Henry Park: 07:46
Yeah. And I don’t talk about it much unless it’s people who have been there with me. I still have friends from that period. You know the toughest part. If I were depending on what part of my life you asked me, my answer would have been different. Because I was still stuck on trauma, and it would have been, you know, people I blame. It would have been people that I’m resentful of. It would have been things that I feel, you know, happened to me. But, you know, now that I’ve realized that a lot of those things just happen for me, for me to be able to understand and create the kind of communities that I’m creating now.
You know, the thing that I would say that I learned during that period was how to be true to myself. You know, no matter what happens around you and all the different tribulations and trials and challenges you’re faced, you know, it’s important to be true to yourself. And I lost myself, you know, during that period was a dark night of the soul where I really got lost in what things I wanted to do because things were cool or things I wanted to do to be a rebel, you know? And you know it. Ultimately, what I’ve learned through all this is that the highest order of energy that you could ever manifest is love. That is the, the, the most true and most powerful energy that you could ever amass is love.
Dr. Jeremy Weisz: 09:27
How did you get back on track at that point?
Henry Park: 09:29
You know, it was I had luckily parents who were there for me at a very low time. And it was actually my parents, the reason why I left home. We, we, we had a big difference in religion. So, you know, my parents were Jehovah’s Witnesses, and you know, nothing against that religion. It just wasn’t for me. But when you leave that religion, you leave the family. I didn’t realize that. And, you know, I was on the streets because of it. And, you know, there were a lot of things that happened. And I ended up in jail. You know, a friend of mine got shot, and I ended up in jail. Not that I, I shot him, but I was there, and he passed away. And my parents had to. Yeah. And that was, you know, that was a very, very hard period for all of my friends.
And my parents had to pick me up. And at that point, you know, they set their religious differences aside and really urged me to go back to college, and had me come back home, and yeah.
Dr. Jeremy Weisz: 10:40
And no, I appreciate you sharing that, Henry. And, you know, this is the interesting part about like, when we got on, I had no idea we’d be talking about this, obviously. But I find it super fascinating because, like when you look, some of the people I’ve met and I get to know them, and they share some of their background, it’s really amazing. Some of the stuff they overcame to get to where they are. And that’s sometimes just as impressive as or more impressive than what they’re doing now, you know? So I appreciate you kind of sharing that part of your journey.
Henry Park: 11:16
Yeah, yeah. And you know what, in a lot of ways, it’s those challenges that really push you to do things that normal people wouldn’t in their comfort zone, you know, and it’s not, and I, I, I appreciate you recognizing that because, you know, there’s a, that in itself is a rite of passage.
Dr. Jeremy Weisz: 11:36
Well, I think, you know, I have found entrepreneurship is no joke. And so I don’t know if you think of it like this, but I want to talk about the three shifts that you’ve gotten through, because I don’t know the way I view it as well. I look back on. It’s not as bad as when I was sitting in that jail cell. So I can get through like a voice over IP pivot or whatever. So talk about some of those, those pivots, and you know, how do you navigate those with Pandoblox?
Henry Park: 12:04
Yeah, yeah. So Pandoblox. I started eight years ago in blockchain and the, I had another company called 3GC Group that started in 2003 that went through the whole voice over IP and cloud, you know, the, the pivots, I would say what allows an entrepreneur to pivot and, and survive that pivot is vision and really understanding the, the, the voice of the customer and the client’s needs and, and focusing on as very specific client problem for Pandoblox when we got started with blockchain. By the way, I need to give a shout-out to someone I did the non-profit with because the name Pandoblox came from it. So the trees came from Archangel Ancient Tree Archive, a phenomenal non-profit organization. Their mission is to save ancient trees, you know, and so they genetically clone them. Anyway, when I first got started with Pandoblox, the company name was Pangaea. And I read David Milarch, who founded Archangel Ancient Tree Archive. His book, and it inspired me, and he talks about Pandoblox, the largest root system in the oldest living organism in the world, 30 32000 plus years old.
