In this episode of The Digital Edge, host Mark Reed-Edwards sits down with Jonathan Greene, Co-Founder and CEO of RocketSource by Incubeta.
Together, they explore the data silos and security risks that can emerge as organizations begin adopting large language models (LLMs). Jonathan explains why the solution lies in deploying enterprise-grade LLMs. By using a secure, private, cloud-based solution such as Gemini Enterprise, businesses can bring their internal knowledge together in one place and support more informed, confident decision-making.
Listen in as they unpack how enterprise LLMs can help break down silos, organize data effectively, and enable a connected “enterprise hive mind” that improves efficiency and collaboration across the organization.
Read the Full Transcript Here
Mark Reed-Edwards: This is The Digital Edge from Incubeta. I’m Mark Reed-Edwards. This podcast is about how you can balance technology and humanity. How, as AI eats the world, you can integrate efficiency with empathy. We will talk with leaders from Incubeta and across the industry as we traverse the digital edge into tomorrow’s world.
Mark Reed-Edwards: On today’s episode, we’re joined by Jonathan Greene, co-founder and CEO at RocketSource by Incubeta. Jonathan has a wealth of knowledge around generative AI, LLMs, and how to best put them to use for clients to build customer lifetime value through the fusion of behavioral science, data intelligence, and AI-powered experiences.
Mark Reed-Edwards: Jonathan, welcome to The Digital Edge.
Jonathan Greene: Thank you, Mark. Glad to be here.
Mark Reed-Edwards: It’s great to have you here. Can you share a bit about your career journey and how RocketSource, the company you co-founded, came into the Incubeta family?
Jonathan Greene: Absolutely. This will be a little bit of a journey because you gotta go back to my early days to kinda understand my mentality of when I discovered that I thought, you know what? Maybe I’m gonna be an entrepreneur my entire life. And it goes all the way back. I was probably nine, 10 years old. Hot summer day. I grew up in a family where I was doing all kinds of yard work, and I realized that if I wanted to start making a little bit of side money to go hang out with my friends and go to the movies or go do things, I had to go figure out how to get money. Because my parents were surely not giving it to me.
Jonathan Greene: But I would say to them, “What if I took the lawnmower and I go, started knocking on doors and I asked people to mow other people’s lawns.” “Yeah, you can do that. We’ll let you take the lawnmower, but you gotta pay for the gas and everything.” So I started a lawn business early on. I’d knock on all the neighbors‘ doors, ask ’em if I could mow their lawn, and I would start learning.
Jonathan Greene: Do I ask, it’s gonna be $20 up front or $10 up front, or do I go back at the end after I mow the lawn and ask for $10? And there’s a story that I’ll never forget where we just finished mowing Mrs. Kramer’s lawn, and literally we spent 15 minutes. My buddy helped me that day and we mowed her lawn, and we knocked on her door and said, “Hi, Mrs. Kramer. All right, that’ll be $25.” She says, “Boys, $25? You’ve been here for 15 minutes.”
Jonathan Greene: I said, “I know, Mrs. Kramer, but look, see the lawn? It’s been mowed crisscrossed twice. We’ve trimmed it. We even weeded your garden. And doesn’t it look amazing?” “Sure enough, boys. Okay, here you go. Let me write you a check.”
Jonathan Greene: And that moment really stuck on me to understand that regardless of where I’d go in my life, if I just put in the hard work, delivered something of value, I could ask for something that I expected. And so I sort of kickstarted my career being an entrepreneur, which then led me down a path of creating a window washing business, a car detailing business.
Jonathan Greene: I grew up in a household where my father was an accountant. And so I spent a lot of time watching him on a computer and I was always curious. So I got into computers at a young age and I started tinkering on them, and I met someone in my neighborhood who said, “Hey, Jonathan? Do you know how to build a website? I wanna start selling stuff online.” I’m like, I have no clue. But I’d done so many prior experiences in learning how to mow lawns, learning how to do car detailing, learning how to fix fences and fix plumbing and other things, I’m like, “Sure, I can figure that out.”
