The following interview is a conversation we had with Greg Fallon, CEO of Geminus, on our podcast Category Visionaries. You can view the full episode here: $12M Raised to Help the Industrial Sector Prepare for the Energy Transition

Greg Fallon
Hey, Brett, it’s great to meet you and good to be here. 

Brett
Yeah, super excited. So, to kick things off, let’s start with maybe just a quick summary of who you are and a bit more about your background. 

Greg Fallon
Yeah, well, thanks for that. So I am kind of a lifelong nerd, and I’m pursuing my dream with this particular company. I started my journey academically as getting my phd in mechanical engineering. I was actually in my PhD program and really fell in love with this concept of being able to accurately simulate the world around us. And I was building a laboratory at the University of Virginia. And at the time, there was a new industry emerging. So very high fidelity or high accuracy engineering simulations were starting to become commercial in the mid ninety s. And there was a bunch of startups that came about in the late 80s, early nineties. I fell in love with one of them and had a chance to join one in Hanover, New Hampshire. 

Greg Fallon
So I left my PhD program and moved into the business realm, and we created a company named Fluent. And were simulating the way that airflows and fluids flow around us, and that became one of the leading companies in this new sector called High Fidelity, or engineering simulation. That’s about a $20 billion market today, and it’s growing at about 10% a year. So that was my experience and foray into startups. We grew the company, we sold it in 2006 to a publicly traded company who also had a similar mission. I stayed there for a while, taking various roles, moving from direct sales leadership more into marketing and strategy. And at the same time, I really had a passion for startups. I really enjoyed the early days of fluent, so I actually ended up starting a company that focused on personalized monitoring, not unlike Fitbit. 

Greg Fallon
In fact, were gearing up to be a competitor to Fitbit, and were about to raise $12 million the day Lehman brothers collapsed. So that startup, we abandoned it. I stayed in the engineering simulation space and got excited about, well, there was two things. Number one, I was really kind of discouraged by the lack of innovation in the space. We had the ability to create these really complex models that can predict the world around us, but they were very computationally intensive and time intensive. It could take you hours to weeks to answer a single question. And while that was exciting in a way, because it replaced physical testing, which would take months, sometimes years, to get answer, it wasn’t anything near real time. 

Greg Fallon
And what I really wanted to do, and I’ve had this vision since I was a kid, was to visualize accurately what was happening with the world around us. Right. I used to spend afternoons on the back deck of my grandfather’s sailboat, looking at the eddies coming off of the rudder and imagining that I could see the air swirling around us. So I had this kind of early passion for that, and I wasn’t seeing any progress towards real time solutions. So there was a company in San Francisco that was doing some interesting work, Autodesk. I moved there and started to leave some innovative product teams. 

Greg Fallon
We commercialized a product called Generative Design, which was an AI product that would take a request from an engineer with requirements saying, look, make me something that can hold 12oz of hot water without burning my hand, and it would give you all the possible ways to do that and to manufacture it. So we launched that product in 2017. That was pretty exciting. I moved into other roles there, led our advanced manufacturing group and 3d printing, then moved on to create a developer platform and lead a developer platform. But all the time, I was still missing this concept of, what if we could really do a better job of understanding the world around us, at least as engineers. And there was a guy at the University of Michigan who was gaining in prominence, turns out to be my Co-Founder now, Karthik Durasami. 

Greg Fallon
And he had done some research at Stanford and later at Michigan, and he was combining the field of machine learning, traditional neural nets, with this heavy computational sciences. And he was having a lot of luck. He actually created a new academic field with a really fun name, AI augmented computational physics. And he and I got linked up, and Geminus was born. And I’ll tell the story here in a minute, but, yeah, that’s my personal journey. Kind of a lifelong nerd with a really kind of penchant for new and innovation projects. 

Brett
What was that like leaving Autodesk? So I have to imagine you were feeling pretty good there. 

Greg Fallon
You were in a nice role. 

Brett
It’s a very established company. Probably felt like a very safe place to be. Was that hard to leave and go. 

