The Search for Product-Market Fit - HBS Class Summary

To get back to the programming, I am so, so excited to introduce you all to Jeff Busking. He is general partner and co founder at flybridge Capital Partners here in Boston and a senior lecturer at Harvard Business School. Jeff has also been a really instrumental faculty mentor to the Black Tech Master Series initiative. And we today, as always, are super, super grateful for his support and his mentorship. So, Jeff, thank you so much for being here with us today. I'm super excited for this presentation from you and I will hand it over to you to introduce yourself.

Thank you so much, Kerry. It is great to be here. Just an honor to be in front of all of you once again. A year ago when I was with you all, it was one of the last meetings I was in face to face, in person. It was an amazing meeting. Pressing a lot of flesh, saying hello to a lot of people in a crowded room. Seems kind of crazy. Now here we are, all virtual, trying to do a similar thing. And that thing that I've been asked to do by Carrie and by Brian and the organizers of the Black Tech Master Series is to try to compress and synthesize my MBA class in 45 minutes. So I'm going to take a $75,000 tuition, rich academic experience and try to compress it into 20 or 25 slides and 45 minutes to try to tell you what we've been studying at Harvard on this question of the search for product market fit. It's a really amazing time to be an entrepreneur. I'm sure you all have heard this from many others. It's an extraordinary time. The markets have never been more robust. Financing has never been more available. We are seeing across our venture capital portfolio market sizes expanding far larger than we ever could have imagined. But the one thing that hasn't changed is the approach that the best founders take as they search for product market fit in trying to build their startups from zero to something from zero to create something of tremendous value from scratch. And so that's what we're going to talk about today. So if you could throw up the slides for me, we'll, we'll jump right in and I'm going to use these slides to, to talk about this journey and try to convey a couple really important messages. As, as Carrie was kind enough to say, my, my background, for folks who don't know me, in addition to being a venture capitalist and teaching at Harvard Business School, I was a former entrepreneur. And, and so I've had a lot of experience doing things wrong. And so what I'm going to try to convey to you has a lot of scar tissue behind it in terms of the right way to approach creating and building a startup. So let's just talk about the concepts that I'm going to cover in this session. I'm going to tell you about how to assess business models, because not all business models are created equal. In fact, if you're ever wondering why is it that some companies are valued at one or two times their revenue and other companies are valued at 20 or 30 times their revenue, I'm going to try to answer that question. The second concept that we're going to convey is the importance of the startup as an experimentation machine. What it is that you do in those first few months and first year is all about running experiments. We're going to deconstruct what product market fit really means. It's a buzzword that's thrown around a lot and as well as a couple other buzzwords that you might be hearing about lean startup theory and the customer discovery or customer development process. I'll try to deconstruct those and bring it to life. And then we'll talk about the best methodology that the top top entrepreneurs have found over the years to achieve product market fit and what metrics they're using to measure that. So that's going to be our agenda. Let's jump right in. So the conceptual framework that I'm going to begin with is something that's a page from your high school biology class or high school chemistry class, which is that a startup is an experimentation machine. What that means is, is that when you're building your startup, you want to think about running a series of experiments. And just like you learned in high school biology, you want to develop a hypothesis that will be the experiment that you focus on, the results of which will help determine whether that hypothesis is true or false. You want to collect results that allow you to learn to develop the next experiment and allow you to iterate really effectively. And the reason I convey this as a conceptual idea is that too often I see startups jump right in to thinking they know the answers to all the questions. They jump right into building a product, they jump right into spending money on their go to market and on acquiring customers, when in truth, you have to approach the early days of the startup journey with a tremendous amount of humility. And you have to think about that journey as being a journey of a sequence of experiments that you want to run to learn more and more about the problem space and about the customer and discover the value proposition that you're going to address. And so if you think about that conceptual framework and then bring it to life in terms of the business model of a startup, the most important question that you can ask yourself and that you can answer is what experiments should you run and in what sequence? And I'm showing you here my belief, my approach, which is that there are three types of experiments that you want to run and you want to run them in precisely this 1, 2, 3 sequence. The first is that you want to run customer value proposition experiments. You don't want to build anything, you don't want to spend any money, you don't want to jump in until you really deeply understand the customer needs and the value that you're going to deliver to them. And I'll say the word customer probably 100 times in this conversation. Know your customer, become intimate with your customer, understand the problem that you're that they're facing, and understand how your solution affects them. That's where startups really need to center their energy in the earliest days. One of the things I found with many of the companies I work with is they'll tell me two years in, three years in, we didn't understand our customer, or we changed who our customer was, or we changed the value proposition. All shortcuts that they could have avoided if they had really zoned in on that customer value proposition