Dr. Jeremy Weisz: 08:21
And I will get to formally introduce you. But I’m just going to keep going on this conversation because. So I remember I had Nicole Donnelly on. She, you know, rattle off like all the different AI stuff she’s using. One of the things she mentioned was Gamma, which is for slides. And it seems like, you know, these companies are such a fast paced environment. And I love for you to talk about AI impacting not just small SaaS companies, but larger SaaS companies, because I know you have a lot of thoughts on that.
Kevin Surace: 08:51
Yeah. So by the way, I’ve used Gamma and now and I went from Gamma to Manus, which is owned by Facebook, which Facebook paid like $5.6 billion for. Right. And within a few months, other models came out. This, this, the space is moving so fast. I don’t know how you survive if you’re a small third party, because everything that these third parties are doing that, you know, where they kind of put a wrapper around Gemini or GPT or whatever. Eventually the foundational model companies are doing it.
Dr. Jeremy Weisz: 09:26
They can just come out with it. Yeah, totally.
Kevin Surace: 09:27
Yeah. Just come out with it. I’ll add it as a feature. People will stick with me. And then what do you do?
Like if you’re gamma and what you did was, by the way, if you’re Canva, you know, with all due respect to Canva, who’s heading to an IPO, I, you know, Canva is a great online editing tool for slides, right? Great. And they have some AI in there to co-pilot it and okay, fine. And then Claude comes out with an instant slide maker. I need a slide deck of 30 slides that says the following from these research points and here’s my point of view. It takes it ten minutes, but it generates stunning slides.
So if I’m Canva, how do I go? With all due respect, how do I go public? Right. Because I don’t need their editing tool. I can tell Claude to edit it for me. I don’t even need to know the tools. It’s just in the way. So we’re going from intent to finished product, intent to finish product. We’ll come back to Appvane because that’s what we do there too.
Okay. You asked about the large SaaS company. So the SaaSpocalypse over the last few months and in hitting a SaaS company, market caps. It’s probably because some companies came out and said, I replaced Salesforce, I replaced Workday, I replaced PeopleSoft, I just replaced them. A couple of my guys coded it up over the weekend, just the features that we needed. And so we’re dropping our subscription.
No question that you can get Claude to code you essentially a look alike Salesforce that has just the features that you need, not the 100,000 features they have. Right. And you will be able to make that work for you. In fact, it’ll work perfectly and it’ll be fine. It’ll save you money. But here’s the downside. The downside is are you really in the CRM business? No, you’re, you know, you’re manufacturing trinkets and selling them whatever it is. You manufacture water pipes, you sell them, you use Salesforce as your CRM. So you’re the water pipe business. You’re not in the CRM business. There is no question that you could code your own and bring it up. But now you have governance issues and databases. You have all kinds of things that they deal with and security issues and all that, right? That now you’re in the software business, you’re running a, you know. So I get that they’re charging you $5 million a year, you know, to use Salesforce or whatever the number is. However, you’re paying for a lot more than just the features in the software.
So I suspect that while startups will indeed code their own CRM because they want to save the 100k a year because it’s real money, they could put into something else large companies, which is the majority of business on a Salesforce or a Workday or a PeopleSoft or an SAP or something, are just not going to walk away from these vendors and say, three kids in a garage or in a code one up for me, they’re just not going to. Now, here’s the little fly in the ointment. Fly in the ointment is a startup in Silicon Valley, instead of spending the $5 billion that Salesforce spent to eventually get the product that they have today could build Salesforce’s product for nothing and take on the governance and the other things and sell their product for, you know, $2,000 a year. Just undercut, literally undercut Salesforce from the bottom up. And now you’ve got people who are paying 200,000 go, I’ll just pay 2000. I’ll pay 5000. Right? So that’s where I think the risk is. It isn’t that every company is going to go build their own Salesforce. It’s a ridiculous idea. But startups will build a Salesforce replacement and do so in a weekend.
