"The thing about technology is that it’s just an accelerant. Like when you think about, when you think about the purpose of technology, it’s really, it is a tool and it’s to help us do work, to help us accomplish work, whether it’s a very simple tool, like a wheel or a ramp or a pulley, simple machines that third graders learn about in science class, that’s real technology that once upon a time completely changed the game in terms of construction and transport and so on. We don’t think of it as technology much anymore, but you go back in time to Bronze Age or pre-bronze age, very simple things were high tech at the time."
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Jesse: Welcome to the smart athlete podcast. I’m your host, Jesse Funk. My guest today has his master’s in computer science, where he originally was in the air force Academy, he was a Lieutenant, that’s where he kind of started his early career in computer science. He’s gone on to be the author, I think now in the third edition, hopefully he’ll correct me here in a minute, the third edition of Mining the Social Web. He’s also the founder of two software’s and service companies; Throwdowns and strongest AI. Welcome to the show Matthew Russell.
Matthew: Hey, glad to be here. This is cool.
Jesse: Matthew, did I get that correctly it is third edition of the book right now?
Matthew: Yeah, it’s in the third edition. It sure is.
Jesse: So, the first thing I have to ask you was just something, that skeptical mind from college, you probably had similar thoughts when you were there. When new editions of books come out, I think it’s particularly a culprit in textbooks because I feel like that’s a racket. Your book is not nearly as pricey as a textbook. What are you actually doing when you’re coming out with subsequent additions? You know, what’s the purpose of making those updates?
Matthew: Yeah, that’s a great question. So, different authors and publishers are probably going to give you slightly different answers. So, for me with Mining the Social Web, the way the book came about was that, so you could go to pre IPO for Facebook, Twitter, etc., right? That the social web was just this new construct, it wasn’t even obvious that it was really going to catch on maybe to a lot of people at the time, like call it the two, 2006 ish timeframe or so, give or take.
You know, I started to look at it closely and thought, “okay, there really is something big here.” And my background being in computer science, data, analytics, machine learning, I was very interested in the data more so than the user experience or the current incarnation of product. And so, I wanted to write a book that taught people how to get access to that data, how to really wrap their arms around it, make sense of it and then start to solve problems with it in a color by number kind of way.
So, version one of the book sort of took a snapshot of the social web as it existed around the time it published, took the easiest and best to use technology to help people make sense of the data. And I’d written some books before this. So, I had a little bit of practice in terms of publishing a large written work, but the book itself you know, it was a little bit messy, there was just a lot to cover and a lot to sort of put together, but it turned out pretty good.
The second edition for me was a complete rewrite, because the second edition for me was the opportunity to write the book that I wished that I would have written the first time around. So, I wanted the second edition to be, you could cherry pick any chapter and it told you a great story, you could read it from cover to cover and it was a nice cohesive story with a nice crescendo and increasing complexity as you built one chapter on another. And, of course, we refreshed the tech that you could use to get your arms around the data and so forth.
That was a pretty big success, honestly, the second edition. I treated it as a product. So, I sort of looked at it as an entrepreneur and said, okay, how do I think of this as a living breathing product? How do I engage my audience? How do I acquire readers? I didn’t just throw it over to the publisher and expect amazing things to happen. You know, I really hustled in the marketing side of the book and that worked out pretty well.
And so, with the third edition we didn’t really rewrite the book, but we did take sort of the same approach. We said, “what’s changed with the social web? what do we need to do to refresh it?” So, we updated some of the technology, we added a chapter on Instagram which had become a big thing since the second edition had published, updated the tool chain to make it a little more accessible based on things we’ve learned.
And brought on a co author, a really, really great guy who was able to do a lot of the work with me. And you know, he was, he was just a blessing to have involved because it’s a lot of work to write a book, but it’s a lot of work to refresh it and really do it the right way. It wasn’t just fixes or something like that, there’s a lot of work involved.
Jesse: I can’t recall off the top of my head, whether it was a blog post that you’ve written or your coauthor. But I do remember a mention of the difficulty in putting together a book because publishing schedules are so much longer and take so much more time compared to the speed of software development and deployment.
So, how do you match that? How do you how do you keep up with the constant changes? Obviously, some of the minutia is going to get lost as we make minor updates to the platforms, the various platforms you talk about. Is there any way to— Do you take broad strokes and say, this is kind of what you’re looking for, regardless of whatever interface or set up you have at the time?
Matthew: Yeah, I think like the phrase that comes to mind as you’re talking about this is just the publisher’s tool chain. So, there’s a lot of ways you can go about writing a book. You could write it all in TXT files, you could use Microsoft word, you could use a doc book editors. There’s a lot of different standards and a lot of different tools that can make the job easier or harder. And some of those tools depend on your preferences and just the way you like to work, what you’re used to, what’s efficient for you based on your skills and experience.