and running those experiments early. The second area of experiments is around the go to market. Once you've determined who the customer is and what the value is that you want to deliver, you then begin to experiment with how to reach that customer, how to intersect them in their moment of where they have the need that you're solving and how to convince them that you're the right solution and make it easy for them to buy. And then the final experiment type that you want to run is around the business model or cash flow experiments. What's the price you should charge? How do you figure out how to deliver that product in a cost effective fashion? And I would again submit you want to do these things in sequence because if you jump to worrying about business model and making money, you'll lose the magic of the earliest days of finding product market fit with customers who really care about what you're delivering. And as someone once told me when I was an entrepreneur, like, nobody cares about your stupid little startup, Jeff. Like you think it's the most important thing in the world to you, but when you're out talking to other people, nobody cares unless you can really convey a compelling value proposition. That's Not a little better than the current situation, but 10x better. That blows away inertia and really compels customers to jump on board. The second thing you need to worry about as you think about building your startup as an experimentation machine, is to instrument your machine and your organization to be able to run those experiments across all the relevant functions. You got to build your product team, build your growth team, build, build your sales team, and build your business development team and build it in a way that allows them and creates an environment where they can run experiments quickly and effectively. Because if you believe that startups are experimentation machines, the faster you run experiments, the quicker you learn. And the quicker you learn, the more swiftly you'll get to the right answer and find product market fit. So that's the scientific method that you want to, that you want to approach with, you know, researching the problem, developing hypotheses, running experiments, and then concluding, you know, what the right approach is for your startup. So that's the basic conceptual framework. Let's dive in now to a couple of constraints, because as we all know, you have really, you know, some important constraints when you run these experiments. You have only a finite amount of time, a finite amount of money. You have the team that you have, maybe it's just yourself and you have the particular strategy that you've created. And so the thing you want to do is, in the context of those constraints, design your experiments very thoughtfully and carefully. Because test selection is strategy. The tests that you run, the experiments you run, the sequence that you run them in really matter. And so one of the things we teach our students is to think strategically before you leap in, but don't overthink it like you do want to leap in and actually run experiments, face the customer, get the product out there in the wild. And when you think about test selection, you want to think about three things. First, which business model component is most controversial? If you unlock that, what value could you possibly create? What are the milestones that you need to achieve for people to believe in you, even more and more, for your value to go up in a non linear fashion? Because startups and value are not a linear progression over time. There are moments where you have a breakthrough. First customer ship or first product, first revenue, a major team hire, where you see these jumps in valuation and you really want to think about how do you run the right experiments that will cause those leaps? And then finally, where does the greatest risk occur? When you're talking to partners or to prospective employees, what do they seem hesitant about and how do you address those risks early on. So if you trust me on this one, that the customer value prop experiments are the most important, the sub thesis of that is that the most important thing you can do is really understand who your customer is. And there's something in customer discovery and customer development that is called the Persona, where you try to create a description of your customer and bring them to life. And that's called Persona development. And I'm showing you here a sample user Persona to bring that idea to life. This is a Persona that I grabbed off the Internet from a facility, a software company that was selling to facilities managers. And they would create a picture of this facilities manager and describe him, his background, his age, his academic experience, problems are, what his role is, and importantly, what his goals and challenges are. Because you really want to understand who your customer is, what their problems are, what they read, who they listen to, who are their influencers, and then you bring it to life with a picture, with a poster. There's a company here in Boston called HubSpot that some of you may have heard of. It's been an incredibly successful marketing software company, now public and worth tens of billions of dollars. Early on in their history, they developed these Personas. In their case, it was Marketing Mary. And they would poster their conference rooms with Marketing Mary and pictures of her. And they had pictures of her kids and pictures of her school, all fictional, all fabricated, but all to bring to life this important notion of who is your customer, to really understand their needs deeply and really develop an understanding of what their problems were. And one of the pieces of advice I give my students is to really define the customer in as tight and narrow a way as possible. So you want to start narrow with a smaller and smaller description of your customer. And it's not that you don't want to be ambitious. You all should be incredibly ambitious founders. You should be looking to build big companies that serve big markets. But to begin, you want to begin with a tight, narrow environment, because the nature of early markets is that the innovators, and this is a model called Crossing the Chasm, which was made famous decades ago by Geoffrey Moore. But the innovators are the ones you want to target initially, the ones who are willing to take a risk on a