And now one more fly in that ointment. If one startup can do it in a weekend, 100 startups can do it in a weekend. So there’s going to be a very, very, very competitive business because what we’ve done is democratized the ability to write SaaS. Big SaaS systems. Democratize the ability. It used to take a thousand coders five years, and now it takes two kids in a garage the weekend. I’ve got a guy across the street from me. I won’t tell you what he’s doing, but he came over and he said, I’m not a coder, but I want to build this SaaS system. And he started about a year ago. He started thinking about it, and in the last couple of months he went to Claude and had Claude code the whole thing. What he showed me was stunning. And if we were talking about doing it the traditional way, I’d say, go raise $2.5 million, hire a handful of coders, spend a year, year and a half doing this, right? He did it in a month himself. He’s not a coder. The front end, the back end, everything. And it works. And it’s a SaaS, an important SaaS system of which there’s no competition for today. And he said, what I like about this is I could whip this up in a few weeks myself. It cost me $40. But the downside is anyone else can whip it up themselves in a matter of weeks. It costs $40. So there’s no moat like software used to be a moat because you needed somebody. It may no longer be a moat itself, right?
Dr. Jeremy Weisz: 14:40
So where do you see things not being replaced? You think, okay, the people are going to win know how to sell, right? Because everyone can create it, right?
Kevin Surace: 14:52
Well.
Dr. Jeremy Weisz: 14:52
Where do you see people?
Kevin Surace: 14:53
Probably. I guess first thing it does is it lowers what AI is going to do to every field, right, is lower the cost of goods and services because you can make things, deliver things, service things at a much lower cost, because most of your cost is human capital and you don’t need as much human capital to put some of these things out there, right? So it is possible that the ASP on a CRM goes from 500 000 a year to 50,000 a year. I’m making it up. But that could be with Joe’s CRM, right? Could be.
So you have to think about that. And I think that’s going to happen in every industry. I don’t, I wouldn’t tell you that a Salesforce and a Workday and stuff won’t respond. They’re going to have to. They’re going to have to figure out how do they play. And maybe they introduce a lower cost product that has limited features that competes really, really well with a bunch of startups that have low cost products.
Who wins in the sales game? The problem is the sales game is turning into an AI game itself. All the go to market is being driven by AI. AI is placing calls, AI is answering calls. AI is sorting through the leads. AI is prioritizing leads. Like all of that is happening, right? If you’re not doing that, you’re behind. So everybody’s got the same tools. Like all my companies are using a whole AI stack to find customers, target customers, get to customers. ET cetera. ET cetera. And everyone’s using the same thing.
So I don’t know that someone’s going to beat someone else simply because they’ve got a better sales stack. They may have better salespeople, more experienced salespeople. They may have the killer closer or 2 or 10 or 100 or 1000. Right. But I don’t, I think we’re all going to use the same AI stacks.
And so again, it’s going to be a highly competitive world. We are not going to be in a place where there’s 1 or 2 SaaS companies that do x. There could be a hundred that do it because again, two guys can go whip this thing up, not SAP. It’s a huge ERP system, but probably most other things, right? A lot of things. I mean, look at Epic not to pick on them if you know who they are, but they run basically.
Dr. Jeremy Weisz: 17:10
They’re in Wisconsin. They’re private, I believe.
Kevin Surace: 17:12
Yeah, they’re private, they’re private.
Dr. Jeremy Weisz: 17:14
I went to Madison for school. So I’ve heard of Epic, you know.
Kevin Surace: 17:17
Huge company. And, and what’s fascinating about that is they are, pretty much they own every doctor’s office, every hospital. Right? Everyone’s on Epic. It’s very, very, very expensive, you know, $17 million a year per hospital or some crazy thing like that. Right. And yes, there’s lots of governance around it. And there’s, there’s a lot around the thing, I get that. But in the end, you’re storing patient records and you got billing associated with that. So is it possible that someone comes along and instead of Epic spending 30 years developing that software, someone comes along, writes basically what you need in AI and delivers it to a hospital for $1 million. Undercuts Epic. Disrupts Epic. This is how you disrupt businesses, right? And probably picks up a handful of hospitals and has a nice business.
I don’t know that they get public, but they probably have a nice business with three people working there. You know what I mean? It’s very interesting. So these are the things we have to think about. Every business being disrupted. The internet came and disrupted most of the businesses that we know and those who didn’t participate in the internet, most newspapers, died. It was that that was the end. So that’s going to happen with AI. And we’re just getting to the very start of it. It’s going to be a fun ride.