Greg Fallon
Start your own know? No, it wasn’t. First of all, Autodesk is a great place to work. It was really great. I was very well paid. I had a very senior position there and I loved it. I loved the people. But the passion for what Geminus does and what Karthik’s research did was just ingrained in my dna. And so it was a two week was, I heard about this opportunity and jumped on it. And I was with Geminus within actually three weeks. 

Brett
Wow. Now, a few questions we’d like to ask. And the goal here is really just to better understand what makes you tick. First one, what CEO do you admire the most and what do you admire about them? 

Greg Fallon
Oh, my gosh. I’d say that from a CEO perspective, and this is kind of hope it’s not too panic, but I really admire Sadia Nardella at Microsoft. And what I admire about him is kind of his penchant for change. Right? He’s changing this gigantic company that was an early tech leader and should have been a dinosaur. And at least I thought they were going to be discarded in the 2010 and replaced by someone else. And he really changed the company. That’s one. Also, I really like his life story. I find him a very compelling human being and very kind of approachable. So I admire his vulnerability, the way he seems to approach the world around him. So, yeah, I would say that he’s the number one. 

Brett
What was his quote a few months ago is something about making Google dance, I think, which I thought was just an awesome line. It’s been very fun to watch this whole dynamic where all of a sudden bing is being talked about as a rival to Google. I went on Bing one time and thought it was horrible and I never really went on there again. But now there’s a lot of talk about Google being displaced and Microsoft potentially replacing them, or just even the fact that Microsoft is being talked about as a competitor to Google search. I think it’s a very fascinating time to be in tech. 

Greg Fallon
Totally. I would have lost a lot of money if I had to place a bet on who would win the search wars. 

Brett
Now, what about books? And the way we like to frame this, we got this from Ryan Holiday, but he calls them quake books. So I think his loose definition was a quake book is a book that rocks you to your core. It really influences how you think about the world and how you approach life. Do any quake books come to mind for you? 

Greg Fallon
Yeah, I mean, look, I love books. I love reading. And can I give two? There are books that rock me to the core as a human being, and then there’s kind of books that really drive me as a Founder. So this one book that I really love, and this is more of a book that I’ve come to love as an adult, was a book called the lonely Sea in the sky by Sir Francis Chichester. And he was an early explorer. In the pre World War II days, he flew an air Maine from New Zealand to England on his own, which was a really big feat at the time he did it. And he was one of the first people to sail around the world in a yacht. And he did that at a very late age, which is what I really admired about him. 

Greg Fallon
I think he was, like, 72 when he set off on the journey or something like that. Don’t quote me, but the fact that what I really liked about him is, number one, he had no pretenses, and he would just go out and try things, and he seemed to have very little fear in what he did, and he never allowed anything to hold him back. I mean, for this person to have set off to sail around the world at 72 at a time where most people, the life expectancy was probably in the was pretty amazing. So that’s one that really sticks with me and makes me think about resilience as I think about the dark days as a startup Founder. From a Founder perspective, I read lots of business books all the time. 

Greg Fallon
I’m covered with bookshelves around me, in front of me that I look at all day, but the one that I like is really classic. My favorite business related book that drives me as a Founder is crossing the chasm by Jeffrey Moore. I think that book is timeless in the way that it captures the evolution of new disruptive technologies. 

Brett
It’s so fascinating with that book, too, that it was written in, like, was it the late eighty s or early ninety s? And it’s still just as relevant today. I think listeners are probably annoyed by me saying this, because whenever someone talks about that book, I say the same thing. But a few years ago, someone referred that book to me and I was like, this is dumb. Why am I going to read a book about technology from the. Doesn’t make any sense. And I read it, I’m like, wow, I’m a moron. This is very accurate and completely applies to everything today, regardless of when it was written. 

Greg Fallon
I agree with you, Brett. It’s unbelievable what the staying power that book has. I mean, most business books are good for a year or two, maybe five, but I think I was looking at his most recent edition. It’s like on the fourth edition, he’s updating all the business case studies. There’s been technology cycles that have come and gone throughout the lifespan of that book, yet it’s just as relevant today as the day he released it. 