startup. It's a consumer customer, a business customer, whoever, whomever it is. But they're willing to take a risk. And the Airbnb founder, Brian Chesky has this great line which is it's better to have 100 people love you than a million people sort of like you. In Other words, when you're building your company and building your product as narrow as possible, just get a small subset of that target customer to think what you're doing is unbelievably valuable and unbelievably important. And then once you figure out how to solve their problem, you can expand from the innovators to the early adopters and then crossing the chasm, which I'll explain in a minute to the majority user. Okay, so what is this chasm idea? The chasm is at some point you can afford to be a little sloppy in your delivery of your product. The user interface may not be perfect. In fact, it may be a very incomplete product, as all of us have experienced with some of the early versions of now very well known and famous products like Snapchat and Twitter and even the Apple iPhone. Early first versions are clunky and awkward, but innovators will still enjoy that. But as you get to the majority, you need to build a more complete product. And the point here is that when you're a startup, it's okay to target the innovators. It's okay to have a product that's a little awkward, a little incomplete, but just get it out there and again, try to get 100 users to love it. And that's the essence of what are known as the lean startup principles. The lean startup principles are that you've got to get out there and run these experiments and put your product in the hands of users early on so that you can get that experience and get that feedback. And so the approach that you want to take is create what is known as a minimum viable product, an mvp. So the minimum viable product is the least amount of work that you can put towards creating a product that the users will have enough experience that you can test your hypothesis. It has enough features, enough capabilities that you can learn from the experience of getting users to use that. The minimum viable product allows you to learn from the user feedback and then adjust and iterate and build the key dimension. The key element here is you don't scale, you don't invest, you don't do anything until you nail that minimum viable product. In fact, I even tell people, don't write any code. You know, here's an example of this idea of business plan canvassing where you just write out the business plan and then build a prototype. Maybe it's a paper based prototype, maybe it's a. You use some tool like Figma or others to design a prototype, but you don't spend a ton of time investing to build Instead, you invest to test. The metric is, am I learning? Not am I creating a lot of revenue or creating a lot of users? Small number of users, large amount of learning. One of the tests to determine if the users are really taking up that minimum viable product, if they're really using it in the right way, is known as a 40% test, which an entrepreneur named Sean Ellis coined. And the 40% test, Sean said, is that you ask the users after they've experienced your product again, even if it's a hundred of them or a thousand of them. You know, would you be deeply disappointed if I took the product away from you? And you can just imagine that in your own life there are products that you use. Think today. The apps that you look at when you wake up in the morning, or the favorite products that you experience over the course of your day. If those were taken away, would you be very disappointed, somewhat disappointed, or not at all disappointed? And the 40% test is if more than 40% say they would be very disappointed, you found product market fit. If most of the people really care that much, then you've got a nice to have product, a must have product. You have a product that you know if you put it in front of somebody and give it away for free, they'll use it and enjoy it. But you don't have a product that's core, that's core to their experience, that's incredibly valuable and that they can't live without. And that's really the objective that you have. That's the dynamic of the value prop experiments and determining the who. And then you really think now about the what. What is it that you're delivering to them? And again, don't write a lot of code, don't spend months building. Really take your time to run these tests and get a deep understanding of what problems you're solving. I was talking to a CEO just a few weeks ago who said to me something incredible. She said, you know, Jeff, I've been running this company for 10 years, and I finally now understand who my customer is and what pain I'm addressing. Ten years, tens of millions of dollars later. Don't be like her. Figure it out sooner. Okay, so now when you get into the mode of building, building the what, you have to deploy what I refer to as design thinking, which is a methodology that Stanford created that involves a very rigorous process of customer discovery, this iterative process of really understanding and empathizing with the customer and defining what they're looking for and what their problems are and beginning to test them. And I think the best example of this is an example I heard about from many years ago, which is how Intuit does their design thinking. In the days when software was sold in retail stores, in the days when we used to go to retail stores, Intuit would send their engineers and product people to the retail store, and they would watch consumers pick their software packages off the shelf, put them in the shopping cart and check them out. And then the engineer and product leader would approach the customer and say, hey, I see you're buying TurboTax or Quicken. Do you mind if I follow you home and check out how you use the product? They called it the Follow me home program, which sounds incredibly creepy. I'm not sure you could do this in 2021, but in the early days, they would actually go home with the customer and watch them open up the software box, install the software, and begin to use it. And the reason that's such a powerful idea is it puts the product designer, it puts the engineer, the entrepreneur, in your case, right. Face up close to the customer and watching how they interact with the product. And so it allows them to really empathize with things that maybe seem clear to you as the designer, but are not