It’s one tree root system that spans from New York to California, and so the tree inspired me to call this Pandoblox. And you know, last week we did the Earth Day celebration with his trees. It was amazing. He flew down, and it was such an amazing experience. But Pandoblox, you know, we got started as a blockchain. So the idea is the root system of data across the world, right? For various enterprise functions. But as we dove into it and we’re doing a lot of architecture type work for large enterprises in the medical and media entertainment, what we realized was that most companies weren’t ready with their data to automate any function in it, let alone put it in an immutable ledger, like a blockchain that would forever, you know, keep that unbreakable blockchain. And so we pivoted, realizing what the client needed, and got into machine learning operations.
So, you know, doing big data, massive petabytes, worth of data transformations, normalization, that kind of thing using machine learning ops. And then as we tackle that, we started realizing, wait a minute, all of these tools that are being used at the large enterprise level were meant and designed for data enterprise level, data engineers, data operations management that mid-market don’t have. And so we wanted to fixate on the mid-market because everyone else is focusing on small business or large enterprise with a lot of these automation tools, which dives into the old way of doing things, the traditional SaaS, right? The traditional software as a service was designed around a GUI, right? Easy administration, you know, reduces the amount of software engineering, so that administratively, you could do it.
But then that whole industry, if you look at the entire industry and including the services that support it, it’s sort of upside down.
You got the software itself, you know, for every dollar you spend on software management or the software subscription, you spend $9 on supporting it, right? And so AI changes that, you know, AI, the way we’re iterating on AI is very opposite the way we’re iterating on machine learning, because AI evolves with you and it learns with you. You know, machine learning had to be Guardrail and very tightly scoped, whereas gen AI, you know, you have it built with you and iterate with you and all that. And so, we pivoted from there, doing big-scale projects around machine learning. And we wanted to create a platform focusing on the mid market, and in the mid market, when you really study the mid market, understand the problem statement, it’s not only that they don’t have the data engineers and an enterprise-level data operations team. So you know, when you’re talking about enterprise data, we’re not just talking about the tooling and the technology.
You’re talking about a whole governance structure, compliance structure, a whole team of Bas and program managers and project managers that are navigating between departments, creating domains of data to share, and, you know, creating dashboards and KPIs so that the company itself can share data between departments instead of keeping them in silos. It’s a massive, massive effort. And so one of the things that we realized when we started interviewing, you know, people in that mid-market space, and our first board advisor, who we interviewed to design it, was Pat Turpin, who you mentioned earlier, who was the founder of Popchips and before then was at Costco, and it was on the board of 12 other CPG companies that are mid-market. When we sat down and interviewed him to really understand the problem, it’s it was he who oversaw all of the data and systems in the mid-market. It is mechanical.
It’s a break-fix. It’s its help desk. If they have an integrated information system or data operations in it. Yet they don’t have the resources for it. Right? So they typically upskill a help desk service engineer into becoming a director or VP. And that’s it. And so. What we realized was that in order for us to target the mid-market, we have to design our solution to be operated by someone like Pat, the CEO, CFO, or COO. You can’t gear it to be managed by the help desk person. And so when we got rid of the UI, UX, we got rid of that administrative portal because there’s no C-level executive that’s going to want to go through a two-month super user course to learn how to administer any software. They’re just going to want someone else to do that. And so naturally, you know, the interface is like a chatbot, right? You ask it to do something, and the AI follows you around and learns from you on how you want to do things.
And, it needs to learn the difference between how Pat wants to do it, versus how Deron wants to do it, versus how a worker bee employee wants to do it. You know, it needs to know the difference. And so, you know, and, and the last thing a C-level executive wants to do is manage multiple chatbots. They don’t know how to do that. And then, you know, worry about the user provisions and security concerns and governance and compliance concerns. So all of that needs to be baked in. And so if you want to create a system that a C-level executive can manage, you cannot build it around a GUI. You don’t have the time and resources to manage that. And so this is where the service of the software model comes in, for us, you know, our entire solution, from designing to implementing and managing the AI, is all tied into the subscription. They don’t need to hire anyone for it. They don’t need to learn anything. It’s the job of our platform to learn.