Brett
I’ll have to check out the explorer book as well. About six months ago or eight months ago, I got just kind of obsessed with books that are still kind of thrilling and exciting and give you some lessons in life, but not business books. So I read river of doubt about Teddy Roosevelt’s explorations in the Amazon, and then Ernest Shackleton and that whole voyage that he took. So I’ll check out the one that you mentioned there. It definitely sounds fascinating and sounds like it’s probably similar to those types of books. Very cool. 

Greg Fallon
And by the way, river of doubt is one of my favorite books. 

Brett
Yeah, that’s up there for me. I recommend that to everyone. Someone on the podcast told me about it. That’s such a fascinating book. It’s insane to think about that former president going down in the rivers like that. 

Greg Fallon
Yeah, I know. It’s really cool. And it’s got some deep personal growth aspects to it as well, which I really enjoyed. 

Brett
Yeah, totally agree. Now let’s switch gears and let’s dive a bit deeper into the company. So, just at a very high level, and we can think about this like the elevator pitch. What is the pitch? 

Greg Fallon
What does that look like? So, it depends on who we’re talking to. But look, for this audience, we’re a deep learning company for engineering applications, and we’re focused on two primary goals. One is making machines, all machines, more efficient, and the other one is around compressing the design cycles for designing and creating those machines. And the two are very related, but it’s something that we happen to do very well. That’s the pitch, and I’ll give you some examples, too. So, when we talk about making machines more efficient, most people who aren’t mechanical engineers or chemical engineers don’t realize that the big plants and pieces of equipment around us are mostly inefficient in a huge way. 

Greg Fallon
I think that the Un most recent climate report said that if the machines that are out there just improved their efficiency to the best they had ever done, not the best they can do, you would reduce global greenhouse gases by, like, 12%. But the reality is that most machines are operated really far away from their optimum, like 20, 40%. And so if you take a power plant, for example, some power plants are more efficient than 20 or 40% away, but they produce, they’re very expensive to run and they’re very complex to run. A typical power plant will have hundreds or thousands of settings that can be adjusted at any given time to produce the power, the output based on a given input. And so how do you know what the optimum settings are at any given time? Right. 

Greg Fallon
You have this really complex model where you have kind of 1000 factorial, you have 1000 different settings in terms of the options that you have. And there’s no technology today that can be tractably used in a reasonable amount of time or cost to deliver the exact recipe to operate that power plant at 100% efficiency all the time. AI, specifically the type of AI we do, makes that possible, and we do it in a really inexpensive way. And we’ll talk about that, I’m sure, later. So that’s one big example. Another example of use case for Geminus is, let’s say you’re an engineer and you’re designing and scaling up a carbon capture system. That’s a pretty intense engineering problem. 

Greg Fallon
It may work really well at a lab scale, but if you want to scale it up to the size of a building where you’re trying to capture massive amounts of carbon, things change, the physics change dramatically. And it’s a big engineering problem requiring lots of testing, simulation and experiments. It could take you years to go through that particular process for any given product. But what if you could cut that time by half using AI? And that’s the type of things that we do when we talk about helping compress design cycles. 

Brett
I read on the website that you’re challenging the AI status quo. Can you just frame that for us? What is the status quo? What does that look like for the customers that you’re selling to? 

Greg Fallon
Yeah, well, so that was actually kind of why were founded. So the status quo is that with traditional AI, right, think about just if you want to take large learning models or any type of model in neural net, the typical way to train them is through data. And so when people think data like power plant, you think about measurement data, right? And everybody assumes, I think, or at least I used to assume, that in the industrial world, where you have these fancy engineers, people have lots of data. And so the typical way to train a model, for example, for power plant, would be to collect lots of data and create a model. Well, first of all, there isn’t a lot of data in the industrial environment compared to the amount of change that happens. 