clear to the customer. Placement of the interfaces, design of the buttons, or the language, all of those things that they can now smooth out and get experience with. So that's the approach, design thinking and customer discovery. All right, let me jump ahead now to the go to market experiments. Now that I've covered in a rich way, the customer value prop experiments. So in the world of go to market, once you feel like you've got a pretty good customer value prop, and once you feel like you've got a pretty good sense of what you're building now, you want to test that by getting out into the market, and you want to run a bunch of hypotheses. You want to test the initial market, you want to test the sales model, choice of channels, and the growth engine. And one of the things that I encourage my students to think about very strategically is initial market selection. In approaching initial market selection, and this is from a book also by Geoffrey Moore called Inside the Tornado. There's a metaphor that I find very useful, which is the bowling alley metaphor. And the initial market that you pick, even if you have grand ambitions to build a massive company, the initial market is your head pin. It's the first thing, the first segment, and the first application. And so when you pick that head pin, you know, in the case of Snapchat, that head pin typically I think as you look back on the history of Snapchat, were teenage girls who wanted to share photos of each other, you know, what was going on during the course of their day, or maybe what they were wearing to school that day. You know, picking a narrow segment and a narrow application. In the case of Facebook, the initial segment were students at Harvard University who were wanting to connect for social purposes. Then they expanded, they expanded to other universities, and they expanded to grownups and old people like me. And then they expanded from there globally. So you think about that initial market selection. It's really important to pick an initial market that's going to yield a good outcome for you because it's going to allow you to discover these really important elements. First, you want to pick an initial market that's consistent with your mission or passion. Don't pick a market that you're not excited about. We have a founder that we study in my class who is looking to create synthetic palm oil. Palm oil is a very dangerous, environmentally dangerous product. A lot of trees get knocked down throughout Latin America, South America, Southeast Asia, huge environmental problems. And she invented, with a bunch of MIT scientists the ability to create palm oil synthetically. But how does she insert herself into the value chain? And what first market should she pick? And one of the things we discuss in the class is her mission is to save the planet, but to get into the game. The first market she picks is a cosmetics product. It's a cosmetics product because it's small batch, easy to make, high value. So even though her manufacturing is very inefficient, she has good coverage from a price standpoint. And so being really thoughtful and strategic about picking these initial markets that allow you to build enough proof points and create enough value to build out your operations and build out the capabilities for the ultimate goal. And one of the things we also talk about is different sales models for different types of customers. And this is a little bit thinking about the B2B context, the business to business context, more than perhaps B2C. But if you think about the average revenue per account, which is my X axis here as compared to number of customers, my Y axis, naturally, and this is a log scale, naturally, the smaller the revenue per customer, the more customers that you're going to have. So if you're charging, as you see in this first column, $100 per customer, you could have millions of customers all the way. To the other extreme, if you're charging, charging a million dollars per customer, if you're trying to sell to whales, then you may only have 100 of those and thinking about your sales strategy across each part of the chain and your model, your go to market motion, and your sales model. So thinking about your pricing and thinking about your go to market is really critical. But one of the most important things I tell people in these early days is that founders should lead the way on on selling. It's something that is known as the sales learning curve, that as a founder, you have to sell yourself personally so that you can personally get down before you can build a sales team. One of the big mistakes I see founders make early on is they outsource sales. They say, well, I'm not a salesperson. I'll hire a salesperson who's got a ton of experience. They'll come in and they'll help me down the learning curve. And that's a terrible approach. What you really want to do is sell yourself personally because just like with value prop experiments, go to market experiments only the founder can really understand and appreciate, and so only you can learn the art of selling. One of the companies that we study is a company called Ovia, led by Paris Wallace. And Ovia is a product for women who are attempting to get pregnant. It's a mobile app. And over time, what they discovered is that the real customer for that product were employer health plans because they would reduce high risk pregnancy and therefore create a tremendous amount of value. And so the founder, Paris decided, okay, I got to go sell health plans and employers on this model. And so he personally went out and did the selling, which worked great. He made good money, he got some sales. And they said, okay, well, I don't really know what I'm doing in selling. I'm not a salesperson, as you know by background. Let me hire a senior enterprise salesperson to come in and take it over. And that was a disaster. And the reason it was a disaster is he did it too soon. He hadn't really figured out the formula. He was only dealing. If you go back to the Crossing the chasm model, he had discovered the innovators, but he hadn't really understood the early adopters and the early majority. And so until he got into it himself in more detail, not just closing one or two quick deals, but really living in the market, he couldn't hand it off to a professional sales team. And that's what's really, really critical in the go to market experiments. There are two schools of