Dr. Jeremy Weisz: 21:02
So, Henry, let me just see if I understand. So in an enterprise, obviously, there’s a software, but there’s a team of people that can implement that software, or they hire a high-level person for six figures or whatever it is to do it. And so you found, well, you know, we could provide the solution, but also the service as well, right? For this, the mid-market. So you can come in, you don’t have to hire, you don’t have to have a big team. You don’t have to hire a separate, high-paying consultant to implement something. And you could plug right in. What does talk about the onboarding for a second? Because I know it’s probably, you know, there’s different onboarding in each of those, I imagine.
Henry Park: 21:47
Yeah. No. And what you just touched there is the beginning of the services software model, right? The implementation design, the actual activation of that software, is baked into the service model. Right. And into the AI. But when we talk about service software, it goes more than that. So the technology itself is designed to really. Accomplish outcomes and functions that companies typically would want to hire a role for. Right. So, you know, the implementation being baked into a new AI SaaS model is a given, but to really make it impactful for any executive that’s focused on, you know, quick decision making, you know, activating the business, growing the business, scaling the business, they’re going to want to make that AI accountable.
They’re going to want it to be given certain outcomes and goals that they want to achieve. And it better go really fast. And so our implementation process is very different than a traditional SaaS model where the traditional SaaS model, where you design it around features and function, right? And there’s a whole implementation, and then you have to go outsource it. And then you’ve got to, you know, outsource a team to maintain that over time. Although the SaaS, the traditional SaaS model includes, you know, upgrading the software and maintaining the software, well, you still have to, you know, deal with all of the upgrades around your workflow and all the functions that you need to maintain.
And then you have to hire an administrative team to run it, you know, and manage it. So, you know, all of those things are actually baked into the new AI services software model. But really, when we’re talking about implementation, it’s very different. We sit down with the client and understand what the outcomes they want are. It’s almost like an interview where we’re going, hey, you want this role filled, right? So, typically, what ends up happening is we meet with the client and realize that they have a unicorn role. They’re trying to hire around like data analysts or financial analysts. And, we look at their job description and go, wait a minute. Like, do you really want this in one role? Like, I’ve never heard of that. You know, this is exactly.
Dr. Jeremy Weisz: 24:32
I saw a post on social media the other day. I was like, I need somebody who knows a guy who can sell, who can do outbound. I’m like, those are like four different positions in one, right?
Henry Park: 24:43
In one. Right. And that’s like the weird puberty stage of a mid-market company where they’ve grown past their, you know, mom and pop operation and now they’re getting into more enterprise, you know, function and environment. And then they don’t know what to hire. So they got this crazy unicorn hires like 3 or 4 jobs in one in data, in systems management.
It’s typical in the mid-market. So, the data analyst or the financial analyst is the most mis-specified role. And so, you know, when we’re talking about onboarding and sitting down and breaking that down and going, okay, what do you really need?
Like, you know, beyond your controller and your CFO or your COO and your CEO, what do you really need in this role? And let’s, let’s figure out what you want the AI to do. Because the AI can do it, you know, a thousand times faster. Than a human being. And then breaking down that role and going, okay, here’s the human role you need to decide and discern, because AI is not really good at that. It could mimic certain things, but really, deciding, really discerning AI is not built for that. It’s its reactive inference. That’s the AI that’s in all the large language models. It wasn’t designed to actually think proactively. It’s mimicking a language pattern, right? And so, you know, we design our solution around outcomes and roles. And then we have the AI fulfill and augment the human in the loop model.
For us as an architecture, we always have someone human overseeing the AI and learning. The AI is going to tell someone to learn, you know, in ChatGPT, it’s the individual, right? In an enterprise environment, you need it to be around roles with data permissions, governance, and auditing permissions with different levels of data access and security access. I mean, you need to do it in enterprise format because these bots, they work 24 hours a day. They don’t stop. So who’s going to oversee them? You need a you need an enterprise structure to do that.