So, the publisher that I’ve written, all of my books with as a partner is O’Reilly media. So, pretty, pretty innovative organization. You know, Tim O’Reilly is sort of known as a very forward thinker, very future oriented, and he’s right about a lot of the things that he predicts. And so even though publishing sort of traditionally is looked at as a little bit of a sleepy industry, I think there’s a lot of innovation within O’Reilly and I’ve seen some of that firsthand.
So, the tool chain that that was used across all the books that I wrote, I saw that evolve and get a little more efficient along the way, because on some level you just have to realize you really are just building a product. I mean, a book is a product, and like any product, if you have better tools for the job, there is efficiency to be gained, you do have to learn how to use the tools or they won’t be as efficient for you. But usually that upfront learning curve is going to be worth conquering because it will pay for itself.
So, for me, coming from a technology background, I took a really close look at automation and just all of the ways that I could streamline the process. So, for me, it was not an authoring process in Microsoft word or some type of point and click editor. You know, I was working more with like abbreviated text formats that I could write some scripts and move code examples in and out of the pros, run automated tests on my code examples. All of those things that would be very difficult to do with a more traditional tool chain.
Jesse: So, thinking about the book in particular. For me, the broad question is why should we mind the social web? And, this is obviously two different questions, should we mind the social web? You know what I mean? So, the ethics of it, and then also in practice, what’s the purpose? What do we get out of it?
Matthew: Yeah. So, there’s a joke about the internet, it was just this idea that you know, how could the government convince everybody to put all of their personal information out in the open and make it very easy to surveil every activity every minute of every day? And what do you know, they came up with this idea through DARPA for the worldwide web, right?
So, it’s a bit of a joke that you think about the reality of that. I mean, the data’s out there, somebody is mining it, and you can either be aware and informed and familiar with the possibilities, whether it’s for curiosity sake or whether it’s because you want to use that to make certain privacy decisions for your own life, or maybe you do have a business model that just fundamentally could depend on it.
What if you could find lots of data exhaust all over the internet that people are readily publishing about themselves, find a way to aggregate it and wring out some really valuable information. Maybe that’s for profit, maybe that’s for social good, maybe that’s for combinations thereof. There’s always going to be someone that’s going to do that for nefarious purposes or selfish purposes as well, it’s just the nature of the beast.
But I would just say it’s one of those things if you are a consumer of social media, if you are a participant, if your children or family members or anyone you care about is a participant, I think there’s just an intellectual curiosity of what’s really out there and what’s really possible to do with it as a starting point. And then beyond that, when money flow gets involved then all sorts of other motives can also become involved and usually do, and the stakes get high sometimes with all of that.
Jesse: Sometimes I kind of think about it. Like, I mean, it’s all a tool, right? Let’s take a hammer for example, and this is a little bit obtuse example, but I mean, a hammer is a tool, so I can use it to hammer nails, which is its intended purpose. I can also bludgeon somebody with it. it’s not necessarily the Hammer’s intention to bludgeon somebody, but it can be used that way.
So, I think when I have this conversation with people, it’s kind of as you mentioned, there’s always somebody that’s probably going to have less than honorable intentions with a tool. And this may be simply the naive optimist that I am, but I feel like generally speaking that’s not the large case use. I feel like the majority of people, vast majority really are using tools to build and create something positive, to try to impact people in some form or another.
Matthew: Yeah So, the thing about technology is that it’s just an accelerant. Like when you think about, when you think about the purpose of technology, it’s really, it is a tool and it’s to help us do work, to help us accomplish work, whether it’s a very simple tool, like a wheel or a ramp or a pulley, simple machines that third graders learn about in science class, that’s real technology that once upon a time completely changed the game in terms of construction and transport and so on.
We don’t think of it as technology much anymore, but you go back in time to Bronze Age or pre-bronze age, very simple things were high tech at the time, but any very simple thing you can use it for any purpose.
I have a very classical of humanity, I sort of look at humans as humans haven’t changed very much in a very long time, technology has, that’s kind of the point. And so, what we are able to do today with technology is just sort of the inevitable outcome of who we are as humans and our motives and our actions when it becomes easier and more accessible to do all of those things. You know, whether it’s travel from point A to point B, at some point you had to walk or run, and then eventually you could ride a horse, and eventually you could maybe get in a steam engine and ride up and down the river, and eventually an automobile and eventually a rocket or a plane and so on.