Dr. Jeremy Weisz: 18:40
Well, Kevin, I’m going to formally introduce you now that we’ve just jumped right into it. And before I do, this episode is brought to you by Rise25. At Rise25, we help businesses connect to their dream relationships and partnerships. We do that in a few ways. One, we’re an easy button for a company to launch and run a podcast with strategy, accountability, and the full execution. Number two, an easy button for a company’s gifting. So making gifting, staying top of mind for clients, partners, prospects, even staff from a culture perspective. You just give us the list and we do everything else. It’s not like Kevin, I guess like a labeled mug. I like getting food. So we send food. So I’ll think of sending someone a sweet snack every 3 to 4 months for 4 to 5 years.
So anyways, the number one thing in my life is relationships. I’m always looking at ways to give to my best relationships. Personally, I found no better way over the past decade to profile the people I admire and send them sweet treats in the mail. So check out Rise25.com or email [email protected].
I’m excited already. We just jumped right in with Kevin. But you know, he does many things. And some people consider him the father of the AI virtual assistant, even inventing the virtual assistant, which we’ll talk about. He’s been awarded 95 worldwide patents. He does speaking. He has several companies. We’ll take a look at them. Appvance AI and also TokenCore.com. And then check out the book also,The Joy–Success Cycle. So Kevin, thanks for joining me. And let’s maybe jump into, do you want to start with Appvance or Token Core?
Kevin Surace: 20:23
Sure. Yeah, sure. Let’s talk about Appvance. Appvance is a SaaS company that has been in business for, I don’t know, 12, 13 years, something like that. And there you go. Our AI finds bugs that no one else can. So here’s what’s interesting since day one because I was in the AI space, right? I started the company specifically to bring AI to the software QA space. QA automation, and we have continued to be at the absolute forefront of advancing that technology. And it’s been a really exciting journey. The challenges, however, is when you bring AI to a field like this is that many, many, many people for a number of years didn’t want it in their shop. It’s the best way I can say it. And I’ll give you an example.
There was a customer that prospect that I went and visited myself and great company and great team and all of that. And we did a little POC for them, a proof of concept. Right? And so we took something called AI script generation that takes your business rules, let’s say business requirements and writes hundreds or thousands of use cases that test those business requirements in every possible way a user could. So you’re not thinking of just specific test cases. You’re just letting it go. In just a few hours, it wrote thousands of test scripts, ran the test scripts against their production system. And when we showed up, we showed them the results.
Now they’re very proud of their production system because they have virtually no known bugs. We showed them over 200 bugs. Some of them were exceptionally serious. The QA, some of the QA leaders and some of the QA team members were in the room. In the room. It was like I slapped them in the face, you know, because what they’re thinking of is this thing wrote thousands of test scripts and ran them in a couple of hours. It would have taken us months to do that. But moreover, we’ve had years to do it and we never found those bugs. And by the way, the bugs are repeatable. Here’s the script to repeat it.
We didn’t get that order. They didn’t want us around. Now, you know, if it was up to the CIO, he or she would want us around. But off of the CIO isn’t in those meetings. It’s QA manager, QA director, QA team members. So one of the things you find is you bring AI into some of these roles, is that some of the people really push back against it and go, that thing’s finding bugs that we haven’t found in years. I look like an idiot. I don’t want, I’m going to push this off as far as I can. I’m going to sabotage it.
And we’ve had several cases where actually people on the ground did sabotage it. They actually put lines of code in the AI written scripts to break them, and we could tell they were human written, they weren’t something that the AI would have written. And of course they’re telling us, no, no, no, no, we didn’t, we didn’t do that. I’m going. Yes you did. Yes. I’m not stupid. Yes, you did. So, but here’s the bottom line. If you’re a CIO or VP, and you care about the quality of your software, both for internal use and external use. And most software’s used internal in a company, by the way, a little bit faces the outside world. This technology finds bugs. No other company, no other technology can. You don’t need to use a recorder. All of this is automated. It’s ridiculously incredible.
And you know, we’re super proud of the AI team that built this and the customers who are on it. You can see some of the customers around here also, I’ll give you a case study. One case study, insurance company, they had some applications and some teams that were very underfunded. They didn’t have enough people in those teams. And so they let AI script generation, you know, generate scripts and generate tests and find the bugs. And the net result is after two years, they estimated not a 100%, but a 100x. 100x improvement in productivity. That is, it would have taken 100 times more people than they had to get the results that they got from this. Now, they would have never hired 100 times the couple of people that they have in that group, to be clear. Right. But to get the results equivalent to do that work, it was 100x more.