Dr. Jeremy Weisz: 27:00
So the first step is, I mean, what I like is just your approach to the client, the customer, right? And focusing on what they want and the outcomes and roles, because it’s all about how it’s going to benefit them. How are people using it? Like, what are they using it for? Are there some examples?
Henry Park: 27:17
Yeah, they’re using it for a lot of different things. You’re ultimately at the core of what our product does, which is to create a single source of truth for data. So, you know, most companies, most mid-market companies, they don’t really have a functional data warehouse. They might have a limited data mart. They’re using BI tools first before getting their data ready. And so most companies are mid-market companies. If you’re dealing with BAE Systems before you have an enterprise data warehouse, you’re only dealing with like 10% of your company data. You need to normalize 100% of it.
Download all of the source data from all your enterprise systems and all of your Google files from the last 15 years that you’ve been in business. You need to take all of that and analyze it, normalize it in a way that’s functional for the business, and that’s the core of what we do. And then we layer various AI functions around it, just like a large enterprise would. So it varies, you know, for access partners, it has a lot to do with inventory management, which has a lot to do with pairing that up with sales forecasting and margin analysis, really breaking things down into.
Dr. Jeremy Weisz: 28:35
For what type of business is that?
Henry Park: 28:38
It’s a, it’s a private equity roll-up of food supply. It’s a distributor for food supply and janitorial products for various industries. It’s in the distribution industry. And so they’re really focused on understanding, like, you know, what’s cost per SKU all the way down from every, you know, facet of the business and every operational cost. And in order to do that, you need to integrate everything from payroll data to inventory data to the ERP data, right? And your warehouse management data. All of those things need to be integrated to understand the true cost by SKU. And you know, that whole process of doing that can be very, very manual. If you’re dealing with traditional SaaS platforms like ERP or CRM, you know, they don’t have AI bots interwoven into the data in between them. You know, it’s, they may be now developing AI within their own tool, but, you know, it’s just within their own traditional SaaS environment.
Dr. Jeremy Weisz: 29:51
I think, Henry, you know, with like, from an e-commerce perspective, obviously, if they’re not tightly managing their inventory, that’s real cash that they could be losing or using for something else. How big does a, you know, e-commerce company, I mean, in this case, you know, there’s a lot of food. I’ve had a bunch of protein bar companies and kombucha companies on the podcast. How big does a company have to be for it to go? Okay, it makes sense to use Pandoblox.
Henry Park: 30:19
That’s a good question. And at first, it was the 50 million to 500 million a year company. But it’s going both down and up. So, you know, we’re talking to the CEO of an architecture company that’s, you know, 15 million in revenue. But she’s realizing, you know, how many manual processes she has. And so she’s scaling and growing. And so instead of hiring people that are averaging, what, $100,000 a year in salary, she wants to implement AI, right? And so it’s, it’s going down to that $15 million a year mark on the high end. We’re, we’re dealing with an e-commerce company that’s, you know, dealing with a lot of electronics that’s in that, you know, 600, $700 million a year, year, year phase. And, you know, what they’re looking at is they’re used to having, you know, 18 people in their data team. So they have one team focused in on IPAs, the traditional SaaS like Zapier, you know, the Zapier model and the Dev Bhoomi, and all of those are in that IPAs space, right?
Integration platform as a service. And then you got the data warehouse stack, right? AWS, Azure, or whatever. All of that is, is one pillar. And then you got the BI stack, which, like the Tableau and Power BI of the world, all three stacks are managed by different engineers, skill sets, and operations teams, right? So, you know, this company had 18 people, you know, managing all three stacks. And now they’re looking at using our platform because our platform is one stack. All of that is just one subscription. And then on top of that, they get a large language model with it. They get all sorts of reasoning models into it. They can build as many AI bots as they want. And so. They’re looking at reducing that team of 18 down to three, one in each department, or yeah, one in each. That’s focused on working directly with the business units in outcomes-based modeling for their data.