That’s pretty profound really, because once upon a time the theoretical limit of where you could travel to from point A to point B, it was just like a fixed possibility. It’s a very different number today than a hundred years ago. Completely different. And then you just think, “what’s the impact of that? What happens when that becomes economical and accessible and nearly anyone can do it?” To me, that’s just an example of technology. Like, transportation’s the easy one that just kind of intuitively anyone can grok that, but yeah, whether it’s the hammer or the computer, or a fitness app, whatever it is, it’s just a way to do work.
I think technology automates work or augments work. So, in automation you think of AI in general and all the we hear about that, there’s at least two really clear use cases, broad, you can automate work which humans shouldn’t do in the first place because maybe a machine really can do it better with more consistency, more accuracy, where there’s augmentation.
So, there’s a unit of work you really do want a human to do it, at least for the time being, but technology can accelerate or scale that human talent to a multiple, maybe 10 or 100 times more work by a subject matter export, or a well-trained technician of some kind could get something done. So, two different use cases for, as we start to go from analog to digital and thinking about technology.
Jesse: The augmentation makes you think about, I don’t know if this is a literal example, I think so, but it’s talking about improving the efficiency or the efficacy of a single worker in— I think the example I saw or recall was talking about law offices. And so, you have the lawyer in charge and then they used to have a number of people under them that would have to be going through texts to find all of these different things.
Well, with the digitization of all of this information and the ability to perform a Boolean search to say, “Hey, this is what I want to find.” You eliminate all that kind of redundancy or human labor needed to find all these specific cases you can get to it much, much faster than you would have previously. So, in both cases, it seems like you’re reducing human labor.
Now, I don’t know that I have a hard stance on this at this point. So, I’m curious, and this is kind of where you exist in software development, I’ll say for lack of a better broad term. But I’d kind of like your thoughts on, is it actually doom and gloom when we’re replacing people for using software or machines to automate or augment jobs, or is it a matter of we’re simply shifting where human labor is needed?
Matthew: Yeah. So, I think what we’re seeing is, I think this pattern has been in place for a very long time. And so, to approach the question, as we think about the world- Like, I think our human brains are really good at linear predictions. So, if it took some unit of time to do something, we can sort of do that multiple on the mental math and sort of imagine, “well, yeah, if it took a year for something to happen, then in two years here’s probably where we could be with the possibility.”
But the thing about technology is that it’s not a linear problem, there’s sort of a nonlinear acceleration, and I don’t think we’re very good just as humans at predicting nonlinear curves. And so, when we when we think about the world today and the digitization of so many things, it’s a little bit harder to grok what’s going to happen a year from now. It’s very tough to look back at the progress in the previous 12 months and make a good prediction about the next 12 months.
But I do think if you look back, you do see that curve. And so, to start to approach the question a little bit, I don’t really think what’s happening with AI personally is a fundamentally different with all of the hysteria that sometimes comes along with it, especially from some of the leaders in the space that in some way have a lot of incentives for their perspective to become true because of investments, because of money flow, because of what they want to be true.
But I do think that it’s just a tool that can do a job. There are certain types of precautions with any technology that we should take, AI is just another example of that as well. So, if you go into a factory maybe you’ve got to put on a hard hat and you don’t stick your finger in the conveyor belt, right? It’s a safety for caution. If you go in the nuclear power plant, it’s maybe a little more high-tech than a factory, and you might have to put on a special radiation shield of some kind and not get within some proximity of the reactor.
Well, with AI I think what kind of scares people is that it doesn’t have that same kind of physicality in the abstract, and there’s a lot of sci-fi, and a lot of sci-fi becomes true sometimes, at least the survivorship bias of the good Sci-fi makes you think that way. And then you sort of let your imagination go to wherever you want it to go, or wherever it naturally goes. Like I do understand the fear of technology going wrong and what’s possible. But as a practitioner in the space I don’t lose any sleep over it myself. I have a very tough time worrying about Terminator scenarios and that sort of thing.
I’m not saying that’s completely out of the realm of possibility because I don’t think it’s out of the realm of possibility given enough time, given enough money, but in this decade I’m not worried about the kinds of things that Ray Kurzweil might lead people to believe they should be worried about.
Jesse: It seems like sometimes— I guess I’ll say from a personal standpoint I try to divorce myself a little bit from news and even social media recently. Because I think if you look— I go back to look at the money and the saying, if it bleeds, it leads, right? Like that’s what grabs our attention. So, if you think about the economic implications of if news outlets and those kinds of media agencies we’re only trying to give a real, more balanced perspective of the reality of the situation, well that’s not interesting, it doesn’t catch our attention. But you know, an Arnold Schwarzenegger Terminator coming down the street to get us because Matthew’s AI went rogue, well now I’m paying attention.