Greg Fallon
And so if you take this measurement centric approach to AI, not only is it expensive, because you often have to add like hundreds of thousands or millions of dollars of sensors and all sorts of infrastructure to collect the data and clean up the data, but you also have limitations into kind of what the models can do. Right. If you’re creating an AI model to map the performance of a power plant based on historical data, the best you’re ever going to do is tell that plant how to operate at its previous peak. You’re never going to be able to understand how to make that plant operate at efficiencies it had never gotten to before. 

Greg Fallon
So the state of the art is really very expensive, deployments and years to create a model, and it makes AI impractical to deploy when it comes to the industrial environment, specifically machines. Right? I mean, there’s lots of other problems in the industrial environment, like production planning, that can be tackled, but it comes to the behavior of machines. Traditional AI is really not suitable. 

Brett
You mentioned that there’s a lack of data coming from these machines in this industrial environment. Why is that? I would think that these machines are now starting to be digitized and that everything’s smart. Is that not the case? Is everything not smart yet? 

Greg Fallon
Well, first of all, everything is not smart yet. And when you have really expensive assets, they tend to have a very long life, like 50 years. So you still have a lot of assets today that are running the world that were built 10, 20, 30 years ago and don’t have a lot of sensors. But even if you take machines that are fully sensorized today, the problem is that they may have loads of sensors, but they’re not going to have an infinite number of sensors. And with the way machines typically work, they’re driven by the laws of physics, and you can’t sensorize everything. And it’s often what happens between the sensors that really matters, because change happens very quickly in these machines. So it would be impossible to infinitely sensorize a machine. 

Greg Fallon
You might be to be able to do it in a few machines, but if you’re going to do it across all industries, it would be almost impossible to sensorize to the point that you could get really good predictions. Got it. 

Brett
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Greg Fallon
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Greg Fallon
Now back today’s episode. 

Brett
What do you do to stand out in a world that’s so full of noise with AI? Obviously AI is everywhere you look. I know it reached the peak level when my mom texted me and asked me about AI and Chat GPT. So we’re definitely in the mainstream now. There’s definitely a lot of buzz and hype around AI. How do you stand out and how do you educate the market to understand that your AI is different and better than everything else that’s out there on the market today? 

Greg Fallon
Brett, you’re shooting an arrow through my heart. That is like a huge problem. I mean, everybody talks about AI. There is AI washing. There are credible AI solutions that being thrust on everyone all the time. So it’s really hard to cut through the noise. We kind of have three strategies that we have found helpful. Number one, in the industrial space, the biggest challenge is credibility. You’re dealing with the largest corporations in the world and it’s difficult from a startup to work with these corporations. Credibility is a big issue, and one of the things that we have done really well is identify credible companies to whom we can add value as a partner, who can bring us credibility to their customers who might be these large corporations. 

Greg Fallon
And that has really let us stand out because they have the ear of at least their customer base. That’s one way to cut through the noise, is to partner with these folks. We have a very exciting partnership with SLB. They used to be called Slumberger. They’re kind of a leader in energy engineering, both renewable and traditional energy. We’ve got some other really exciting partnerships we’re going to be announcing here in the next four weeks or so. So that was the big one was partnered credibility. The other thing is focus. And this kind of goes back to the core elements of crossing the chasm. 

Greg Fallon
We found that if we can focus on to start a very small audience that is highly credible, that understands what we do inherently and has already looked at other forms of AI and is familiar with some of the drawbacks, we can resonate instantly. And at first our journey towards focus was hard. And I think that’s like most startups, right? We spent a long time going out and talking to everybody and their brother, trying to figure out how to talk to them in a way that made sense. And 99% of the audience just didn’t understand the problem. And maybe we would get lucky because they liked us, but more often than not, we would end up resonating with 1%. That’s where the whole idea of ideal customer profile comes. But it’s really important to us because of this noise issue. 

Greg Fallon
And so what we do today is we’ve gotten very clear on our ICP, and we’re using really sophisticated tools that are available now to help target customers and really understand which customers are more likely to resonate with. There’s a great tool called six Sense that’s out there that senses signals from large corporations. What are their employees searching on? What keywords are they looking at? How do they stack rank? And that really helps us get very focused so we know who to talk to. And then we overlap that with our partners or advisors. The last is really around advisors overcoming the noise. So we partner with not only companies, but individuals who are thought leaders and help leverage them for both their network and their credibility. 