Jonathan Greene: And I was pretty handy on computers. And so I started and I built my first e-commerce site. This is like right after the dot-com bubble. And then shortly thereafter, I entered university years. And so I started my first company, which was building websites. I live in the state of Utah and through a connection, I picked up a client — the Utah State Office of Education — and started building this massive interactive website where schools had to submit applications in terms of how they would spend what was called this trust line money. And I’d have to build a system where districts, administrators would log in and they would have to figure out how to prove it.
Jonathan Greene: And I connected this ecosystem together. I’m like, wow. Okay. And so with the launch of this company I built and just started growing and connected through other friends across the board who were at other universities who graduated in design, who left Utah and went to San Francisco, or went to New York City and started networking with those friends, which then led me into some enterprise clients and started building enterprise big applications.
Jonathan Greene: And along that way, got involved in all things iOS, from iPhone apps to iPad apps. I remember this group called me up and said, can you build us a sales rep app for an iPad? So when a sales rep goes to a meeting, they can just start asking questions and taking notes on an iPad.
Jonathan Greene: I’m like, “Sure, I’ll figure it out.”
Jonathan Greene: That was the spirit of what got me to this path in technology after building so many different applications and interfaces. I started realizing, I’m only in this lens of tech, right? And I only understand, we at the time, we would call it just end user experience.
Jonathan Greene: And so we would spend a lot of time doing the tech side of things. I would work with really hardcore UX/UI designers. And then I spent a lot of time in the world of data and then I started just getting more curious. I’m like, “I only see one piece of this large elephant, right? And I’m only maybe the end piece of where a transaction takes place. But what about the entire business model and what makes consumers choose brand A versus brand B?” And my curiosity just really got the best of me there.
Jonathan Greene: And at the same time, I had met a woman who is now my wife and she’s a therapist. And we would have all these deep conversations about human behavior. I dove deeply into studying why humans do what they do.
Jonathan Greene: And I started realizing like, “Hey, there’s something here.” And so through networking, I met some really awesome business partners. We formed RocketSource, this next iteration of a service-based company building digital experiences, but we gotta combine it with a handful of things. We said, “Let’s build something new, something interesting where we could build a thesis off a single question.”
Jonathan Greene: I’m like, “What do you mean?” What we all came up with, which really made sense to me, was trying to answer this question, which is: Why do your customers stay with you? Because if you can answer why they stay with you, it can give you really good insight into how we’re gonna go acquire new like-minded customers that want to go down that same path.
Jonathan Greene: So we dug deep into that and built an experience where, look, let’s go after enterprise, let’s go after those who really want to build data infrastructure that can answer that hard question. Let’s go after and build stuff like, LTV to CAC modeling, which is lifetime value to cost of acquisition, cost ratio modeling.
Jonathan Greene: And then from there, we then ultimately end up building a large format of a digital experience that delivers the end result. And we can drive growth, but to gain traction along the way to really get RocketSource going, we said, “Look. Most companies in this day and age are going to need, all the methodologies and frameworks and things to follow, to really crack the nut.”
Jonathan Greene: This is pre AI. This is early, 2016, 2017. And so we said, “OK, we could either attach ourself to a cloud platform like Google or Microsoft or AWS or we can start out and build a slew of frameworks. Really hardcore frameworks that can help us, guide us and steer us to answer these hard questions.
Jonathan Greene: And so we said, “OK, let’s do this. And what is that gonna take?” That drove us down a path to write an enormous amount of content. So we started writing these long form blog posts. They’re like 20,000 words. They’re really dense and they’re heavy and they got tons of graphics, but they’re meaningful and they go after and they solve very specific things.
Jonathan Greene: And as we started this journey, and I know I’m moving fast here, Mark.
Mark Reed-Edwards: I am on the edge of my seat, Jonathan.
Jonathan Greene: It’s coming together. So, we were like in our third blog post and we started really crafting all this web content. I can’t remember if it was myself or my business partner.