And to couple that with now I work in the digital space, because I mean, e-commerce, eyeballs are the new currency, there’s a lot of people that refer to it as that. So, it’s like, if we can keep your attention, that’s how we make money. So, sometimes I think about it with that, and how it kind of preys on, I’ll say humans in a general sense, our tendency to focus on the negative instead of trying to look at the realism of the situation.
Matthew: Yeah. Well, when you think about what sells and there’s this adage, “you can sell against pain, pleasure or peace of mind” those are three really broad categories, and on some level you think about all of the marketing messages you ever see and they’re just appealing on that emotional level, whether it’s very direct or very indirect, to one or more of those motives. And there no doubt that if there’s something that might scare you and affect your peace of mind, that won’t sit well with you and by definition it’s going to take up some space in your brain for a while and you’re going to come back to it.
Or if there’s something that is causing you pain today, same idea, and in B to C of course, pleasure, well, that’s what everybody wants to buy. We don’t buy what we need, we buy what we want. And we want pleasure.
Jesse: Yeah. And that’s the thing, that’s the other thing. This is a side note, and because you’re an entrepreneur, you know this. But for you, the listener, we like to pretend that we buy things for rational reasons, but we buy them for emotional reasons and we rationalize after the fact and that’s where copywriting, which is all the sales text you read and those kinds of things come into play. And as Matthew mentioned, it’s appealing to those things.
When you think about a concrete example like security systems, the texts that you’re going to read is trying to scare you a little bit, because when you’re scared, you’re going to be more likely to purchase that security system because it’s going to give you the feeling of being secure and not being afraid anymore. So, there is a both a— and I’ve mentioned this other times on the podcast, but there are a light side and a dark side so to speak of sales and kind of appealing to those things in spaces that aren’t even necessarily like security, or as you mentioned, in AI where certain people might have motives to scare you versus giving the reality of the situation.
Matthew: Yeah. Most of my professional background has been in the B2B space where you have a clear buyer and there’s a real business decision, and there’s a real problem with real pain and a real solution, sort of a very rational needs-based, cost benefit analysis. But yeah, in the B to C space, totally emotional in nature and very much like, “do I want it?” And the rationalization really does come after.
Jesse: Yeah, it seems like in B2B, business to business for the listener if you don’t know what that means, and B2C is business to consumer, or direct to consumer, I might also say that. With B2B it’s like if you’re selling me software for my business, all I’m concerned with generally speaking is will it save me time and will this produce more money than it costs me to pay for it? You know? So, there’s obviously a pain there, I want my time back, I want more money, but it’s not a matter of you’ve got to scare me. It’s just, do the numbers work? Let’s do it. It doesn’t involve all the extra coaxing and convincing that sometimes consumer goods need.
But thinking about that, you are kind of— Well, you’re a little bit in B2B, but in some ways I would say you’re kind of in this hybrid of B2B, B2C now with throwdowns and strongest AI. So, how do you get— I guess, take me back a little bit. You’re in the air force, when did you get into CrossFit? I have to give you a hard time, why did you leave Triathlon? I mean what else do you do need? You get three sports. But how do you get to where you are now in that space? I’m assuming that’s probably connected to getting into these software and service companies.
Matthew: Yeah. So, after some time in the military I started to work as a computer scientist in the private sector in data and analytics oriented roles and got involved in an early stage software company building some pretty cutting edge technology at the time for understanding natural language.
So, how do you take a machine and build models to understand the text, not just the keyword search it and find any document with a certain word or near match, but conceptually something a lot closer to like sentiment analysis or a contextual understanding of are you looking for Apple the fruit or Apple the company? Was Apple the company referenced in a favorable or non-favorable way? How could that then be used maybe to predict certain market trends or do product research, consumer reviews.
You sort of see where a machine understanding language is a pretty powerful thing because you either pay humans to read those documents and synthesize them in their own brains and do the analysis, make decisions, or you automate it. But there’s a level at which no group of humans could ever read everything in a certain unit of time and produce the analysis, it’s physically impossible.
If all 8 billion people in the world right now were able to read, say every email that goes in and out of an investment bank and coordinate and come up with the analysis and the summary, like that’s an impossible problem, no amount of people can really solve it. There’s just too much overhead in coordination. That’s perfect for a machine. It’s perfect for a machine to do 99.9, 9% of that work and then have some human experts understand it.
So, those were the kinds of problems we started to work on early and you know, now a lot of that technology is pretty readily available in the open source world, and I don’t know if I’d call it a commodity, but maybe borderline commodity to some extent now with cloud services that the companies like Google and Amazon offer. So, it’s been a little time getting to be involved in early stage technology companies.
My background professionally is technology, obviously, but the fitness was always the hobby.