Greg Fallon
And when I say leverage them, I think it’s a bi directional relationship because they end up finding it very fulfilling to work with a startup and help us get going. And then the last thing that we’ve done, which was risky, but it paid off really well for us, was we made some investments in PR. We have some relationships with some very senior reporters that were personal, that they helped us really kind of get a leg up with a few folks. We ended up on CNN a couple of weeks ago, and along with that, we made sure we crafted a really big story that was time sensitive. And it just so happens that story resonates with the ethos of our company, and that really is around accelerating our ability as a humanity to combat climate change. 

Brett
I watched that interview as I was preparing for this interview, and it was awesome. You did such a great job, and I can see how that brought a lot of value to you. I’ll definitely link to it in the show notes now. I’m sure every Founder listening in is thinking, okay, cool, I want to be on CNN, so take us behind the scenes. How did you pull that off exactly? Was that through a PR firm? You said it was some context you have. Can you just take us behind the scenes of everything that happened between the idea and you being featured in CNN and having this awesome interview? 

Greg Fallon
Yeah, I mean, we got lucky Friday. We had some personal relationships with some really senior correspondents and reporters that advised us they fell in love with our company, became advisors, and really helped us make sure that we had a story that was relevant for the news media. And then helped us within their network. So I would like to say that it was as easy as hiring a PR firm, but it wasn’t. It was a matter of leveraging our network. 

Brett
Now, when it comes to finding early adopters, is that hard to do in the industrial sector? Are people in the industrial sector quick to experiment and test with new technology? I know very little about the space, but from the outside, it seems like they aren’t very quick to embrace new technology, especially with what you said about these machines. And this equipment sometimes lasts for 2030 years. So how do you find those early adopters? 

Greg Fallon
Yeah, so, Brett, that’s the core challenge. So we did a lot of kind of thinking and testing hypotheses. So the first thing that we did is we kind of, first of all, just to take a step back, our technology is applicable towards any industrial vertical, right? Whether it’s like food manufacturing or aerospace engineering or mobility and cars. We’re applicable without modification of the technology across all these verticals, which was great when you start to think about market potential, but it’s really hard when you start to think about focus. And so we did a couple of things. Number one, went out and tested a lot of different verticals. We spent a lot of money and time doing that. I’m not sure it was money well spent. 

Greg Fallon
So we did kind of an experimentation there that was, I think, going after it the hard way, the way that really paid dividends for us, was just taking a step back and being thoughtful and saying, okay, what do we know about the industrial space? And we just said, okay, well, what are the macro trends facing industry today? Okay, there’s geopolitical change. So which verticals are going to be economically most resilient over the next few years, assuming that the economy is in a state of uncertainty for the next several years. So went through and we identified the industries that we thought were going to be most resilient. And then we said, okay, what industries are most profitable in those areas, and who are the ones that invest the most in r and D? 

Greg Fallon
And there’s a lot of data around r and D spend by industry. So were able to kind of narrow down the different verticals. But yet even within a vertical, as you pointed out, the majority of industrial companies are not major innovators. They definitely have engineering teams that do incremental innovation for them. But the idea of kind of being leaders is different. And so then went out, we started to talk to people. We did it the hard way, to be honest with you. We burned a lot of cycles doing pocs with companies who we thought were innovative. That turned out not to be. And I’ll tell you, like two weeks ago, I just asked Chat GPT who the most innovative energy companies were, and it mapped exactly to our experience over the last two years. 

Greg Fallon
And so then we started, over the last couple of months, we started to get really aggressive in the use of new AI tools and new digital tools. It’s amazing the information that we’re able to find and how well it maps to these things. 

Brett
Who’s the buyer there? Who’s making those key decisions? Is it like a chief digital transformation officer or a chief digital officer? Is it something like that? Or who is that main buyer? 