thought on pacing when it comes to scaling. And there's sometimes characterized as the east coast school and the West Coast. The west coast school of thought, which is pioneered and popularized by Reid Hoffman, the founder of LinkedIn is blitzscaling, and Reid wrote a book of that title. And his thesis is that startups are all about growth and that you've got to use capital and your execution capacity as a competitive advantage and drive scale as quickly as possible. Now, Reid admits this works best in businesses that have strong network effects. And for those of you who don't know, network effects mean that the value of the company increases exponentially with the value of the network, that a service is more valuable if more people are on it, Snapchat being a great example, Facebook as well. Those services are useless if only five or ten people are there, but incredibly valuable if all your friends are there. In network effect businesses where scale matters, where it feels like winner take all, you want to scale quickly. All the things I just taught you about with regard to iteration and experiments and careful growth and figuring it out, at some point when you begin to see the early signs of product market fit, when you feel like it's getting easier, when you're passing the 40% test, when people would be really disappointed if your product disappeared, then you really want to press on the gas and scale fast. That's the Blitzscaling school. The avoid premature scaling school is, you know, you really want to be careful about wasting capital, waste wasting time, be more careful about hitting product market fit, and even then pace your scaling. Because when you build a business, you want to build it with a solid foundation. Those are two very different approaches. And what I would tell you is that neither is right or wrong. There are elements of both that are absolutely right and are dangerous and absolutely wrong. And it's really a question of your business. As I said earlier, if you have a strong network effect, then scaling may make more sense. If you don't, then it doesn't. All right, now let's get into business model and this is where we're leading into some fun math elements of business models and startups. The thing that I really want to convey here is the importance of understanding your unit economics. Eventually, once you know the value proposition of the customer and once you figure out how to reach that customer with the go to market, you've got to nail your LTV and CAC math. LTV stands for lifetime value, also sometimes referred to as customer lifetime value. And CAC refers to customer acquisition cost. Lifetime value means the discounted present value of all the profits that you earn from a customer. And the actual acquisition cost is how expensive is it to acquire that customer. And the key when looking at lifetime value versus customer acquisition cost obviously is you want the value to be meaningfully greater than the cost. If you're giving away a dollar, it's really easy to build a business. One of my students like to say, if I stand out in the quad and give away burritos and everybody lines up, that's not product market fit, that's just giving away burritos in the quad. What you want to do is obviously build a model and a business and again, wait until you nail the value prop and the go to market before you worry about this. But nail the unit economics and in particular create a magical business model. And this slide answers the question why are some businesses worth 20 times revenue and some worth only 2 times revenue? You want to have, you know, a really tight viral loop, strong network effects, recurring revenue, so the customer comes back every year like in a subscription business or a software As a service SaaS business, high gross margins and metrics that are improving with scale. And I'll give you one example. We have a storage and client content management software company that is called Nasuni, name doesn't matter. But every year their customers use more files, store more stuff and pay them more. And so we could literally fire the sales force, cut the entire marketing budget and every year we would still grow 20% a year because our customers are using more of the product. That's a magic business model. So you want to have these business models that just keep cranking. And that's why if you look at why is Google worth over a trillion dollars? Why is Facebook so valuable? Why is zoom so valuable even though we're using obviously hopin? It's because those business models have these compelling network effects and this recurring nature and this benefits of scale and that's why they're so much more valuable than businesses that don't have it. And so when you sort of boil it down, the metrics that matter for product market fit is if your lifetime value is not just a little bit better, but a lot better than your customer. Acquisition costs three times better is sort of the magic number that people throw around. If Your recurring revenue MRR stands for monthly recurring revenue is growing rapidly, 10% a month is sort of a standard fast growing metric. If you have little churn, if you're seeing your customers stick around, if your net promoter score, which is known as the amount that people would recommend your service is in the 40s or 50s. And if your sales team is really working and you're passing that 40% test, well, you do all those Things, guys. Then you have product market fit. And that's really the essence of this journey. The final essence of the journey is product usage. And I'm going to show you something that a woman named Sarah Tavel created which I think is a spectacular framework called the hierarchy of engagement. And then I'm going to end here and take questions from Brian and Carrie. But you know, as users engage, you want to, you want to have them move up the hierarchy and begin to exhibit the behavior that creates this self perpetuating model. Growing users and then retaining users and then having them be self perpetuating. You want to avoid the vanity metrics of people who just download your product or app and never use it. Instead really measure carefully usage and use. So I'm going to stop there with the prepared remarks. You can stop screen sharing. Thank you so much, Brian. You're welcome to come up or Carrie. Thank you. Hey Carrie. And let's have some conversation and take some questions. Thank you so much.

