Podcast / Fund-Build-Scale

Fund/Build/Scale: Fundraising from Both Sides of the Table (Transcript)

Here is the full transcript of the conversation between Fund/Build/Scale podcast host Walter Thompson, MindsDB CEO and Co-founder Jorge Torres and Mayfield Partner Vijay Reddy:

Jorge Torres  00:02

We humans, we are like these pattern recognition machines. And the more you do it, the more the pattern starts to become second nature. Given that there’s so many unknowns and the journey ahead for any entrepreneur, you want to find investors that not only understand it because it just logically makes sense what you’re saying, but they understand it because they’ve walked that journey before a few times.

Walter Thompson  00:29

That was Jorge Torres, CEO and co-founder of MindsDB. Jorge and Vijay Reddy, AI startup investor at Mayfield, were the first few people I interviewed for season one. We met up at Jorge’s office in San Francisco’s Mission District on a rainy Friday afternoon in November 2023. We dived into pitch tactics and investor outreach, but we also spend time talking about the frameworks VCs use to evaluate zero-day investments, which red flags investors and founders both need to look out for, and how to find an investor you can partner with for the next decade, not just the next funding round. 

Jorge has been through the fundraising process three times and Vijay is an experienced seed investor, so I was glad to talk to them both about fundraising from both sides of the table.

Walter Thompson  01:19

Vijay and Jorge, thank you very much for being here today. So today, we’re gonna talk about fundraising from both sides of the table. Vijay, you’re an experienced investor, Jorge, you have raised, how many times?

Jorge Torres  01:54

Three times? 

Walter Thompson  01:56

We’re in a hype cycle, I don’t think that’s a controversial opinion, which means a lot of future AI founders are probably spirit feeling serious FOMO at the moment, I think. And that leads to a lot of people that just want to pitch and get out there as quickly as they can to get their company going. So before you start fundraising, I guess my first question for you, Vijay is from another early-stage AI founder. What is it that really convinces you to invest in early-stage companies? And what can founders do to get to that point?

Vijay Reddy  02:28

So I think I think it’s fundamental, right? So raising funds for an AI startup is like raising funds for any startup. Keeping AI aside, when we look at the teams, I think every fund has its own metrics, which every fund looks at it differently. For us, we start with a people-first philosophy, “is it someone we can back? Do they have the same values? And is this a team you want to go in bed with in for, like, 7 to 10 years?” And so that’s the first item we’ll look at. And we can talk about how we can screen for that. 

And second is, then we’ll look at the markets. Others look at markets first, and people next, but for us, it’s always people-first, and then we’ll look at the market; is it big and growing and a nice, attractive market to go after? And it doesn’t have to be a day zero, right? Sometimes most of our investments are day zero, there are blue ocean, there’s zero TAM, but can this become a bigger attractor? So once we have those two, then we go into the specifics of that particular company. Do they have the right technology? How good is the team? How good is the opportunity? And then we dive into the product and technology. But that’s more on the latter side after we clear the people and the markets filter.

Walter Thompson  03:54

What does that process look like for you, as far as assessing a team? How do you approach this? What are the balances used to kind of get in there and assess their appropriateness for this product or solving this problem.

Vijay Reddy  04:06

So we invest very few deals there. Very, very concentrated portfolio in the sense that every deal matters to us. So we don’t spray and pray right? For us to make a deal work, we need to make sure the team has some attributes, which we look for. It’s not just the founder, it’s the team that can come together. Do they have the product market fit? Can they attract talent? Can the founder attract talent? Does the founder understand the technology? So there’s a lot of different attributes we’ll look for in a founder. And usually in the first half hour we can get a good sense of hey, is this person in the team, someone we want to spend more time with? And when we do we tend to dig in a little bit. But for the first filter when we do talk to them and we try to meet them in person or not. We can still do the zoom thing, but we tend to spend a lot of time on the human filter. And then we spend more time on technology afterwards.

Walter Thompson  05:09

Jorge, for your perspective, what do you think a team needs before they start pitching before they put a pitch deck together? What do they actually need to have figured out before they go into the market and start asking strangers for money?