Greg Fallon
Yeah, so first of all, you hit it right? So there’s a main influencer who is the chief digital officer, CTO. Sometimes they’re in the same organization, sometimes they’re the CIO. They tend to be the major influencer, and in some companies they’re the buyer, the economic buyer, in others they’re not. And so one of the things that we have had to get really good at is dealing with complex sale scenarios. We may have twelve stakeholders in a given deal, and it may be a split decision between, like, a chief digital officer who becomes our advocate, but then the operating teams that run these big assets who actually have to buy in and sometimes fund them. So it’s complex. 

Greg Fallon
I think our best friend is the chief digital officer, but then we also have to make sure that we build credibility within these engineering teams and that actually fits into our ideal customer profile. We think as we’re getting going, we’ve identified a certain subset of companies that have very strong relationships between their chief digital officer, their digital transformation teams and their operating units. It’s those companies that we’re targeting first, and we actually are having good luck now that we came to that realization. 

Brett
A lot of founders that I speak to on the podcast face a very similar situation where there’s a lot of different buyers that are involved in the buying process, and at some point they have to narrow it down on their website to say, okay, here’s who we’re going to try to speak to the most. What was that like for you, and who are you trying to speak to? Like, when I go to the website now, who is that really geared towards? 

Greg Fallon
Well, I don’t think we’re very good at it yet, to be quite honest. The website today is really geared for investors and press. I think we’re about to release a new version where we’re focused on the CTO and CDOS organization. And we’re finding that we need to make sure that we have ample content for the end users and the technologists themselves. And so we have three user personas for the end users. They’re data scientists, they’re folks that are called computational scientists, and then there are actual engineers who design and run processes. And so we’re going to have tiered content on the website. That kind of is high level, is attractive to the chief technology officer, chief digital officer, digital transformation group, and then as you dig into the product pages, you’ll be able to get more and more information. 

Greg Fallon
And we’ve benchmarked our website against others. And quite honestly, I haven’t found a single startup out there that does a good job. I think it’s a big challenge. I think that speaks to the challenge that exists. But we think that we’ve got a process that will let us tell this cascaded message in a very simple way. 

Brett
And when it comes to market category, I introduced you as industrial AI optimization. Is industrial optimization an established category and you’re coming in and disrupting it by adding in AI? Or is this entire concept and idea a totally new category that’s being created? 

Greg Fallon
I’ve been thinking about that question a lot, and I used to think that we’re creating a new category, and I’ve come to realize that there are a set of tools that have been around for about 40 years that kind of call themselves industrial optimization and really kind of think that they are. So I would say that we’re redefining a category, and I liken ourselves to the ipod. There were music players for sure, but the ipod completely changed what a music player was. 

Brett
Makes a lot of sense. And that’s something I think, again, all founders struggle with that is, how do you position this? Do you make the category creation play? And there’s obviously all the benefits that get talked about there, but there’s also a lot of downsides, and there’s a lot of risk to doing that. So I agree with that approach. And I think in most cases, companies are much better off taking that kind of disruptor position or challenger position in established category and taking that line item that’s already there. So that makes a lot of sense. Now, let’s talk a little bit about funding. So I mentioned there in the intro, you’ve raised 12 million to date. What have you learned about fundraising? 

Greg Fallon
Oh, my. I’ve learned a lot about what not to do, but I think the things that I’ve learned, you probably could have told me when I started out. One thing is, first of all, if you’re fundraising, it is a full time job. You have to focus on it. You can’t really afford to do anything else. You better have a team that is under you, that is running the rest of the company while you’re fundraising. But the most important thing in fundraising is to figure, especially in the current environment where I think most investors are sitting on the sidelines or just investing in their existing portfolio to keep them alive. But you really need to figure out your IIP, your ideal investor profile, and you have to be very deliberate in pursuing those particular types of investors. 

Greg Fallon
I spent a lot of time talking to investors that were really excited, but we would get to the end and I would get one partner super bought in, but then the investment committee, other partners would be very skeptical and we’re in a very difficult, deep tech industry. So I started to get very deliberate in the investor profile, and I call it the IIP. The other thing that I learned along the way, and I think this is common knowledge, but I’m going to say it because it’s really important for the audience to hear. Associates are often gold on the number of meetings that they create for the VC. So if you are reactive in fundraising and reactive to inbound inquiries, you’re likely going to be wasting your time. Now, there is one thing that I use those calls for, which is important. 