Fitness was going back to when I was even a teenager, it was always the way I like to spend my time and it was both just the pleasure of it feeling good while I’m training, but also there was something about just how can I maximize my own human potential and then being pretty analytically minded. Well, how do I measure that? And how do I know that I’m really running the best plan here? What would it take for me to achieve a certain goal? what kind of time horizon and so on.
And so, I’d never quite figured out how to put technology and fitness together in a way that it could just make sense as a business. I just never quite been able to do it, but I gradually found a way to do it. And a lot of it was because once I was involved in triathlon and CrossFit, I started to really quantify the training. I’m going to create a distinction between exercise and training. If I want to exercise going to go and sweat and feel good and get some work done, go get in a “workout”, but it’s mostly for me to feel good and for me to move my body.
If I’m going to train, it’s going to be in alignment with the goal. I’m trying to achieve something. There’s a margin of error that I should be caring about if I’m training versus exercising. And I started to realize, “Oh, fitness is this fad driven industry precisely because we’ve got lots of exercisers who like to try new things and gradually get very bored of the new things and need new things.” But it, but it’s a very fad driven industry, I think because it’s not personalized. If I create a program that works for everybody, then it kind of works for nobody because there’s no personalization for you specifically and your unique goals, or me specifically in my unique goals.
And so, it really hit me that if you could deliver technology that can provide personalized coaching, personalized training advice for some niche segment, well that could be a complete game changer, that could start with some narrow sliver of a market, but as it matures it could reach a much broader market. And that was when I was really able to put the pieces together and say, okay, I’m here doing CrossFit.
It’s a very data driven, lots of variables involved. You know, there’s weightlifting, there’s gymnastics, there’s modern structural endurance. It’s sort of training for the unknown and the unknowable as they say. So, it’s a very multifaceted problem, but it’s a very data-driven problem. And there’s a lot of good doctrine around the ways that they’ve gone about quantifying fitness and how you measure that.
And when I was able to cast that as a machine learning problem, as a problem that, with users could produce data, with data could produce AI, and then with that, there could be this real value for a group of people that have fitness as a lifestyle. It took a while to put those pieces together the way I just described it, but that’s really where it all came into focus for me and I was able to say, “okay, there is a way to take everything that I’ve learned up to this point and project it into a particular market with a particular set of problems because that market has not been well served by this kind of technology yet.
This market’s been over served by maybe video on demand, or let me sell you another workout program because it’s my workout program and you should believe me this time because I want to race, or I’m a world champion in something.”
That doesn’t translate very well to an arbitrary person, maybe in CrossFit what works for Rich Froning or Matt Frazier, I would be crippled if they gave me their training program, and I tried to do it for more than a couple of days. I need something that’s going to be tailored to my skill level, my experience level, my mobility level, plus my goals. I may not have the goal to be the fittest man on earth, while they obviously do, and they’ve done that. You know, my goal may be a little bit more skewed in one direction or another.
And that’s the thing with the personalization, right? That’s why I’m very excited about technology and what it can do in fitness, because I think the more personalized the experience can be for the consumer, we’re back to like, well, why would they buy a product? Or why would they use a product well in this space? I think it’s because it will serve them well when Fitness is their hobby or Fitness is their lifestyle, it’s more of I want to spend more money on this digital product because I buy the new shoes and I buy the latest apparel and I pay for the personal coach every once in a while, I spend lots of discretionary income on fitness because it’s more than a hobby. It’s my lifestyle. It’s what I wake up in the morning and what is the first thing I think about? one of the things is training. It’s like, “okay, well, how am I going to train today? What am I going to do today?” Right?
Jesse: Yeah. You know, the thing you mentioned is— I talked about this with other guys, I’ve talked about this on my other show where I just talk about running and teach people about running. It’s that the idea that people like to hone in on the pros, right? Or the top of the sport, whoever that is, whether we’re talking about pros, not pros, doesn’t matter. And say, “well, I’ll just do whatever they are doing.” Like, okay, well, you’re missing so many things.
As you mentioned, the personalization factors which include, among other things, the entire history of their fitness leading up to that point that you may not have. So, it’s funny that people want to focus in on that, but it’s the completely wrong thing to do because it has nothing to do with what you specifically need to do for your specific goals.
So, thinking about the AI in particular, I know I’ve spoken with several people recently even, Matt Jordan comes to mind, he works at the Canadian Institute of sport— Is that right? It’s basically the Canadian Olympic training center, I can’t remember the actual name of it at the moment in Calgary. And so, some are people who are kind of in a more academic role, trying to figure out how to quantify and track all of these points of training, training load, quantifying fatigue, all these kinds of things.
