete. And that’s a big change, by the way, among many that we make without remorse or apology as we go. So as we’re standing up these new opportunities, some of this is you and me and many of the other very talented people at super{set} we get to work with where, and it sounds crazy when people hear this, and I talk about it with, my wife has asked me, “How do you do this?” “We just kind of sit back, smoke a bowl, stare at a whiteboard, and just start swinging a cat. How about this? How about that?” We’re doing it with climate change right now. It starts with climate change is unignorably huge and important, and shame on us if we don’t start pointing our brains at that space. That’s literally how we get the party started there.

Vivek: And climate change, actually, is very… and we didn’t talk about this in the last episode, but I think it’s relevant for this one because we’re talking about where our ideas come from. Our belief is we want to do well by doing good. And so, climate change is one of those things where it’s just… Not only is the opportunity huge, but it’s just good for where we are as a civilization right now.

Tom: That’s right. So let’s take it a step further because that’s a good live example. So climate change, we just start with that impulse and then we call three, or four, or five of our friends, and we meet new people. We’re always trying to make new friends, and we bring them in for hour-long sessions where we ask really naive, occasionally stupid, questions. But it’s so valuable to ask those questions because, as I think we mentioned in the last podcast, we’re like children, unencumbered, who look at their adults like, “Why are you all tripping and why do you do that?” We just show up, “Why does it have to be that way? What if you tried this other thing?” From there, and we touched on this in the last episode, we start to formulate our hypotheses. We start to write what we call the solution memo. What’s the solution memo? Give us a quick-

Vivek: Yeah. So, this is, again, as you said, we’ve been doing this for two and a half, three years and we were trying to introduce some structure into our formation process. So the solution memo is the culmination of our initial efforts at learning about how to make souffle, or even getting crisper on what the mac and cheese is going to be. Even though we might know a thing or two about a company that we want to start in the Mac and Cheese category, we still have to write it down.

Tom: That’s right.

Vivek: What’s the business context? What are the statements of pain? What are the problems that we think we want to try and solve? What benefits that they might provide? Who are the users who have these problems, and who might use our software?

Tom: What are the solution vectors?

Vivek: What are the solution vectors that we want to examine and go down on. Then also, who else is doing it? What does the competition look like? What other things have people tried in this category? What’s worked? What’s not worked?

Tom: Last night, we were having a meeting along these lines for a new formation project and we’re talking to one of these very smart people, big brain on a stick, who is deep in the domain, and we say, “Look, we don’t know who the competitors are, but markets are efficient. They’re out there. We can’t name them today. Next step, we got to go smoke them out of the bush. Figure out who they are, because they’ve got to be out there somewhere.”

Vivek: That’s another important criteria for us. We don’t necessarily want to be pioneers, and we don’t necessarily crave the first mover advantage, do we?

Tom: There are some places where we do that, by the way our very first company, Rapt. I’m a total puppy and this is what young entrepreneurs always do. When asked, “Who are your competitors?” They say, “Oh, I have no, it’s so innovative, there are no competitors.” Ding, ding, ding, ding, ding. Run for the hills. So what are the big lessons learned from all the scar tissue and pain? There is no, no, no, no, no, we want to show up at arenas where there are lots of worthy contenders because the second mouse gets the cheese.

Vivek: Yeah. And I think that’s, as we’re talking sometimes to co-founders and even some investors that we’ve come across, the response is, or the observation is, “Well, somebody’s already doing it, so it’s not that interesting.” We saw that at Krux. It’s, “The space is already backed up. There’s nothing for you to do over here.”

Tom: Let’s dwell on that for a minute, because we were told in sharp unambiguous terms.

Vivek: Categorical terms.

Tom: This company, that company, we’re not going to name them now, “You’re late to the party and it already happened,” and, “Oh my goodness.” We talked also about the certainty to knowledge ratio, and VCs were frequently wrong and never confused. Man, were they wrong.

Vivek: They were.

Tom: So we really like showing up in places where there are other contenders, and then we persuade ourselves in the solution memo that there’s a secret.

Vivek: There’s something we can do.

Tom: There’s a technical moat that we can do that allows us to punch through and create unassailable value.

A Message from Our Sponsor

Tom: Should we switch gears for a minute and do one of our totally unpaid for promotions? What do you think?

Vivek: Sure.

Tom: Any ideas?

Vivek: I was going to ask you, actually.

Tom: Well, I think we should have a moment of silence and appreciation, or I can.

Vivek: Really?

Tom: Yeah.

Vivek: Coming from… Oh, I see. I see why you might say that.

Tom: Well, here we are talking about all these formation-

Vivek: How many domains do you own, Tom? How many?

Tom: All these formation projects, you have to have a URL for it, but, by the way…

Vivek: Okay, here it comes.

Tom: As you’re teasing me.

Vivek: Listeners, here it comes.