Jonathan Greene: We found this article by Google when they were writing about this transformer, and if you wanna read about that transformer, there’s a killer podcast on the Google AI that I’ve talked about on LinkedIn where they actually tell this story. They publish this article about a transformer, which becomes ultimately GPT — a generative pre-trained model.
Jonathan Greene: And our, we were like, “OK, maybe we’ve really got something.” If we could fast forward from 2017 into early 2022, and if Google really does this. And there is a generative pre-trained model. That means we could chat our data, we could have a conversation with it, we could have an experience with it.
Jonathan Greene: And so we then decided to double down on thinking, “OK, let’s craft a whole bunch of content, go through a bunch of case studies, build a bunch of training models, all centered around our frameworks, which is ultimately trying to figure out why do your customers stay with you?”
Jonathan Greene: Why does a customer choose brand A versus brand B? How do we convert a brand new customer into becoming a brand ambassador? How do we solve for consumer’s awareness stage from completely unaware of a problem, to unaware of a solution, to becoming aware of a problem that they have and aware of a solution, and then ultimately. Their brand unaware to brand aware and guiding them down a path.
Jonathan Greene: How could we figure out a massive customer journey map that could really answer these core questions of why do customers fall off of certain parts of the funnel? Why do they jump back in? What’s gonna drive higher conversion rates? And so literally, Mark, we spent years and years just documenting everything and building up an incredible knowledge base.
Jonathan Greene: Fast forward now here comes ChatGPT, the first consumer base model on the market, and we start playing around with it and realizing, “OK, this is great, but it’s just a general public knowledge model. How do I attach this to my model, my knowledge? ‚Cause I’m not giving my knowledge to ChatGPT.”
Jonathan Greene: And so for a couple years, from ’23 into early ’25, we tinkered with a slew of different AI models that came on the market, across ChatGPT, Perplexity, Claude, Gemini, across the board, and like, “OK, these are all great.”
Jonathan Greene: But only a few of ’em could really start doing what we call RAG architecture — retrieval, augmented generation — where I could take a public model and I could attach it to my private data and have it learn from my private data, and then I go back to the public model and say, now enhance it with your brain, and see what outcomes I could produce.
Jonathan Greene: And so we tinkered with a slew of different RAG architecture models and it was quite interesting to figure out which ones work and not work. And so where we landed and where we are today is there’s really only a couple. And the one that so far we’d like the best is Gemini Enterprise.
Jonathan Greene: Yeah, because in the world of Google architecture, I can build an entire ecosystem on my Google Cloud platform where I have my knowledge base, which was structured in my data, my information. I can take all my BigQuery databases, which have any kind of customer survey data or things that I’ve gone after, or third-party data or facts data, say from USAFacts — anything else that’s interesting to me that I train in a certain way.
Jonathan Greene: And then I can append that. I can not only query my data, but then I can attach it to say, “OK, Gemini 3 Pro, you query it and you enhance it. And now let’s see what our outcomes can be.” And I can start building experiences from that.
Jonathan Greene: So that’s a long intro into where we are today, but that’s what got us there is really after a question of curiosity, why do your customers stay with you? And knowing that if we could figure that out, we could take those insights and apply it to acquisition models. Because being so retention focused is where the secret sauce is.
Jonathan Greene: And then the path we led on that said, how do we ultimately build a fantastic knowledge base, apply it into RAG architecture for the future of AI and make use of it. So that’s where we are today.
Mark Reed-Edwards: So, Jonathan, that all started with mowing Mrs. Kramer’s lawn. Now, did you get her as a returning customer?
Jonathan Greene: Oh yeah. We had a fabulous summer with Mrs. Kramer. Mrs. Kramer led into Mrs. Pet, led into Mrs. Kirkham, all these different funny characters of my life where I realized that if I just worked hard, delivered really excellent customer service and a product they love, they were repeat customers.
Mark Reed-Edwards: So how did RocketSource come into the Incubeta family?
Jonathan Greene: As we started to continue to grow at RocketSource, we got to a certain point where, because we had attached ourselves so much to building frameworks, methodologies and models, we realized that we potentially could only open up a handful of doors every year to continue to grow RocketSource organically.