Yeah, let's jump in. Well, Jeff, first of all just want to really thank you for the session. Looking at the chat, folks are just getting so many gems and nugget, nuggets of information. So this has been awesome. I'd love to start by asking you how does your having been an entrepreneur influence your thinking as an investor and specifically what might have been blind spots you could have had had you not also been on the entrepreneurial side of this ecosystem?

Yeah, it's a great question, Carrie. First of all, I made so many mistakes as an entrepreneur. I mean, both of my companies ended up being successful, but they were both really bumpy along the way. And I think that's something that's very true. I call it the TechCrunch effect. The articles look great in TechCrunch, but under the hood there's a huge amount of paddling and chaos and churn. And I just, I made a lot of mistakes that as an investor I don't have any better perspective on. One is I made bad hires. I would hire people because of their pedigree or their resume because I was a young entrepreneur and I wanted senior people around me to cover for me. That's a huge mistake that I try to coach entrepreneurs about. If you want to build a company, it's okay to start with younger, inexperienced people. I'm not ageist or, you know, biased in any way, but people you don't have to stretch for the big company experience. It's better to have scrappy culture early on. And then you know this point about experiments Every experiment that I ran as an entrepreneur was 10 times more expensive than it needed to be and way more complicated. I would just overthink things as opposed to just keeping things really simple and focusing on the very narrow problems that I was trying to address and get answers to.