Tom: You’re teasing me for all these domain names, but I have these little hot flashes. In 2012, and it’s not an exaggeration. I woke up like I do in the middle of the night, “super{set}. Great name.” It’s the set of all sets, if you like math. You like to work out, you do your super sets. It has all kinds of cool meanings, and it’s just a cool word. Was not taken. I pounced like a cheetah on GoDaddy, or whatever, as you just buy the domain. It’s $4 and 99 cents, or something, for super{set}. It’s useful sometimes, but yes, you’re right, I have a bad habit of just impulsively setting up [crosstalk].

Vivek: Can I tell you a funny story about super{set}? So super{set}, as you know, is also the name of an Apache opensource project. One of our email aliases that we have at super{set} is admin@superset.com. So everybody who uses super{set}, the open source project, has admin@superset.com as their catch-all email. So guess what? I get emails addressed to admin@superset.com from Home Depot. I can tell you who all use super{set} because of the emails. Where I get emails from.

Tom: The power of naming.

Vivek: Power of naming.

Tom: We appreciate all the naming services that make it easy for us. By the way, this is also a funny thing, we were just mentioning it in our investor letter. Companies are going through an average of like-

Vivek: Three names, yeah.

Tom: …three name changes from scratch to launch.

Vivek: Actually that’s true. Habu, Ketch, Markov.

Tom: Markov we started was-

Vivek: Intellistructure.

Tom: Intellistructure. Then we went to Mescelaro, and now it’s Markov. We’re going to stick to Markov.

Vivek: I think we’re going to stick to Markov.

Tom: But you have to have a nice bullpen of possibilities, such that you can stand up these companies and give them a URL as you get going.

Vivek: Thank God for ICANN.

Tom: There you go. Should we go back to the main line?

Gaining Conviction — Before We Write a Single Line of Code

Vivek: Let’s go back. So now, we’ve written the solution memo, and we’ve convinced ourselves that there’s a [bear] there that we want to go chase down. How do we get conviction?

Tom: So look, there’s a lot of chatter about product-market fit around these parts and it’s important for the Stage 2 leg of the journey. And let’s not talk about it because there are differing definitions of product-market fit. We all kind of have a sense of what it’s about. What about the stage that precedes it, which is what we’re talking about here?

Tom: Well, I have a lot of passion for what we’ve taken to calling market-message fit. Before I have a product, I need to have a clear, coherent conception of what the thing is. I need to be able to say it to you. And this is what we do a lot of. I say it, you say it, I say it, you say it back to me. Is that the thing? Is that the thing? So we just need to persuade ourselves that you and I aren’t high when we’re talking about these things from scratch. Then we have to go and talk to the panels of people that we’re assembling. So there’s this constant reflective equilibrium we’re getting into with them. We’re like I say… and they say, “Nah, don’t really, I don’t get it.”

Vivek: Doesn’t resonate.

Tom: “That doesn’t resonate.”

Vivek: “Say it again.”

Tom: “That’s not my problem.” “No, that’s not my pain point, the way I say it is.” So it’s this very kind of iterative communications process. It’s about clear thinking and being able to articulate what it is. That’s what we mean by the message. And if there’s coherence and correspondence between the message and the market, then you’re underway. Because, as we also like to say, “Look, once you have that clarity and that precision, the product starts to fall all organically out of it.”

Vivek: Yeah. It just emerges.

Tom: Then you find the engineers that you want to work with to help code it. It’s all hard, but the hardest part is the front part.

Vivek: It is because, as you correctly observe, there is this back-and-forth that needs to happen between the people you’re talking to and you, the bearer of the message. And there’s an art to it because you can’t lead the witness too much. You have to balance the advocacy with the inquiry. You have to employ the Socratic approach a lot, but also find ways to, “Oh, that’s what you said. So is it this? Or is it that?” You have to get clarity. Your objective is to get clarity and answers to questions that you have, before you start a conversation.

Tom: And you’ve got to be obsessive. By the way, we’ve made mistakes. We see a lot of entrepreneurs making mistakes because you’re hearing what you want to hear.

Vivek: Want to hear.

Tom: We still fall into that ditch, but we have our cockpit checks. We try to, “Wait, did that customer say, ‘Blessed are the peacemakers?’ or did he say, ‘Blessed are the cheese makers?’” By the way, we should do a plug for Gong. We’ll do it officially in another one. I love Gong because I can go back and listen to what they said. It’s so powerful. So market-message fit is about getting to that level of clarity and precision in anticipation of the product and the buildout. But unless and until you have this precision at it’s early stage, you’re going to go down lots of rat holes with no cheese at the bottom. You’re going to thrash, and zig, and zag, and ugh. We’ve done that too. It sucks.

Vivek: It sucks. I think another output of the market-message fit, I think there are two interesting ones. One is it gives you this statements of pain. Yes, the solution memo has an initial idea of what the statements of pain are, but market-message fit and the process you go through to get clarity on the message-market fit, gets you to more precision on the statements of pain. Then, the second thing that emerges from that is what your product strategy is going to be.

Tom: That’s right.

Vivek: What your product strategy is going to be and who your users are. What are the user personas? Who are you solving what problems for? I think that emerges from the process.