So I love it when an AI, you can get more than a ten X productivity improvement. That doesn’t say you need to get rid of 90% of your people. It says you can finally catch up on that incredible multi-year backlog you have of bugs and features. That’s the whole point of leveraging AI in that way.
Dr. Jeremy Weisz: 25:17
Well, Kevin, what’s interesting about this, and, you know, I’m interested to hear how the sales process changed depending on who you talk to. But what’s interesting about this is like, especially with the advent of everyone using AI for code, they’re not some of them are, like you said, are not coders, right? So this tool seems like everyone’s going to need it because they’re like, I don’t know what it’s creating. I’m not even a coder. I don’t know what to look for anyways. And they’re going to be writing things up. I’m curious when you started the idea because you know too much about AI, like, okay, I don’t want to create something that’s just going to be disrupted overnight. Like you talked about. It’s just a skin, a wrapper for something else. What gave you the idea for, for this to move forward with?
Kevin Surace: 26:02
Yeah, $120 billion of spend in the QA world around the world today. 120 billion. 119 billion of that is people. That’s a very simple financial analysis. When you have 119 billion of people in 120 billion of spend, this is an area that is ripe for technology disruption. Because all people, lots of manual, 70% manual testing. The rest is automation, but very slow automation, writing scripts by hand, line by line, and incredibly painful things that people are doing.
And what I want is a machine to just go find my bugs. In fact, the whole idea of scripts and all that just I don’t care. So, you know, the company is really about, here’s my intent of what I wanted to build. Tell me if that’s what we built. Do all the features work the way they’re supposed to? Are there any bugs against the sort of business outcomes, business requirements that I have? And that’s what everybody wants. That’s what you need, at least at the CIO level. Like I said, the lower you get in the organization, like in customer support today, the lower you get in the organization, the more people push off AI and say, I don’t want any of this. Make it go away. This can’t be good for my job.
My recommendation to everybody listening to this is you want to be the robot overlord. You do not want to be the person sabotaging the AI rollout. You will lose in the end. Like AI wins it. Whether it wins this week or wins in three months or it wins next year, it wins. You lose. So you want to be in front of it and say, I’m going to go learn this. And the companies that have been the most successful have formed a tiger team that said, you are highly incentivized to make this AI work, make it happen. And so they’re focused on that. But if you roll it out to all your regular teams, these people think their job is on the line. And it may or may not be, but it is if they don’t like the stuff, right? So or if they lie about it, they sabotage it. So, so that’s, that’s my advice. Anyway.
Dr. Jeremy Weisz: 28:08
I feel like that’s a great what you said is a great investment thesis. I don’t know if you do investing, but the people versus spend. It seems like such a succinct, obvious thing to look at there.
Kevin Surace: 28:20
When it’s 99% people and 1% technology, you go, wow, I think we can use technology to change that balance. And even if you change it by 2 or 3%, it’s billions of dollars, right? It’s really fascinating, really fascinating. So, you know, we’ve been in a leadership position from a technology standpoint. We’re not the largest company out there, but people finally, it’s interesting. Prospects will come and go, oh, well, it’s too expensive. Or it’s this or it’s that or I found this recorder over here.
I said, it’s okay. Why? You’ll be back. Inevitably, they come back in a year and go, you know what? Those people, they said they had some kind of AI thing. We didn’t see any productivity improvement from it. I said, here’s the reasons why I told you that last year. Would you like to try the real deal now? Okay, well, we’ll try it. And then they go, wow, you’re you’re right. You just found bugs that they never found. Yeah, they can’t find them. It’s all manual. No. You know, those are manual assisting tools is what they are. Anyway, it’s an interesting industry.
It’s an interesting industry because the vast majority of people in QA don’t code or code very much right. They can write some selenium scripts maximum and that’s about it. So you’re looking at a different set of people than developers and coders who code who, who are quick to embrace AI, right? So mostly coders aren’t looking at AI as replacing their job. They’re going, I’m going to be the overlord of this thing and I’m going to, I’m going to get my backlog done. And it’s fine. They’re coming around to it.