Jorge Torres  05:21

Yeah, I think it’s to understand that, at the end, it’s  a risk decision, the one that the investors are making, and frankly, speaking, the decision that as an entrepreneur anyone should be making, it’s being able to understand that you’re taking risk, and then you’re taking an opportunity as well. So the most ideal situation is that you are building something that has, or you’re about to embark into something that has a great deal of an opportunity, and then that you’ve thought of all the possible risks that you can control. And therefore, when you present this to the investor, you’re actually tackling the risks that are in their mind. And I think that risks for investors change over the life span of a company. When you’re starting, you have so very little data that the risks are more about, is this group of founders capable of executing what they’re kind of like about to jump into. And I think that that’s something to to your point like that, that human assessment is the most important assessment that they can be making, because companies that die, I think you guys have been doing this for such a long time that you know, that the chances of a company not surviving, because the founder is not being the right fit for the problem for the execution or even within them are very important risks. 

So founder risks in terms of like, are the founders, the right people for doing this, the founders being able to execute because they work well, they don’t have redundancies, you know, like, you can try to understand that this decision from a risk point of view, then when you pitch it, you have to kind of understand that you have that part covered as well. And be honest to yourself as a founder, like, am I going to be in this company for the next 10 years? Can I dedicate, like sleepless nights because it’s going to be hard to be here for 10-15 years? And if the answer is yes, then you know that you can articulate this: Do I have the expertise or the talent to bring people that will bring the expertise I don’t have. So those are the things that I think is one of the buckets. 

But I think that before you even get to the bucket, there is something that is defined not necessarily by you as a founder. And it’s more as, there must be a problem that is so large, so, so, so large, that it must be obvious to you, because you want to dedicate your life to this thing. But it must be obvious when you articulate it as well, it has to make sense to the people you talk to about it, what you’re doing here is you’re telling “look, it doesn’t matter how inexperience I may be because I’m just starting, you know, you have to build the experience in this. But the market is so large that even if I’m not performing 100%, on the solution that needs to get to market, I will iterate fast enough, where I will have enough times to iterate that I will capture a significant percentage of this market.”

Yeah, so this is a market risk. If it doesn’t make sense, from the point of view of an investor, that you’re going to build a business that at least sells $100 million, then all of a sudden the market is not worthwhile the risk. So for an investor that math seems to be very simple. And if you can answer those three things, effectively at the very early stage, then not only two things are going to happen. The first one is you’re going to meet investors that will definitely ride the wave with you because they will likely want to also participate in the solution of that problem. But you will be jumping into something with the right answers. I think that a lot of entrepreneurs, we jump into this thing because we want to be entrepreneurs because it’s an attractive profession to have. But not being clear about these two or three, like specific questions that you should ask yourself and have a very, very concise answer to. It’s a mistake that many of us make, and then until you figure that out, is going to be really hard to make progress.

Walter Thompson  09:36

Following up on that. So just tangibly, Vijay, if I only had — if I was at the ideation stage and didn’t have a demo, and didn’t have customers and only had slides and an idea to share with you would that be enough to pitch you, or do you want to see more concrete things you can investigate before you make a decision?

Vijay Reddy  09:59

I think every VC wants to see as much data as they can have in a given stage to make a decision, right, the more data is good, right? So for late-stage VC, you look at the financial metrics at a cold market, we have a lot more information. at the seed stage, we tend to invest most, a lot of our deals are at PowerPoint stage. And the question going back to Jorge’s is like what are we underwriting, right? There’s people-risk, market-risk, progress and technology risk, go to market risk. So we tend to see how much we can de-risk at any given stage and the valuation and the resources are kind of going hand-in-hand with kind of going back to the risk analogy here, right. So we tend to take less risk on people and market, because that’s fundamental to what we master. 

So if a team is good, if you have a good sense of the market, those are two things we can telll right at the earliest stages. But we’ll have to take product risk, go-to-market risk, we help with idea-market fit, we help with product, we help with hiring and recruiting. So those are risks we’re willing to take at the seed stage. And so we are more than happy, and in fact, we would encourage founders, even if they don’t have a fully structured plan, to work with us. And we can help shape and dive at the seed stage. And that’s part of being a board member and almost every deal, we do take board seats. So we kind of enjoy that part of the journey. So we would typically encourage founders to come in and brainstorm with us even if they don’t have everything set in stone.

Walter Thompson  11:38

I know somebody who’s building now, and she doesn’t even have a front end for the demo, because she has no designer. So she’s trying to hack it herself. But it sounds like you’re saying that that shouldn’t be a blocker or someone as far as like, they could still come to you. And you’ll ideate together I suppose.