And then there’s obviously companies like yours and a number of other kind of fitness trackers who are also working on this problem. I can’t remember whether it was Matt or another guest, I don’t want to put words on everybody’s mouths, but somebody had mentioned that they don’t understand how AI companies are doing this because they don’t believe academics even have this figured out at this point. So, for you approaching this problem, is it a matter of if we can throw enough data into our buckets, see what patterns come out, then you can predict, or how do you approach that problem?
Matthew: Yeah. So, I think you have to— Like so many things, it’s like I was telling a friend yesterday, everything that you think is easy in life, you only think that because somebody else has been good enough at their job to make it look that way. When you actually have to do it yourself and you peel back the layers, you realize nothing is easy in life, all those things you took for granted as being easy, those people doing those jobs were just very competent or good enough to make it look that way for you.
And so, with AI, if we’re only listening to what certain people say about AI, and they’re only talking about the things that are working or the things that aren’t working, there’s this bias, similar kind of bias. So, I think to peel back those layers you have to unwind it and you have to say, well, there is no AI without data, and there is no data without users that produce the data” unless you can find a really good way to synthetically create it. Sometimes you can. And there are no users unless you have a valuable enough tool or product that delivers enough value that they’ll even use it in the first place.
So, if I have something of value to provide a user that solves a real problem in a way that has a cost structure that can let me stay in business, then I can try to siphon off the data exhaust that has a real creative value, and as that data exhaust [inaudible] I can build analytics that increasingly become more and more sophisticated. And at some point you hope that you have a bit of a data moat and a critical mass of data that really puts you in a category of your own, but you don’t just do this overnight.
I don’t like the metaphor that life is a marathon. I know that it is, but my mentality is to approach the marathon as a series of a hundred meter sprints. You know, I want to move quickly, I want to be in a hurry about everything I do, but there’s a part of me that also just understands you can plant a seed and you can give it the perfect lighting and the perfect water, and the perfect environmental conditions, but it’s still going to take some period of time for that particular seed to sprout and grow into a tomato or a husk of corn, or whatever it is.
You know, you can put the cake in the oven and triple the heat, but you can’t cook the cake three times faster by tripling the heat, right? You know, three women can’t make a baby three times faster, right? There’s some things, some cycles in life that just take time. And I think when you’re thinking about building an AI product, you should not underestimate that it is a bit of a long game, whether you want it to be or not.
Now, you should always look for shortcuts. You should always look for ways to use money to get back time, you have capital decisions you have to make all along the way. With enough time and money though, you should be able to do it. But timing does matter, right? if you’re right, but you’re not on time, you’re wrong in business. Timing matters.
Jesse: So, thinking about the way you kind of laid out that Development cycle. How do you get your greatest amount of efficacy with a platform or an AI, as I understand you having explained it to me, so correct me please, is once you already have that big conglomeration of data, right? So, what do you offer early adopters? Which for you listening is the people that start on before something’s really much of a thing, what do you offer early adopters to get them in so you get momentum in the beginning when you don’t have that big moat of data that you’re looking to have down the stream?
Matthew: Yeah. So, it obviously varies by product. So, what you’re really looking for I think in business terms is you’re looking for your unique value proposition. So, if you’re looking at a market, I was telling a colleague, if you’re looking at a market and you say, “wow, I’m in such a crowded market.” To me, that’s just a hint that you don’t really know what your unique value proposition is. You haven’t found the right competitive matrix to put yourself in.
Because if you really have a unique value proposition, then by definition you should be in a subset of a market that is not really crowded because if it’s unique you have some distance between you and some of your competitors. If you’re just trying to sort of compete with everybody on every feature or level up to get to some point, it’s going to seem really crowded and really difficult. And how do you find a unique value proposition? Well, it’s a combination of things.
I think there is some intuition about it, you want to have good founder market fit. If you’re starting a company you’re trying to build a product I think you do want to scratch your own itch because that domain knowledge is critical. You can’t just really outsource that, I don’t think. I think you also have to consider who is out there? what is their messaging? How are they projecting themselves? You obviously do some market research and try to be analytical about it.
But then there’s marketing, which is what a company says about itself, and then there’s just the consumer review, which could be very different, right? You can project any message you want about your product on a website, but what the review say and what are the people who use it say, and what do they say that they would more of, or less of, or where is it strong? Where does it fall short? Right, so you can do that. But you can also build a functional prototype of your own product that’s conceptually smoke and mirrors, but if it can provide a user experience, you can interview a consumer.