But if you’re a manual tester and all you’ve done for 25 years is you get a set of test cases and you literally manually do them and you report back whether it passed or failed. And this thing comes along, it writes a thousand of those, tests them all and delivers the results in an hour, which you, yourself couldn’t deliver in a year. You, you think it’s over? It’s over. Like we’re all done. Wrap it up so I can see why people are worried for sure.
Dr. Jeremy Weisz: 30:28
Do you see there being a transition for those people? Like have you seen companies? Oh, obviously companies use you, but those people are doing manually, what do they do with those people? Do they? Oh, they’re doing higher level things at this point or like they don’t need those people. What are they transitioning to? I guess it’s like a good person.
Kevin Surace: 30:49
Yeah, yeah, yeah. So, so, so, you know, great question. In a lot of areas, we see transitions upward where people become really, really the robot overlord, right? So you’re seeing this in development. We are not seeing mass layoffs of developers. What we’re seeing is people accelerating their development cycle. So instead of even in, you know, instead of a two week sprints, maybe they’re two day sprints now.
Dr. Jeremy Weisz: 31:14
They just get more done in less time.
Kevin Surace: 31:15
You’re just getting more done because there was a huge backlog anyway. But some, you know, some roles don’t scale. Like if manual testing simply goes away because they don’t need it. I can’t train a manual tester to be the robot overlord or to evaluate all of the bugs that come back like they’re just not they don’t have those skills, right? So they’re going to have to reskill in some way like other people will. I think there’s some people in customer support that in some areas, especially offshore, may be have to be reskilled because AI is answering the phone and answering the things.
Now, mostly what we’re doing in customer support today is augmenting CS. So you see these two things working together hand in hand, but in some cases they’re replacing. So there are roles that are going away. But actually over the last two years, the Wall Street Journal did an analysis. 640,000 new jobs with AI in the title were created that didn’t exist before two years ago. So more jobs have been created by far than any have been lost by AI. And I think this whole job apocalypse probably overrated, probably not going to happen.
There are some tasks that go away. I agree with you. They’re gone. But overall, we’re going to create more jobs than we’re going to lose. And here’s the reasons why. Two things. One, there’s a macro population situation, certainly in the United States that is very serious. That is, for the last 20 years, less people have been born than were dying. And so people are leaving the workforce faster than they’re able to come in. So if I said, Jeremy, you want to double the size of your company, if this was five years ago, you’d say, I need twice as many employees. That’s how I do it. Well, today there aren’t twice as many employees. That’s not going to happen. More leave the workforce than come in. So we have to, if we want to grow, grow with the people we have and in fact, grow with less population than we have because they’re leaving faster than they’re coming in. That’s a macro problem. I know one company might beat out another and this and that, but overall across the US, that’s where we are. I can’t change that. Right. So we want to increase productivity and have AI close that gap of the people who are missing.
The second thing is, as you use AI to get more out faster, you drive down the cost of goods and services. And when you drive down the cost of goods and services, what always happens, the demand goes up as the demand goes up. You actually need more people because there’s other elements that you have to service, right? You have to build something on the line or whatever it is. So actually, we’re going to increase the demand for people, but they may not all be in the same roles they were in.
Dr. Jeremy Weisz: 34:00
I know with your book, you told me before you record this is your first and last book, but I have the title for your next book, which is Elevated to the Robot Overlord. Right? So that’s the title of your next one. And then you just go in like everyone use our software because you’re just elevated to the, you gotta get Appvance. Don’t worry. You’re, you’re elevated to the, you know.
Kevin Surace: 34:24
Robot overlord.
Dr. Jeremy Weisz: 34:24
Overlord. That’s it. Right?
Kevin Surace: 34:27
Well, but look, what do finance people do, right? When we came out with Excel in 1989. And all these people had pencils and ledger books. And they, they literally looked at that and said, my life is over. This is what I, this is finance. I do ledger books. And then everybody graduated and learned to be strategic financial people. And we employ more people in finance than we ever have. And nobody is working with a pencil on a ledger book. They’re analyzing those outcomes and deciding where to spend money and how we spent money. And did we spend it right? And is that the direction of the company, blah, blah, blah.
So we’ve been through a cycle like this before where a model came out and solved math forever. We don’t do math anymore. It’s solved math forever. And everybody got reskilled and it all worked out and they became the Excel overlords is the truth. And that’s where we are.