Jonathan Greene: And we said, if we had a larger partner who we could fold into that could open up a thousand doors a year, and in the right tech stack, we could accelerate our growth faster. And then we could really put all of our frameworks and methodology in play and in practice in a much larger setting than we ever thought possible.
Jonathan Greene: And that’s where we were introduced to Incubeta. And we got to know their leadership. We got to understand their vision and where they wanted to take things and their connection into the Google ecosystem, and it really started just making sense.
Jonathan Greene: After a lot of conversations and digging deep, we showcased to them our approach to all of our AI models, our approach to human-centric AI, our approach to really uncovering these hardcore questions about why your customers stay and being more tech agnostic in a way that we could navigate it in interesting new ways.
Jonathan Greene: We said, yeah, this could be our new home. And that’s how we made the deal work. And so far it’s been an incredible journey.
Mark Reed-Edwards: Yeah. It’s fascinating how those things just come together. So how do you set yourself up to have a digital edge these days, especially in this AI world?
Jonathan Greene: That’s a great question, Mark. And I’m gonna go back to what I said in my original opening story. Any company that wants to have the digital edge, to have a competitive advantage, to create internal IP, it starts with your knowledge base. So think about this for a moment.
Jonathan Greene: This is my lens for how I see it. 2010, 2012, with the onslaught of SaaS, companies just poured numerous amounts of investment in dollars into writing source code and building out their products. They didn’t spend a ton of time writing and investing in knowledge bases.
Jonathan Greene: And so a lot of companies today are backtracking, thinking, “We don’t have enough documentation that trains humans how to do their jobs, that trains machines how to do their jobs, and how to train humans how to talk to machines to do their jobs.”
Jonathan Greene: So to me, our biggest competitive advantage and what we’re doing day in and day out with organizations is going in and doing an analysis of their current knowledge base.
Jonathan Greene: What kind of documentation do they have available, whether that’s stored in Google Drive or Microsoft SharePoint or other cloud-based tools, and really understanding how well is it written?
Jonathan Greene: Did they go through and properly architect what we call README files that teaches any sort of LLM, a large language model from a consumer based or an enterprise LLM for RAG architecture — retrieval augmented generation — that connects to that knowledge base and how well can it understand and interpret what to do?
Jonathan Greene: And if you were to ask it questions, can it actually do its job?
Jonathan Greene: And so oftentimes the competitive edge we find is first going through and analyzing everything across the board in that knowledge base, understanding what intellectual property is in there.
Jonathan Greene: How do we keep it private and secure? And it maintains that it stays there and get that in place?
Jonathan Greene: And then the second component is we go deep into all available data sets that a company has and has stored over time and years. What kind of training and availability within that data that we can make use of?
Jonathan Greene: And once we combine those two together and we start deploying different scenarios and seeing what we can cook in the kitchen, so to speak, we then build what we call a prioritization matrix. It says, “Hey, if you invest further within AI, you’re gonna get X, Y, Z out of it by knowing what’s in your knowledge base and what is in your private data.”
Jonathan Greene: And then we just work them through a path, a journey that goes up the scale. Because from there you go into what specific agents can you build that can automate very specific tasks from your private data and knowledge.
Jonathan Greene: To then move further into what kind of custom new IP can you generate from this internal system that’s doing and thinking for you, to actually start producing better results to enhance that knowledge base.
Jonathan Greene: That’s where the multiplier effects really starts to take place. So that’s my lens of a competitive advantage: How good is your internal knowledge base and private data?
Mark Reed-Edwards: Yeah. That leads into my next question. In this world of AI hype, how should decision makers think about AI?
Jonathan Greene: So let’s say you’re in an organization and you’ve got employees across the board that are using consumer based LLMs. Pretty much every piece of content they’re pumping out there has been enhanced by their consumer version of an LLM.
Jonathan Greene: They’re probably leaking data where they don’t know they’re leaking data. It’s disparate, it’s siloed. It’s just unorganized. It’s hard then to decide on where to invest dollars because you’re still living in that silo world.