Greg Fallon
I mean, there’s actually two things that I get out of those calls. And by the way, I don’t turn down any inbound calls, but I do it on purpose, in a deliberate fashion. Number one, I use them for practice. Right? So I consider every investor call a way to get better. So I test our messaging. I improve the questions that I ask. I improve the way that I run the calls. So that’s one. And the other thing that it’s helped me with is building a reputation in the investment community, which helped massively. And so by being generous with my time with these folks, I really ended up getting contacts and connections to people who were meaningful investors. And I found that we do have a reputation that’s evolved in the industry. It was loads of hard work, but I think it was worth it. 

Brett
Now, let’s imagine you were starting the company again today from scratch. What would be the number one piece of advice you’d give to yourself? 

Greg Fallon
The piece of advice that I would give to myself is very obvious, but I don’t think I followed it as diligently, or at least I didn’t know what it meant. I mean, there’s two pieces of advice. First one is fail often and fail fast and be okay with failure. Everybody said that to me at the beginning, and I thought that I understood what that really meant, but I didn’t. And I think that I now have a certain amount of confidence that it’s okay. Things are going to go wrong. As a CEO, you need to keep the company alive, and you need to learn from your mistakes, and that’s what it’s all about. And so when I talk about fail off and fail fast, it’s really the fast piece that is critical. 

Greg Fallon
You have to constantly be innovating to find ways to gather information and test your assumptions, and you need to be able to pivot on a dime. So that’s one big one. But it’s this idea that fail often and fail fast is okay. You have to be okay with that. The other one is also going to sound kind of trivial, but it’s trust your instincts. Everybody says that, but at the end of the day, as a Founder, you have a certain set of instincts. You have to trust them because you don’t have anything else. And I think for the most part, I did that well. But I think if I went back two years, I would probably have been much more confident in my instincts because most of the things that I thought were going to happen in the very beginning ended up happening. 

Brett
Final question for you before we run out of time here. What’s the next three to five years going to look like? Can you just paint a picture for us of that big picture vision? 

Greg Fallon
Yeah. So, first of all, I’m very excited about the next three to five years, and I’m going to talk about the next three to five years from Geminus’s perspective, but this is going to have implications in the world. I mentioned at the very beginning that most machines are operated pretty far away from optimum. And if we’re going to survive as a planet, we have to use less resources. We have to emit less greenhouse gases. We have to actually get to zero greenhouse gases. The only way to do that, or one major way to do it is everything has to be run almost optimally. So my vision for the next three to five years is to have AI helping to optimize every machine, plant and system on the planet. I think in the three years, it’s most kind of very expensive assets. 

Greg Fallon
And I think as we get to five to ten years, it’s everything from your iPhone to your car to your battery in your car. I think that we can make smart machines really happen. At scale. 

Brett
Amazing. I love the vision and I love everything that you’re building, and I love the problems that you’re solving. We are up on time here, so we’re going to have to wrap before we do. If any founders listening in want to follow along with your journey as you build and execute on this vision, where should they go? 

Greg Fallon
I would follow us on know I’m most active on LinkedIn. We post on LinkedIn almost daily. I think that would be the first place that I would go. 

Brett
Amazing. Greg, thank you so much for taking the time to talk about what you’re building and to share some of the lessons that you’ve learned along the way. I’ve really enjoyed this conversation and appreciate you taking the time. 

Greg Fallon
Likewise, Brett. Thank you. 

Brett
All right, keep in touch. This episode of Category Visionaries is brought to you by Front Lines Media, Silicon Valley’s leading podcast production studio. If you’re a B2B Founder looking for help launching and growing your own podcast, visit frontlines.io podcast. 

Greg Fallon
And for the latest episode, search for. 

Brett
Category Visionaries on your podcast platform of choice. Thanks for listening, and we’ll catch you on the next episode. You close.