And we’re wrapping all sorts of AI around them. And so we’re finding that our approach is working for the smaller end of the market as well as the larger end of the market, because all, you know, what, what, what people are missing in this services software model. What they’re missing are people who know how to work in that operating system. It’s a very, very different way of operating than in the traditional SaaS world, because in the traditional SaaS world, you had to, you know, hardwire and, and, you know, create all sorts of guardrails around things and, and scope things out, you know, in a very tight scope of work, you know. But in an AI environment, man, you’re actually building together with AI and adjusting and iterating at a much, much faster pace, assuming that there’s going to be changes because depending on how the AI actually learns, and the human decides around various workflows, the AI is going to adjust.
Dr. Jeremy Weisz: 34:05
What about Hallmark? I know you’ve worked with Hallmark. What, what kind of roles or functions did they were they looking for?
Henry Park: 34:15
So there’s not much I there’s not a lot I could share on Hallmark. But, you know, one of the things. One of the things that I could say is. They are a very interesting company for us in that their strategy is to integrate all their different companies together. You know, they’re they’ve got the retail, they’ve got the brick and mortar business, which is the biggest part of the business. And then they have Hallmark Media, which is a very successful branch. And so, you know, their strategy is to have, you know, a single company that has a culture and strategy between all the different companies. And so, you know, there’s so much you could do in that kind of environment with AI, but you have to do it in a new services software model versus the traditional SaaS model, because there isn’t anything really built for an environment like this, right? Right. There’s no traditional SaaS model built just for them.
Dr. Jeremy Weisz: 35:36
So on the partnership perspective, Henry, I can see you mentioned, you know, access partners. I can see how, if a private equity group has a portfolio of companies, they may want to roll it out and use it across different companies. What other agencies are you finding that do data analytics for different companies, are using Pandoblox as a back end to help these companies, or who are like the partnerships that you’re finding are attracted to what you do?
Henry Park: 36:13
And it’s growing. We just launched our product last year. Mid last year. One of the interesting partnerships is the managed service providers. Traditionally managed service is growing by the way by leaps and bounds. Actually, private equity is leading that. So they’re consolidating it. MSPs, it’s pretty incredible. It’s come back. But the traditional IT MSP model is around break-fix, around infrastructure. And so they typically don’t have the systems teams and the data operations teams to be able to. To implement anything at scale. You know, I think a lot of these MSPs are trying to implement Copilot, Microsoft Copilot, but that, you know, most enterprises aren’t happy with that, right? You know, they.
Dr. Jeremy Weisz: 37:15
Because they’re implemented, it’s like a closed AI system, and it’s very secure as opposed to connecting it outside their closed system.
Henry Park: 37:25
Yeah. And it’s a templated copilot where, you know, you’re not able to split off various data layers, like the, you know, you would need to split off the engagement trace layer to really be able to extract and control what the AI actually does. You know, the copilot model doesn’t enable you to do that. It’s very templated. And so, you know, most companies are doing very little with Copilot. That’s a big, big issue with Microsoft long-term that they need to strategically address. You know, here Claude’s eating their lunch. You know, they’ve opened up the data model to have engineers be able to do a whole lot more, you know, internally we use everything. We use Gemini Claude, you know, open source, you know. We we don’t we don’t really use ChatGPT internally. But yeah, there’s just a lot of these that MSPs are using traditional SaaS tools, and they’re just not built to be able to flex and be able to work directly with what the client wants. And so we’ve built our environment, including the people who manage these tools, to be able to really focus on the client and focus on the outcomes they’re looking for and deliver on outcomes, right.
And so I think it’s MSP is a really good partnership and a way to grow. You know, data analysts, you know, what, what is our biggest growth is partnering with business consultants. So, you know, the mid-market focused Ernst and Youngs of the world, the mid-market focus. Accenture’s of the world. Because, you know, they don’t have a full stack, you know, development team at their beck and call. You know, they can’t provide the entire Accenture-type solution, right? They just want to focus on the business consulting, right? A lot of them are fractional executives, like a fractional CFO, a fractional COO. There’s this huge movement in the business consulting world around fractional. And there’s a PE firm that backed fractional AI, which was, you know, and they spent a, a gob of money. They just burned it, man. It was they spent, they were focused.