Jonathan Greene: Once you go through a full discovery of our internal data, full discovery of our internal knowledge, and you deploy what I would consider an enterprise LLM — so it’s no longer a consumer LLM.
Jonathan Greene: An enterprise LLM is inside of a private secure cloud. An example would be Gemini Enterprise, where all of that knowledge and data is housed within an area where only internal people have access and they’re querying internal data.
Jonathan Greene: And then they’re asking it very specific questions. It can really help decision makers understand: Where are our silos? What have we now broken down?
Jonathan Greene: How do we start building things where we’re templatizing and using things in a similar manner?
Jonathan Greene: What we’ve created now is an enterprise hive mind. I’ve broken down the silos. I’ve got multiple teams — from office of the CMO, Marketing, office of my CRO, everyone in sales, maybe in operations — they’re all now speaking and understanding the same language from go-to-market to the actual products they’re selling to the actual delivery. It’s all connected in one ecosystem.
Jonathan Greene: That’s an enterprise LLM. And once decision makers see and understand that, they’re like, “OK, this is a no-brainer. Why has this taking so long?” And it takes so long to get there because again, these organizations are siloed and you have CIO and CTOs off saying, “This is our AI strategy.”
Jonathan Greene: And you have CMOs off saying, “No, I’m gonna use these systems for my AI strategy.” And you got rev ops saying, “No, we’re using Salesforce and Agent Force to do it this way.”
Jonathan Greene: And because of all this disconnectedness, they never get into an enterprise hive mind where everything is connected.
Jonathan Greene: But I think once we get there, and when I see organizations get to that point, I’m seeing some incredible work, where it’s used as a tool to enhance the output, which ultimately then is driving better customer experiences, which is therefore driving some really incredible growth.
Mark Reed-Edwards: So that leads me into my next question, conveniently. What’s the best approach to AI architecture and ensuring it won’t be outmoded or you won’t be outflanked by your competition?
Jonathan Greene: Love the question. And that’s a question we’ve been answering, since 2023 really, when the first iteration of ChatGPT came online.
Jonathan Greene: How do we build our architecture where: if I want to use ChatGPT, if I wanna use Claude for coding, if I want to use Perplexity for reasoning or I want to use Gemini for research or Notebook LLM for research, right?
Jonathan Greene: How can I make sure that I can be agnostic in my architecture, build sort of an AI council and go across the board across all of them.
Jonathan Greene: That’s a big question we’ve been asking ourselves, and it takes a process of experimenting.
Jonathan Greene: And through that experimentation process, we’ve ultimately come down to number one, we own our knowledge base.
Jonathan Greene: Our knowledge base sits in cloud architecture that we own, is kept private, and any of the consumer LLMs do not have access to it.
Jonathan Greene: Number two is, again, all the data that we’ve collected over the years, we have systematized and built into areas that it makes sense to query.
Jonathan Greene: And once we attach those two and keep them in a place we know, let’s say we run a deployment now with Gemini Enterprise, we can connect those dots and I’ve now connected private RAG architecture with say a Gemini Pro 3, and it’s working. It’s working great.
Jonathan Greene: Come down the road, my company’s acquired again, or something happens and we’re now a Microsoft Cloud shop. Guess what? I can take my data and I can take my knowledge base and now I can append it to an Azure Cloud and run their private version of ChatGPT.
Jonathan Greene: Or I can also say, “Hey, within my code base. So now I’m using Claude 4 in very specific ways to help me as a coding assistant, I can also attach it there and keep that private.”
Jonathan Greene: So it’s about keeping what is central and core to you in your cloud architecture, private that belongs to you, and then testing out numerous models that are appended on top of that and building those layers of security and governance so that they only have access to very specific things.
Jonathan Greene: So you keep what’s private to you and then you decide what you release out into the public LLMs.
Jonathan Greene: That’s our vision of how that architecture works. And so, come down the road, there’s another new cloud or some other new AI tool we want to try, we can plug into it.
Jonathan Greene: For example, let’s be super futuristic, right? At CES back in January, the amount of robots that are coming out.