Vijay Reddy  11:50

Yeah, I think for the right things, though, right. So we don’t have the bandwidth. Again. There’s hundreds of hackathons, there’s dozens of startups, we can spend time with every one of them. But for special teams, we call it “n-of-one” teams where you have a special sauce, which you know, either, you know the market really, really well. Either you’ve been involved with companies in the space before, or your the world’s leading expert in that particular space. So hat’s how we look at the n-of-one teams. And if we’re building something very unique, very special, and you have a differentiated way of going to market. That’s what we would like to spend more time on just given that this number of hours today.

Walter Thompson  13:52

I want to keep the conversation positive because this is a hard thing to do, starting up a company. But what are some red flags that you see at that early stage that tell you early on, “this is not the right team, this is not the right person.” Generally speaking, what are just the typical red flags that are an easy no?

Vijay Reddy  14:12

So there’s quite a few of them, right? And sometimes it’s obvious, sometimes it’s not obvious. So there are things which have made them successful in their own fields, which might not translate very well to being a founder. Right? So to give an example, if you don’t know who your buyer persona, or who you’re selling to, that’s an open question. And that’s something you can diligence before you don’t have to build a product for that. You just need to have empathy for a customer and should know what you’re trying to build. Right. There are many founders who really liked the technology but haven’t thought about the business plan. They’re extremely — we call them “brilliant jerks” at large companies that are extremely good at individual contribution, but that’s not a good skill set to start a company. There are some founders who don’t know who the competition is. And these are things which you could have done homework before. So there’s a lot of this nuanced way of how, as, as investors, we’ve seen so many companies, and we tend to pick up on those if not any homework or not in a good listener, right. And sometimes we meet people across different areas, a spectrum. But in most cases, we tend to look for outliers, right? So if you’re brilliant at something, and if you can go build a team, which is very differentiated, and those are things to look for, so we’re still looking for people who are exceptional in some category.

Walter Thompson  15:45

So flipping that a little bit, as a founder, what are some red flags that as a founder make you not want to work with an investor?

Jorge Torres  15:55

I think that now after doing this for some time, for us, what has worked is to look for investors that have done investments that can add value, because of the experience that we had before. For example, we humans, we are like these pattern recognition machines, and the more you do it, the more the pattern starts to become a second nature. Given that there are so many unknowns, and the journey ahead, for any entrapreneur, you want to find investors that not only understand it, because it just logically makes sense what you’re saying, but they understand it because they’ve walked that journey before a few times. And this type of investor will also get very excited about what you’re doing, because they know it, the more an investor knows an industry, the more there is this affinity, this click that happens when you meet them. 

And when that click doesn’t happen, you have to ask yourself, “is it because there is no experience from the other side in what I’m doing?” And therefore, you should be cognizant that every minute that you have in the day is a minute that you’re not going to be able to take back. So every minute that you’re talking to the wrong investor, you’re just barking up the wrong tree. So understanding the people that have the experience, to guide you through the challenges ahead, is what you should be looking to. And therefore when you meet people, and you’re just essentially realizing very quickly that they just don’t have the experience on the industry that you’re about to jump into, or that you have been working on, then you’re probably you know, all money is green as people say, but you need to guarantee that money comes with a lot of value. 

And that has been the trick for MindsDB; like, when we have gone fundraising, after we understood that there are investors that have done very similar investments to what you’re doing. And they’ve had incredible amounts of value, like 30 minutes talking to them will be six months of you like spinning wheels. That’s what we want. And when it’s the opposite, it’s more like, “I don’t really know what he’s talking about. But you know, seems like the market is moving that direction. So I’m gonna throw money this way. It’s okay to add investors, depending on the value that they add. They may add network, but you don’t want to make them the main investor. 

Walter Thompson  18:18

Unike Vijay, most VCs are not former R&D engineers, right. But with a lot of experience, technically. And so I imagine there’s a lot of investor education involved with trying to get an AI startup funded. Is that something you had to do? How much did you have to work to educate investors about the value of what you’re trying to produce? Or did you just find investors who understood immediately?

Jorge Torres  18:43

I think that it only got really well for us, like everything started to get crystal clear once we started talking to investors, where we were speaking the same language. And then once you do it a few times, you learn very quickly to make that discrimination. That doesn’t mean that other investors that don’t really have the experience on their bags are not valuable. I think that you can then strategize how you build around a little bit differently, you first find these people that they’re just going to add a lot of value on top of the money because of the experience that they have. And then you’re going to build relationships with people that make them useful down the line. Yeah. And then when it comes to making the decision of who you bring into the round, then you pick the best of the best.