Tom: Let’s do a quick example of that. You and I are both crazy about staging and sequencing in product definition. So again, this is before you’ve necessarily even slung a single line of code-

Vivek: Single line of code. Yeah.

Tom: You have to have a Stage 1, Stage 2, Stage 3 articulation of the arc of the company and the post conditions of Stage K are the preconditions of Stage K+1. We’re crazy about this. I’m going to do these things now. That’s going to set up the sockets for the launching into the next phase. It induces this kind of clarity for all of the engineers, and all of the product people, and the sales team because in enterprise software, especially, which is what we do a lot of, you’re selling what’s on the back of the truck and you’re selling the road map.

Vivek: The vision.

Tom: So I catch to fix ideas with an example. We’re very clear with all of our customers, three things-

Vivek: Three stages.

Tom: Comply, control, secure. That’s how we do it. It sounds so trivial, but it electrifies and organizes the company motion.

Vivek: It’s a great way to communicate or start the conversation about your pro… “What does your company do?” “Our company will help you do three things, comply, control and secure. Here’s what we [inaudible] comply, here’s what control is all about, and this is where we’re taking you into secure.”

Vivek: I think the other thing to observe over here is, because people might wonder, “Well, wow. Stage 1, Stage 2, Stage 3. You’re talking about a seven to 10 year buildout. You figure all of that out right in the beginning?” Yeah, kind of. We have very high certainty in what the Stage 1 is going to be. We have, just like any prediction or forecast, less certainty in what the Stage 2 is going to be, and less certainty in the Stage 3, but we have a point of view. Now, as you’ve observed earlier as well, we do change our minds and we do zig and zag, but there is a scaffolding and a framework that we’ve built within which that zigging and zagging occurs.

Tom: You’re revising, as you should, as you must, within a clear envelope of action and market possibility which you defined at design time. We didn’t do that at the first company. We sure did it in the second, and oh my God, that was instructive, “Wow. This really works.”

Vivek: “This really works.” Yeah.

Tom: If you take that approach. Okay. Before we get to the next part, which I think is about wrapping up, I want to ask you about this thing you said in a meeting the other day. You referred to a disposable product. I’m pretty sure I heard you say something along those lines, which is, “Hey, in this early, early stage…” And we’ve seen a lot of engineers get all nerved up about, “Wait a minute, am I building the most scalable, perfect thing? Is this going to take us to the moon?” We’ve struggled getting some of our compatriots to understand, “Guys, right now, especially at this super early stage, you can call it…” And I remember engineers would say, “Well, that’s just a prototype.” Okay.

Vivek: And that’s a good thing.

Tom: Embrace it.

Vivek: It’s a good thing.

Tom: That’s a good, good thing.

Vivek: I think at this stage, sometimes what happens is that when you are talking to people and you’re further down the road in your market-message fit conversations, you reach a stage where it’s very helpful to have a thing to show. “Well, do you mean this? Or do you mean that?” Now, you can use your words but, as we know, pictures speak louder than words. And working software, even if it’s a prototype, speaks louder than just pictures. So when I said disposable software, I meant one of two things. It could be a Figma prototype. Figma is a great tool. So you can design a Figma prototype that helps your potential customers understand what you’re talking about. Or, you can actually just sling some code to convey what you’re talking about. The idea over there, though, is that you have to be open eyed and embrace, and really plan for the fact that’s all going to be throw away work.

Tom: Yeah. Because so many engineers, and God bless them, they want to engineer the bridge such that it can support 24 semis on it at any given time. Hey, in the early stage, we’re trying to get from point A to point B. It might be a pontoon bridge. It might not be the most beautiful work we ever do. The point is to get from here to there. Prove that it’s possible. So we’re unabashed these days about, and getting engineers to understand this is the journey. This isn’t a bug. This is an intentional aspect-

Vivek: Yeah. The feature, not a bug.

Tom: …of what we’re doing. Look, we covered a lot of ground here, but hopefully this sheds light on how-

Vivek: Yeah. Data-driven companies, point number one. And there are plenty, plenty, plenty of opportunities to explore over there. Market-message fit. That’s thing number one. Solution memo, that’s another topic we dug deeper into, and then second mouse gets the cheese.

Tom: That’s right. And look, let’s also just say one of the things we’ve learned at this leg of our journey is that, in the places where we’ve stumbled, it’s probably because we weren’t as fierce as we needed to be about doing it this way.

Vivek: This way. Yeah.

Tom: And maybe for some of the people that we work with, it’s not a match because some people want to show up, and improvise, and chart their own course, and whack through the jungle in a different way, and that’s okay. But these kinds of aspects increasingly define the super{set} approach, and we’re learning that we really got to stick to it because it really works.

Vivek: We do, and I think that’s a good place to end.

Tom: Absolutely. So, that’s how we do it. Looking forward to seeing everybody in Episode 3 soon.

Vivek: Thanks for listening, guys.

Tom: Thanks all.

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