Jonathan Greene: What happens when eventually we’re gonna buy a robot and it’s gonna come into our house, right? It’s gonna be like buying iPhone one to three, to now iPhone seven, to now iPhone 17, right? We’re gonna go through these cycles of robots.
Jonathan Greene: When a robot comes into my house, do I want that robot to gather all of my data that it’s gonna share with other robots or only a select bit of it.
Jonathan Greene: So I can test out multiple robots, I’m gonna keep my data and my infrastructure private and held to me, and then I just keep adding new robots and testing which ones I like. This robot does a really great job at doing the dishes. This one does a great job at doing the laundry.
Jonathan Greene: This one, can it go pick up my kids from school? I know that sounds crazy, but we might live in a world like that at some point. Sure.
Jonathan Greene: And so in that architecture, it’s about how do I store my private data?
Jonathan Greene: I was recently at the University of Oregon speaking to some students, and they asked me a similar question.
Jonathan Greene: And I said, the number one thing you should be thinking about in your four years of college is every single paper you write, every class you attend, every email you send: build your own private model.
Jonathan Greene: Keep it safe — it’s in the Google Cloud in that scenario — so that someday you’ll be able to append that to your own LLM or LLMs you want to test out. You’ll have it, you’ll be able to use it long term.
Jonathan Greene: And they caught that vision and they understood it.
Jonathan Greene: I wish I could go back and say, “Hey, ask me a question at the age of 21 while I was at a university. What was I thinking, feeling, saying at that time?”
Jonathan Greene: And so if we build this the right way, we could have that capacity where you could talk to different iterations of yourself as it grows and learns over time.
Mark Reed-Edwards: So the next couple of questions, Jonathan, I wanna learn a bit more about Jonathan, the person, and learned a heck of a lot about you earlier when you were talking about your early entrepreneurial experiences. But can you give me an example of when you failed and how it impacted your life?
Jonathan Greene: In classic entrepreneur style, we often will promise things that we have no idea or no business delivering on, where we have massive imposter syndrome, but somehow our entrepreneur mind says, “Yes, I’ll figure it out.”
Jonathan Greene: And I can think of a handful of examples where I said, “Yes, I can figure that out.” And we ultimately figured it out. But we never met the client’s expectation.
Jonathan Greene: And because I’m very much a perfectionist, it drove me crazy that ultimately we had failed because we couldn’t meet their expectations.
Jonathan Greene: But we had still delivered on, contractually, what should have been done. But we didn’t get it there because either we didn’t fully understand what the outcomes were going to be or what it should look like.
Jonathan Greene: The failure I often think about is, even today coming onto this podcast, right? Who wants to listen to me, right? Yeah.
Jonathan Greene: I always have this feeling of, am I truly an imposter? What do I know?
Jonathan Greene: And so I always go back to thinking about the Dunning and Kruger Bell Curve effect, right?
Jonathan Greene: Is it better for me, am I on a path where I’m constantly on the upscale of, I don’t know much of anything, but I can tell you what my experiences are and I’m gonna keep learning.
Jonathan Greene: And so through those failure examples, I’m very upfront, at least I try to be in all cases with clients like, “Okay, here’s where we failed. Here’s where potential failures could be, and we will be transparent about them and really set those expectations early on.”
Jonathan Greene: Because if we do that the right way, then we’re learning together and we’re on a path. Because nothing’s gonna be perfect.
Jonathan Greene: And so through enough of those failures, it’s helped me shape and approach some of the AI architecture and AI models we’ve been working on because I can clearly see that if we go down certain paths, we will fail. And that’s been a big part of what I’ve seen time and again.
Mark Reed-Edwards: That self-awareness is critical though, right? If you didn’t know that, you didn’t know certain things, that would be worse than admitting you don’t know some things.
Jonathan Greene: Oh my goodness. Yes, it’s the constant thing. And when someone asks me a question about AI today, I just go, it’s a very broad topic, and so I try to just narrow it down because it’s like someone saying, “Hey, tell me about the internet.”
Mark Reed-Edwards: Yeah, please explain it to me.
Jonathan Greene: Explain to me.