Walter Thompson  19:39

Everyone always wants to know about pitch deck how-tos or a magic formula for what needs to be on a certain slide and so on and so forth. But it seems like what Vijay was saying before is that getting funding for an AI startup is more or less the same as a startup; there’s some specific problems you have to solve and address and think about it. So, if I asked which slides are most important than an AI pitch deck, how would you answer that?

Vijay Reddy  20:07

I think it depends on what kind of industry they are after, right. It’s enterprise sales, open source. So some caveat in that with a more generic answer. But we would like to see the team and the market first, defend the center, if it’s the right team, going after the right market, and then trying to understand a little bit more about like, Who is the person you’re gonna sell to? Or what do they care about, I think then product, and then you go into the tech, and then finally, the competition everything else afterwards, right. But a lot of times people spend the first 10 slides on technology. And that’s really interesting, but as a secondary effect. First try to understand like, do people care? Will they pay for this and does it work? I think going through the sequence, and then talking about the AI would be really helpful. But if you’re an AI specific company, and they see too much of like the AI upfront, and that’s good, but usually ask the question like,”how is AI helpful?” Like it’s a tool in the toolbox? It’s not the and not.

Walter Thompson  21:20

A lot of founders I’ve talked to seem to have a lot of mental blocks or cognitive dissonance around calculating their total addressable market. For an AI startup, is there anything different or special about calculating TAM? Or is it still the same kind of traditional bottom up approach?

Vijay Reddy  21:37

I think a lot of times TAMs don’t exist in some use cases, right? I think you need to figure out, what can the TAM be if the market forces align right, I think, said a lot of cases when you look at the translation market, we’re just talking about this before, the software market for translation is not that big. But then if you take the human capital market, it is a $20 to $30 billion market. So then given the time very differently, than if we’re selling a software into translation company, right? So knowing who you’re selling to and how we can charge for it will help you address the TAM for a founder, a first-time founder. But for us, I think large markets, which are attractive and can support margins tend to have better outcomes then maybe larger markets don’t have margins or small markets which can go into large markets. So there’s some markets we stay away from because it doesn’t fit the profile for us. But when looking at a TAM, it’s good to do a bottoms-up and a top-down and just extrapolate to see what makes sense. What doesn’t make sense.

Walter Thompson  22:39

Jorge, if you were doing a pitch deck today, and you are a first timer working on your TAM slide, who would you show it to before you showed it to Vijay? To check your math and make sure you weren’t just totally, you know, out over your skis?

Jorge Torres  22:53

So as many people as possible. I think that is more than the order in which you show it to people. I think that investors, also their time is money, right? Like the amount of time that you haven’t days limited. And you don’t have that many kind of second, third choice, or shots with them. So what you want to do is you want to identify what are your most ideal investors, and save that to, once you’ve had feedback from the people that you know are not necessarily your most ideal investors, but they can give you feedback on those very initial things. Because every investor will know, if you’re far away from something that makes sense. If you’re close to something that makes sense. So, to be more precise, don’t wait too long to show it to an investor. It’s just that there are so many investors out there. And you can always strike and start with or like, well, here, I’m just spinning wheels to understand, you know, where the traction is happening.

Walter Thompson  24:02

In an idea-stage startup, there’s no social proof to validate your idea. We touched on this a little bit as I suppose but like, can you give some granular specifics as far as what are those tangibles? Like what do they look like when they’re actually like, oh, there’s a market exists for this, like, “even though I don’t know what the TAM is?” Like, what would that look like for you exactly as an investor?

Vijay Reddy  24:26

At this stage, in our AI Start seed fund, we don’t have Gartner top-right quadrant startups. There’s no Gartner quadrant in most of them, right? We don’t have in some cases, the TAM is not defined yet. The categories are not defined yet. And so what we tend to look for is, is there a buyer out there or customer enterprise, who has a really strong pain point, not a nice-to-have, a must-have and is the startup solving them? And we tend to usually do when you do reference calls, we tend to not look at how much revenue if the customer is charging or what the sales cycles are, but it’s more like, how big a pain point was that, and —

Walter Thompson  25:09

— this is the painkiller/vitamin mindset.

Vijay Reddy  25:13

That’s right. And also, how valuable is it for that particular user? So I think narrowing down on who your target buyer persona is, and then finding so much value, not one and a half x, but 10x. So there’s some, there’s lots of founders who really hone in on that and build a 10x better product. And that’s a good validation for us. And if it’s a larger company, and they see a 10x value, that’s even better.