And there’s some best practices and techniques here for “Hey, would you spend five minutes and try to use this and let me watch you?” and “Hey, great. What did you think of that?” “How much would you be willing to pay for that?” “Where did it fall short?” So, I think that’s sort of a top-down approach, but I think that’s a very market driven approach, and I think it’s a very messy process, but you know, no one ever said building a business was easy, right? On a secular level I think it is the ultimate multi objective optimization problem in life. Like, I don’t know of anything that’s harder than building something out of nothing. It’s just the hardest thing.
Jesse: You said a few things I kind of want to touch on. And you talked about you need your unique value proposition. You think about the— The difference, so for you listening— Matthew and I are both entrepreneurs, so there’s a lot of jargon here. It’s basically what makes you different from everybody else, and there’s the idea of, on the most mundane level, so say iPhone came out and then there were a bunch of clones, Chinese clones of iPhones, I’m saying Chinese just as a broad term, I’m sure there were other countries and producers of clones of iPhones. It’s a me too product, there’s nothing unique about that thing, they’re trying to copy the exact same thing.
But then in some sense you can say Samsung Galaxy phone series is not a me too, it’s in a same or similar space, but it offers different features, it’s a different software, it offers different things. So, that’s kind of what the unique value proposition is. But then there’s a deeper way to go there where, I’m sure Matthew you’ve heard this, the blue ocean strategy where you’re trying to create a new sub niche where nobody else is so you no longer have competition.
But the thing that you said that kind of struck a chord with me more, and for anybody who’s an entrepreneur, I often touch on this is the founder market fit, right? I have no business building a software as a service company. I just, my coding skills are basic at best, I wouldn’t even know how to verify that my codes are doing the appropriate thing, so I don’t have good founder market fit for the kind of things that you do. And I think that can’t be understated because that’s—
So, although I often say follow your passion is a bad way to build a business, it is important in the essence that, as you mentioned, you have some knowledge about the market you’re serving, otherwise you’re going in cold and you’re going to miss— There’s so many things you don’t know that you don’t know about that market.
Matthew: Yeah, that’s right. There are the things and you know they’re going to be hard and you’ve experienced them, and then you know about some things, right? these no known knowns, right? You know that there are some gaps in your own knowledge and there’s a marketing function, you don’t really know how hard it’s going to be to think about all of the different aspects of what may be involved.
Like if you’re me coming from a product background, I know that, I’ve been there, I’ve done that, I kind of know that’s hard. Well, marketing, B2C marketing, I know that’s going to be hard, but I don’t really know just how hard it’s going to be, but I’m going to put a placeholder there for it.
And then there’s the unknown unknowns, the blind spots, which by definition, you can’t find a blind spot on your own, that’s why it’s a blind spot. You either literally have to have another person point it out to you or you have to run into it—
Jesse: You run into it the hard way.
Matthew: Yeah. A hundred percent. So, but in all of that, I think the most important thing about founder market fit is that building a business from scratch it’s so hard that if you just don’t love it on some level, if you wouldn’t spend the time staying up late, getting up early, letting go of a 40 or 50 hour a week job, or a 70 or 80 hour a week job where you probably get paid a lot less, at least in the early days. if you just don’t love it and aren’t delighted to be doing it, you just won’t do that for very long.
I mean, on some level I think I have an award-winning tolerance for pain when I look at my own wife and the grit in a lot of situations. I mean, it takes that to build any early stage business. I think there’s some level of wanting to endure it because even though it’s that difficult, there’s a real satisfaction that comes just from being able to do it and know that you’re doing it and know that you’re doing a good job, and even though the progress may be slow at times, having the faith and just sort of the knowing that the vision may never be fully realized, but you are at least approaching the vision. You’re making progress. it’s a little closer than it used to be.
I think if you don’t have founder market fit for a startup, I don’t know how you ever work through that. It’s impossible for me to conceive.
Jesse: Yeah, it’s interesting. Because I know like— I wouldn’t say he’s a mentor, but he’s definitely in the space. I attend his e-commerce conference, Steve [inaudible]. He comes from a software— Well, I think it’s technically hardware, he helped design computer chips, I think at Intel, but I could be wrong. So, sorry, Steve, if I’ve got that wrong. So, he came from a technology background and him and his wife started an online store selling handkerchiefs of all things. He didn’t know much about handkerchiefs, but he found himself becoming obsessive about it and finding a passion in serving that market.
I think that’s really, as far as I know, the only way around it is that your passion for serving people supersedes your current knowledge and interest in the topic itself, and that has limits, but I think that’s the only way you get around it.
Matthew: Yeah. I think that’s an interesting angle. And I think there there’s another angle in between, which is if I go back to writing books, it’s like with the first book you write you don’t know what you’re doing and you figure it out and you underestimated a whole bunch of things, but then you build up the tool chain.