Dr. Jeremy Weisz: 39:58
Fractional, I mean, even mean what is that?
Henry Park: 40:01
Well, they’re providing like fractional, like AI developers and teams to go into like private equity and, you know, and try to implement AI. Ultimately, what they really needed to start it start with is a data platform to normalize their data. Because there were so many traditional SaaS models, including NetSuite and Salesforce. And, you know, everyone else is assuming that the client’s going to have the data ready to put it into their systems.
Dr. Jeremy Weisz: 40:37
Yeah, it’s typically everywhere. Yeah.
Henry Park: 40:40
And it’s in their agreements. If you look at the traditional SaaS model and the client responsibilities, it says clearly in there, it’s your responsibility to get the data right. In the mid-market, they don’t have the resources to do that. And so that was the number one assumption that influenced our design. Let’s assume that they don’t have it right.
So let’s create a platform. We’ll get the data normalized and ready for them.
Dr. Jeremy Weisz: 41:09
You know, I could see I’d love to hear, you know, really how the team evolved from when you first started till now. But I do want to just make a quick comment about. I could see how the IT MSPs, they own those relationships. They’re doing kind of like a preventative or fix on one aspect, but there’s so much more they could be doing because they’re already there, and they can, you know, implement, get the infrastructure there so they can get the data and do something with the data, with what you do. So I can see how, and they’re technical enough to help people see the light as far as that goes. So that’s interesting. What’s the evolution of the team look like for Pando Blacks over the years?
Henry Park: 41:53
Yeah, it’s, I mean, it’s getting them to realize, you know, how fast you know, AI moves. It’s been a big. It’s a bit it’s a, been a big organizational change effort, you know, implementing AI company-wide and getting people to rely on AI to do the things that it can do just much faster. And so it’s a lot of training, a lot of organizational change for us. We’re a human-centered model. It’s always going to be human at the center, right? With the way we iterate with AI and develop as this service is a software model, it’s always going to have humans in it. And so, you know, it’s not like by implementing it, we were cutting heads, right? We’re really upskilling our teams to be able to do ten times more than what they were doing before. And so we haven’t, we’ve definitely slowed down our hiring.
Dr. Jeremy Weisz: 42:55
And when you first started.
Dr. Jeremy Weisz: 42:57
Do you I’m curious, do you just start with like one developer? Like what? How did it first get off the ground?
Henry Park: 43:04
Oh, well, you know, for us on this platform, we basically shifted the machine learning ops full-stack development team over to this. And we had to bring in someone who sort of, you know, pioneered the gen AI side of things because traditional software developers, they tend to have an allergy to the way vibe coding and gen AI operates in an environment they tend to, you know, sort of part of it is looking down on it like, you know, you’re having AI do something that you should be doing and it’s not doing it as well. And part of it is, is fear, right? So it’s a big one, that was probably the biggest. Difficulty and challenge were to get our development teams to start coding.
That was what took a lot of effort. And then someone from the outside will bring in. Yeah. So it’s a it’s a big it is a big, big value stream chain change. You know, your workflows change. You’ve got to get your people. You’ve got to know who in your leadership is going to be open to that change and can lead it. You know, you need a lot of systems thinkers because, you know, AI is very limited. It’s not like a human. It’s all systems, you know, workflows. And, so you got to like get, figure out who’s who can be really good with people, but also think systems, and then re reorganize the workflows around what AI can do. It’s a big lift. It’s not, it’s not easy. It’s not the same as just using ChatGPT at an enterprise scale at an organization-wide level. It’s a big endeavor.
Dr. Jeremy Weisz: 45:00
Hey, I have one last question. First of all, thanks for sharing the journey. And I love how you’re talking about services. Software is more mentors. Those could be distant mentors like some of your favorite books, resources, and just other business mentors. I know you have a board you’ve probably learned from, so it could be a combination of both, but I’d love to hear those that have influenced you in your, your business journey.