Mark Reed-Edwards: System of tubes.
Jonathan Greene: A system of tubes. So I really try to break that down and to keep it simple of what it is we’re talking about.
Jonathan Greene: The self-awareness process, I think, is what’s so critical across everybody that we get to interact with and work with who are out there seeking.
Jonathan Greene: Because all of us humans, if we’re still in existence today, we’re seeking purpose and meaning. And that lens and perspective is different for everyone.
Jonathan Greene: And so what I try to do is just get at the core of what are they seeking? What is their purpose? How do they define meaning in their life? Where are they going?
Jonathan Greene: And some of us, I think often people think, “Oh, Jonathan, you’re an entrepreneur, you must work all the time.” Yes, I work a lot. But there are days where I really enjoy it so it doesn’t feel like work.
Jonathan Greene: And so I have to do many other things to stay balanced in that realm and keep me grounded in where I’m going. Keep my lens and how I view the world in a certain way.
Jonathan Greene: And never get too lost into this is the only way something can get done.
Mark Reed-Edwards: I think you’ve answered this last question, but I’ll ask it anyway. If you could share one piece of hard-earned wisdom you’ve learned over your career, what would it be? Maybe it’s that lesson you learned with Mrs. Kramer early on.
Jonathan Greene: Yeah, I think that’s a great lesson. I would think today, and what I teach my two boys is I often ask them, think about the end in mind. What ultimately do you want in life?
Jonathan Greene: Are you going to build a career where you essentially have to constantly be hunting and going after things just to keep up, to pay your mortgage, pay down your debt, keep up with the Joneses, go after the things you do.
Jonathan Greene: Or do you wanna build a career and a lifestyle that you enjoy because you’re passionate about it, you want to be there.
Jonathan Greene: And so even today, it’s normal. I can put in 60, 80 even more hours per week, but it’s how I find the balance in things. So I don’t just work on AI models every day.
Jonathan Greene: The last couple years, one of the big lessons I’ve learned is, for whatever reason, the universe, I kept hearing violin music in my head and I said, why is that?
Jonathan Greene: And I had played the violin as a child up until the age of 14, 15. And I just quit. I was like, I’m done. I can’t do this anymore. And I sold it and bought a pair of skis.
Jonathan Greene: Skis.
Jonathan Greene: And so now here I am as an adult and I kept hearing violin music. And so a couple years ago a friend challenged me and I said, okay.
Jonathan Greene: The next day, I went and bought a violin. I found a violin teacher, and I’ve been retraining for the past two years, how to play the violin as an adult with a new set of skills, a new lens.
Jonathan Greene: And it has probably been the most grounding experience for me. Because it humbles me every day. I’m not perfect at it.
Jonathan Greene: I’m in the middle of trying to learn how to redo vibrato and like my current arm structure and who I am today in years of tennis, I can’t do vibrato really well. It’s hard.
Jonathan Greene: But that experience alone, it’s just how I find my connectedness to who I am. Because that music makes me feel a certain way when I can play it.
Jonathan Greene: And if I feel that way when I play music, how can I take that purpose and meaning and share it with others.
Mark Reed-Edwards: Wow. Jonathan, this was a great discussion. I really appreciate you joining me here on The Digital Edge.
Jonathan Greene: You are welcome. It’s been fun. I appreciate your good questions, Mark.
Mark Reed-Edwards: I really enjoyed the discussion with Jonathan — from mowing Mrs. Kramer’s lawn through to helping you understand and utilize generative AI, we got a glimpse into the future of AI from one of the brightest minds in the business.
Mark Reed-Edwards: On the next Digital Edge, I’ll be joined by Amy Crowther, President, Americas, for Incubeta. We’ll explore how Incubeta supports the AI-enabled organization. And we’ll look at the best way to get data and creative to work well together.
Mark Reed-Edwards: That’s on the next Digital Edge. I’m Mark Reed-Edwards. I hope you can join us then.
Speakers: Host: Mark Reed-Edwards; Guest: Jonathan Greene, Co-Founder and CEO of RocketSource by Incubeta.