Walter Thompson  25:44

It seems as though major AI players are commoditizing different products quickly, if OpenAI updates their product roadmap, that could create an extinction level event for the wrong startup. How are founders dressing this?

Vijay Reddy  25:56

So I think that’s recently, we’ve seen some companies where they’re trying to build products, which are built on top of other companies’ product lines, and there’s not enough differentiation if that company they’re relying on actually builds that. So for example, if you look at Slack, or Zoom, they have mass market reach. And so they have distribution. And they have data on which the startup is supposedly building a differentiated product. Now, the question you ask yourself is what happens if the companies that you’re relying on add a feature which, which is makes logical sense for them, right, and, and each time Microsoft comes up with a different feature, or Slack or Zoom, a lot of companies have to pivot really quickly, which you could have avoided, if you knew that you were in the line of fire. 

And so I think some founders are really good at understanding that “my core strength is in understanding the customer side of things, and I want to go and use this product in a very differentiated setting,” that’s okay. But if we’re just building a consumer product to go against Microsoft Word, using an AI bot, and if Microsoft adds that feature within the core product, your business has an extinction-level thing. So lots of founders are very good, I think, as Jorge mentioned, we know startups pivot, and that’s one of the things we’ll look at is how, how savvy are they to see market forces and then pivot their business? Well Ahead before they install it.

Walter Thompson  27:47

So if you are an early-stage, if you’re a seed stage idea-stage AI startup, how do you dig a strategic mountain at that point?

Jorge Torres  27:55

I think that the earlier you are, you shouldn’t be bought into a solution that strongly, because the solution is likely going to change, such as your understanding of the problem. I think that therefore, it is more important to be focusing on, “is this the right problem to be solving?” Moat is something that starts coming once you get enough data about the problem to then understand, okay, “what are the players that are working on this problem? And how am I going to identify Is there a cap here that I can get into, and that can be first player? And if I’m not the first player, then how are the people solving it inefficient, and I can solve it 10 times better, 100 times better?”

But if you don’t do that exercise in that order, you may be at the risk of solving a problem that either is not that big, a problem that already has players that can again turn you into an obsolete feature if you if you don’t do all this exercise in this kind of order. So the problem is the most important thing at the very early stage. Moat comes when you understand the problem, and you understand the players of the problem and their solutions. And then you understand the gaps. And if there’s a gap that allows you to be the first player, then your moat is to be always on the forefront. And if there is no gap, but there is just like, very, very bad solutions to the problem, then your moat is that you’re 10 times better or 100 times better than what is there to solve a problem.

Walter Thompson  29:51

Are technical founders better off with a nontechnical partner?

Jorge Torres  29:56

100%. I think that you will soon realize that a company is a symphony of many different instruments. You don’t go to a symphony to hear just one single instrument played by 20 people, you want to guarantee that even if there’s like people that have the same instrument that they’re playing different parts, but at some point, you need to add other instruments. Being very aware that a business is a combination of reading the market, going after that market, and then being able to build a product that can deliver. It’s a good recipe for success. 

And also, it’s a good recipe to understand that maybe those were there is a team and  one person has tendencies to be more driven for business-like operations, and then someone that has a tendency to be more technical, and to put together a solution — these stories can repeat themselves, like Apple is one great example of those, but you keep seeing very successful companies. And even if it’s not out of the founder’s states, you will assume that very early, these teams add someone who will complement one or the other.

Walter Thompson  31:15

Based on your own personal experience, what you’re seeing anecdotally, around how long is the typical fundraising journey these days from going out into the world with a pitch deck and then going home celebrating over a term sheet? What are we seeing as far as average timeline, roughly? Or is there an average?

Vijay Reddy  31:32

I think it’s a very wide range, right? Some companies can raise quickly, if they meet the right co-founder, they have product- market fit or idea-market fit, it’s fairly quick. In some cases, it’s longer, I think it’s, it’s less of a concern, if it takes a longer time, it’s finding the right partner that is more important. So even if it takes you longer, I would suggest looking for the right partner. And when I mean partner, it’s not the fund: it’s the actual people within the fund also. And it’s a huge range. within larger and larger quantities, this is people who will probably want to partner with these people who have completely different philosophies. So let’s say, trying to find the right person within that fund is as important as finding the raising fund itself. So it’s not a race in many ways, but at the seed stage, find the first set of founders who could be who have your back end have the same shared values.