And the second book you’ve got a process and there’s a structure that follows a strategy, and it’s a little more efficient. And you do it a couple more times and eventually you sort of see how you could become a publisher, if that were your goal in life. You’ve sort of built the tool chain, the process, you could imagine what the business model is and so on.
And I think with businesses it’s sort of the same thing. I think if you make it through the whole process and you build a successful business, there’s this benefit you have in the survivorship bias of having figured out one way to solve a very complex problem. You’ve learned a lot of things, right? I love this quote, I’ll paraphrase, but you know, the quote is something to the effect of, “the young man knows the rules to the game, but the older man knows the exceptions”, right?
So, you’ve learned all of the different ways that you can cut yourself on the sharp edges and the prickly parts of it that hurts you or that were more difficult than you expected, but you make it through. And once you make it through, I think you either, at least the way I think about it, you either say, “wow, that that was great, and I never want to do that again, but I’m glad it was a success” or you say, “wow, I’m going to take everything I just learned and benefit from that experience and do it again.” And there’s sort of a compounding interest on that.
So, I think the reason you hear about a “serial entrepreneur” is because if you’re the kind of person that has a certain tolerance for pain and certain kind of passion you like to follow, and you’ve cracked the code once or twice, I see how you could take that pattern and systematically apply it. So, if you start with computer chips but you know how to manage and operate a company, I totally get how you could start selling handkerchiefs as an e-commerce business if you love the process and if you love business as a broad category versus only software or only hard goods or only services and consulting work.
Jesse: Yeah. Matthew, we’re starting to wind down on time. There’s a question I’m asking everybody this season because it really transcends any particular discipline. The question I’m asking everybody and I’d like to know from you is, what do you think the purpose of sport is?
Matthew: Yeah, I think the purpose of sport— You know, maximizing human potential is sort of the first thing that comes to mind. You know, that’s something I’ve thought a lot about. And if you think of any contest, whether it’s a little group of kids on a field that barely know how to kick the ball, or a group of very highly paid professional, best in the world athletes competing in some way, I think on some level the participants are trying to maximize their own human potential, they’re trying to play the best game they can on any given day
And I think if you’re a spectator, that’s also what you’re looking for on some level, you’re looking for people to play a good game. And in theory, if both sides are giving their best effort and it maximizes their human potential, it should be a fair outcome based on the conditions of the day.
And there’s something about the uncertainty of knowing how that match will work out or how that race will end that is just purely entertaining and fascinating because you start to wonder what makes these people tick? And could I ever do that? And what would it take to be able to do that, right? What do these people put themselves through? So, I think it just sort of leads to this state of wonder and fascination.
But that’s the best answer I think I have. I think the side effects are it brings people together and there’s a lot of learning and sort of lot of, there’s a lot of benefits to it, but if I think of why do the people themselves engage in sport? I don’t know if I’ve met anyone that would say something too different from “I want to be the best I can be. I want to want to give my best effort. I want to leave it all out on the field.” That sounds a lot maximizing human potential. And then if there’s a whole industry involved in watching it go down, I think that’s what you’re looking for.
Jesse: Matthew. If people want to kind of follow your SAS companies, see what you’re up to, see about new books, any of that kind of stuff, where can they find you?
Matthew: Yeah. The best way to find me would be— I don’t spend a lot of time on social media right now, but all of my social media accounts are out there and I keep an eye on them from time to time. My companies I would say would be a couple things to check out. So, throwdowns.com. We have a fitness competitions platform that’s pretty holistic end to end, really designed for some of the unique needs of functional fitness sports CrossFit. But more broadly we can support a lot of different sports.
And then our new mobile wearable app, Strongest, will be available in the app store later this quarter. So, you can go to strongest.ai, we have a list you can sign up for to get early access, be a beta tester while we iron out some more of the experience. And yeah, other than those two places I would say this podcast episode was great and probably learned a lot about me just here, if you listen to this the whole way through, so this has been a lot of fun and appreciate the opportunity to chat with you.
Jesse: Yeah, absolutely. And so, for you, if you are interested in CrossFit, functional fitness, and for some reason you’re organizing, while I was looking through Matthews company, Throwdowns, it looks very robust software. I come from a running background, so I think about the software solutions for running races or triathlons, and there are a lot of nice technology needs that you need behind the scenes to make a race go smooth for a race director. The same thing is going to apply for functional fitness and keeping everything running smoothly.
So, if that’s your field, definitely check that out because I think as Matthew mentioned earlier, things only look simple when everybody else has done their job to make it look simple, and that’s kind of what Matthew and that company is trying to accomplish. So, Matthew, thanks for hanging out with me today. I hope you have a great weekend.
Matthew: Thanks. Have a great weekend.