Henry Park: 45:30
Oh man. So many. You know, I learned from everyone. You know, there’s a book by Bill Campbell. I think it’s called the Trillion Dollar Coach. He’s phenomenal. I wish I had met him. I really, really appreciate that book. You know, he talks about the practicality of how technology needs to be wrapped around people. I think a lot of that is how we’ve designed Pandoblox around our service and software model, really making humans at the center. Yeah, Pat’s been a coach of mine. I’ve learned so much from him. He’s on my board. I think one of the things he taught me about a healthy relationship at a board level is it’s, it’s, it’s, it’s not a top-down type relationship. It’s, you know, he’s learning as much as he is. I am from him. Right. On technology and all the other things that he’s been involved in. Deron’s been a phenomenal mentor and coach for me. He’s, you know, very, very successful in that traditional SaaS startup and exit.
You know, I’ve never really exited any of my companies formerly, you know, 3GC was acquired by my Pandoblox company. So it wasn’t like a real formal exit. So he’s been mentoring me to get ready for a much bigger exit. And then there’s my spiritual teacher. So, you know, for me, when I say spirit, I’m talking about your direct relationship with Creator, with your own soul, with God, whomever that could be. Yeah. I’m a very spiritual person now. I’m not religious. And, you know, there’s been so many people, you know, that I’ve learned from David Milarch’s one, the one who founded Archangel Ancient Tree Archive, John Lewis, another who’s a board advisor to my non-profit, Craig Cooke. He’s my qigong teacher. He’s also on the board of Guerrilla Community Movement with me, a phenomenal entrepreneur. He’s half Mohawk, native Indian. You wouldn’t think it when you talk to him. He’s a very accomplished entrepreneur. Doesn’t talk.
Dr. Jeremy Weisz: 48:07
Is David right here? Is this him?
Henry Park: 48:09
That’s David Milarch
Dr. Jeremy Weisz: 48:10
Okay. Yeah yeah.
Henry Park: 48:12
Yeah. Oh, he’s a he’s amazing. He is so tapped into energy. You know he can channel. He could. He’s a clairvoyant. He can talk to trees. It’s it’s it’s amazing. He had an NDE. He actually died and came back to focus on saving these ancient trees. That’s his life mission. Yeah. Jake. That’s his son. He’s an executive director. Yeah. So, you know, I think I’ve been very, very blessed with people around me who really understand what it is to be servant leaders. That’s one of the most important value points for our company is to be servant leaders, both in the nonprofit and the for-profit side. Yeah. So yeah, very, very lucky.
Dr. Jeremy Weisz: 49:15
No, I appreciate you sharing. I want to encourage anyone. Henry, check out pandoblox.com. You can see the website here. Also, check out theguerrillamovement.org. And how can people help out or contribute to the Guerrilla Community Movement?
Henry Park: 49:32
Yeah. Please donate. You know, this organization is completely donation-based, and we’re coming up with some products to really make this more sustainable.
Dr. Jeremy Weisz: 49:43
Source for cause what’s what.
Henry Park: 49:45
The source for a cause? It’s nothing more than an internship right now to teach the kids how to cook and how to market and whatnot. It’s a, it’s a donation effort at this point, but we intend to turn this into an actual product. And so we’re, as the city adopts a Rite of Passage program during the LA Olympics, 28. Our plan is to have the largest Rite of Passage circle ceremony. To celebrate the graduating class. The world’s ever seen and make it a televised effort. And at that point, you know, we’re going to launch our hot sauces, the Rite of Passage hot sauce, and make it a commercial effort. And we’ll see where it goes.
Dr. Jeremy Weisz: 50:30
I think you know a thing or two about commercial effort. So I appreciate it. Everyone, check out pandoblox.com. Check out theguerrillamovement.org, and we’ll see everyone next time. And Henry, thanks so much.
Henry Park: 50:42
Thank you.