Jorge Torres  32:38

Yeah, I think that one story that’s almost telling me that I think that is relevant here is for an investor, the clock’s start ticking from the moment that they make the investments. So it doesn’t really matter what happened before. In the sense of, if it took you some time to get to that point where you’re ready. The investor only cares like you’re ready now. And from now on, the clock is ticking. Therefore, what they’ve been looking at is more like, what is the vectors of growth that have accelerated in the past few months? If it took you something before that, a while even to figure this out, it doesn’t really matter that much, because their capital was not ever, like waiting there for something to happen. Therefore, my observations are these deals tend to happen very quickly once things are starting to move very quickly in one vector of growth in your company, because all of a sudden, there’s an inflection point. That means that you figured out something that makes your opportunity less risky. And therefore, when an investor sees this, they also understand that the opportunity for them has a limited window of time, because if they don’t get it, someone else will. And that’s the best type of view. An investor doesn’t want to be the only investor interested in a company, because you rarely find gold that nobody else sees.

Walter Thompson  34:05

And last question: I guess typically, for let’s say, a B2B SaaS startup, maybe 18 to 24 months of runway is the recommendation. If you were launching an AI startup today, in November of 2023, how much runway would you want after you closed your first round of funding?

Jorge Torres  34:24

I think that for me, it’s important to translate that into risk. So if you think that being concerned about money will deter you from making the right decisions, then you need to raise for the path of money that will guarantee that you can operate mentally. I think that there are entrepreneurs who are okay with 12-month runways and they’re cool as a cucumber. There are other people that cannot operate very well when that stress is upon them. So as a decision of risk, is more of, what will guarantee that you can succeed, if where you succeeding is, “I’m okay, so long, I have 12 months of runway, I’m okay, so I’m gonna have 24 months of runway.” 

And I think that that defines the behavior of a company, you start raising when you’re getting closer to that length. It is important that any round that you raise, in my opinion, has to be raised because of an opportunity, not because of necessity — it never goes well. So you have to guarantee that that timeframe that you have, is not putting you in the necessity for your own personal thing. Again, there are people who are okay, with very short runways, they manage to do it. And that’s fine. There are people that are not. So it just really depends on how you can operate a team. And again, when you’re early on, you may be okay with this, like six months, 12 months, 24 months. But as you start to have other people on your team, it is very important for them to know, “well, if I’m going to join six months on the road, I don’t want to be sweating bullets with you.” So different stages of a company also make that difference. And it’s important to be well capitalized, because it gives the people are going to join you that have the option to join somewhere else as well great awareness that they’re not going to be stressed for that that thing that is not the thing that they signed up for.

Vijay Reddy  36:25

The best time to raise capital is when you don’t need the money, and so at the seed stage, there’s this is notion from founders and VCs, that there’s a clock, it’s get 24 months and keep raising. It’s not right, I think, at the seed stage, you’re building a team, you’re getting a product to GA, you’re selling your first set of products to a customer, and then you realize maybe you have to pivot, right. And so you have to plan for that. You don’t want to learn from the get-go because you have an 18-month clock. But you have to plan appropriately to the risk you’re taking. And most founders don’t realize how many times you have to pivot before you get to a product-market fit, and that’s okay. So I think having enough capital to make those pivots, and not having to worry about doing bridges — it always takes longer than you think, to go get that first product-market fit. So I think having enough buffer and not being forced to go raise because your peers are going and raising at a faster cadence and usually see this. There’s three or four companies. This seems like a race, that if I raise quickly, and I keep going, I can grow faster. But you might be growing faster in the wrong direction and maybe going after the wrong customer persona. So I think being deliberate about which market you’re going first and then trying to add fuel to the fire once you know, it’s actually a better approach than just raising because you can.

Walter Thompson  37:59

Vijay, Jorge, thank you for a fantastic conversation. I really appreciate your time.

Vijay Reddy  38:03

Thanks for having me.

Jorge Torres

Thank you.

Walter Thompson  38:08

I’ll be right back with some show notes after a word from our sponsors. 

For the next episode, “Breaking into enterprise sales,” I interviewed Maria Latushkin, GVP of Technology & Engineering at Albertsons, and Jack Berkowitz, Chief Data Officer at Securiti. 

Maria and Jack are experts in enterprise sales. Both of them have years of experience working inside early-stage startups and buying software for Fortune 250 companies. 


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