Gotcha. Super helpful. So a lot of folks on the line today are non technical founders. So I'm curious what are particular challenges in testing and design that folks who are non technical might run into and what are some good workarounds you've seen if you yourself aren't an engineer?

So paper prototypes, HTML prototypes, learn some of the tools like Figma and invision that allow you to prototype things. And I would say learn basic front end coding. You don't have to be this amazing end to end full stack developer, but just learn how to do some simple HTML work and JavaScript work so you can put things in front of customers. I'm doing a case right now on Squire. People may know that company is this amazing company that's doing barbershop appointments and become this powerhouse now worth many hundreds of millions of dollars. And in my interviews with the two founders, Dave and Song, they talked about the fact that they weren't one was a lawyer, one was an MBA dropout. They didn't know anything about coding, they screwed up everything from a coding standpoint, but they hustled their way into finding and building a basic application, getting in front of the barbers, getting their feedback and iterating successfully from there. So that's my advice.

Great. So thinking back to this year, particularly at hbs, something I really admired about you is this new course Scaling Minority Businesses that you led. I was wondering if you could just tell the group a little bit about that course and what you've learned about working with diverse founders and particular insights they might have to markets and the real value of the founder pool growing into being more diverse and accessible. So we'd love to hear about maybe some interactions you had in that course that opened up the way that you view certain markets that you haven't known before.

Yeah, thank you so much for asking that question, Kerry. You know, in the wake of the murder of George Floyd, two fantastic faculty colleagues and I, Henry McGee and Archie Jones, teamed up to create this course Scaling Minority Businesses where we brought students proximate with 10 black owned businesses in the Boston area to help them with their Covid recovery efforts and also their scaling efforts. And we learned a lot. I learned a tremendous amount about systemic inequities in access to capital and access to Customers and opportunity. And one of the things that I really took away from that course, in addition to what you hear about with regard to resilience and what have you, is that we're in a moment right now where there are extraordinary large forces moving towards helping black and Latinx founders. Whether it's dramatic changes in my industry, the venture capital industry, which were long overdue, whether it's institutions like Harvard having a reckoning themselves with regard to the environment that they've created unknowingly, you know, whether it's conscious bias or unconscious bias, and whether it's large financial institutions and owners of wealth and capital like bank of America and JP Morgan, Citibank, on and on. And, you know, I've talked about this, you know, with you and with a number of your classmates. This is an amazing moment where there's a network in an ecosystem to support black founders that never existed. There's always been a lot of intrinsic support, of course, but now the amount of allyship and openness that exists right now is extraordinary. But nothing's going to be easy. There's still going to be obstacles and roadblocks. And I know from talking to some of the participants in this course, procurement biases and obstacles, fundraising biases and obstacles, they still exist. But I would say this is a moment where there's an opportunity to break through them in a way that has never been before. And I'm very excited about that. Awesome.

And we're super grateful for your partnership and in these efforts. I think where we want to end today is just zooming out, looking at, looking at your career in your field. Folks are really curious to know what motivates you and then more broadly, who inspires you in terms of founders, other investors, other sources of inspiration, what keeps you going, and specifically, who do you turn to for that inspiration?

Wow, that's. You're going deep on me, Kerry, on.

Sunday morning to keep it light.

So, you know, people may not know my personal background, but briefly, my father was a survivor of the Holocaust and came to the US after seeing a democracy fail. And that's always been a tremendous inspiration to me in terms of my passion for social justice and for civic engagement. I think this world of entrepreneurship is an amazing tool for impact, and I love being a part of that ecosystem, just being a contributor to this world of impact and using the power of capitalism and entrepreneurship for change and for good. It's not always a tool for good. But, you know, if you're on this, if you're on this conference, and if you're passionate about tech entrepreneurship, you probably feel the same way. And boy, there's so many role models. You know, for me, Kerry, one of the one things I'll say though is my, my current view is that the, the black leaders in venture capital and entrepreneurship are really stepping up and are extraordinary role models. And I hate to name check, but I'll do a few. You know, Elliot Robinson at Bessemer has just been an incredible leader who I love listening to and watching a number of the entrepreneurs that I work with, like John Belizer, Mara Lydy at Shine, Sheree Robinson at Tastemakers Africa. You know, these are founders that we've invested in that we think the world of. Lolita Taub, who is a very powerful Latinx founder and an entrepreneur and investor who we've partnered with to create a fund for underrepresented founders. Monique Woodward has been very powerful leader and thought leader. So I've just enjoyed learning and listening to to them. I think one of the themes that I've been on lately is trusting black people with wealth and power in a way that, you know, maybe those that our society and our community hasn't done before. And.

Well, what a note to end the session on. Jeff, as always, we really, really appreciate your being here and your partnership on this work. Thank you so much. We learned a ton and really appreciate your time. All right, folks, we have made it to lunchtime, so Brian, I'm going to bring you back to preview.