Dr. Jeremy Weisz: 35:16
There’s going to be an overlord series then I guess.
Kevin Surace: 35:18
Overlord series yes.
Dr. Jeremy Weisz: 35:19
Overlord of the Rings.
Kevin Surace: 35:21
Overlord of the Rings.
Dr. Jeremy Weisz: 35:24
Tell me about how you got the label, whatever you want to call it. Father of the AI virtual assistant.
Kevin Surace: 35:32
Sure. Well, I started a team at a company called General Magic Public Company around 1996, I think. And at that time, the flip phone was just becoming popular, Motorola flip phone. And the internet had just kind of launched in 1995, and we began to be able to share and get email. Right. You know, corporate email. And we had a calendar that could sync over the web now. So now we’ve got calendar, contacts, email, we’ve got all this stuff happening and there’s no Wi-Fi. So once you left your desk, you left all that stuff behind. That was the end. You didn’t even know what your calendar was. So we carried paper calendars, we’d write it down, etc.
So I had the brilliant idea to create a virtual assistant, because if you had a virtual assistant, well then you could call her from the car, from the airport, from wherever you are, and she would tell you what your calendar is and tell you where to go. And so that’s what we did. We built the very first virtual assistant. Her name was Mary, and it was promoted under many, many brand names. We had about 3.5 million users. The Excite virtual assistant, OnStar virtual advisor built that, Portico, My talk, Magic talk built stuff for quest. It was amazing. And she could answer your phone for you. Hi, Dr. Jeremy Weisz’s phone. How can I help you? Hi, this is Kevin Surace, I’d like to make an appointment. Oh, well, I see he knows you. You’re in his contact database. You should do that. When would you like an appointment? He’s got an opening on Wednesday, and she would. She could schedule appointments for you. I mean, we were. So. You can’t even do that now with, like, Siri. So it was fascinating.
And I lived on Mary. I mean, I had to live on that. It was totally amazing. And it changed my life.
Dr. Jeremy Weisz: 37:27
So these companies would be like, Kevin, we need this. And you’d go in and build it for each of these companies so they could use it with their systems.
Kevin Surace: 37:34
Yeah, exactly. So we would integrate it like with Excite, we ran the entire ops center. There’s no remember, there’s no SaaS, there’s no cloud then, right? So it’s literally my, you know, my ops center, we built an ops center. We ran it in Sunnyvale, California. All calls were routed into there and routed back out. All the servers answered the questions. Yes, we had response rates of under a second. We had rec rates in the 97% range recognition rates. I mean, we did a really, really good job.
We were the first people to have linguists that listened to every conversation and make the answers better, which, by the way, is what we’re doing with AI today. If you know, that’s kind of what we call post training and there’s like scale AI. All they do is look at what came in and look at the answers and make sure that they’re aligned. So we invented post training and that’s one of the patents. I mean, all these patents. So we had a dozen patents out of there or so.
And then eventually Siri, a company, a startup started leveraged our patents. They did every they didn’t license them, but they used them. And then they sold to Apple. And once they sold to Apple, it wasn’t in, you know, within a week that the patent troll showed up and said, excuse me, I think I think you owe me a lot of money here. Troll is too strong of a word. But there was a company that bought the patents.
Dr. Jeremy Weisz: 38:57
Right.
Kevin Surace: 38:58
So nonetheless, you know, Apple paid billions. Everybody paid billions for that stuff.
Dr. Jeremy Weisz: 39:03
So is that typically how it works? Do they just say, hey, we’re going to pay you this for the license or there’s like a yearly fee or something like that?
Kevin Surace: 39:10
It can be usage, could be annual, could be upfront. It’s up to the patent company. Often they don’t go after startups. People said, well, why didn’t they go after Siri? They hadn’t. Siri had no revenue. Who cares? But once Siri as a company sold to Apple, you know. Knock, knock. Hello? We’re here. Because then there’s real money, right?
Dr. Jeremy Weisz: 39:35
Yeah, there’s good I guess a good lesson for diligence. If you’re buying a company, you should check if they’re using people’s patents.
Kevin Surace: 39:41
I suspect Apple knew because General Magic was a spin out of Apple. And we invented the virtual assistant. So Apple surely knew Microsoft took an early license for a very low number, $5 million, a forever license just for Microsoft. So they got ahead of everybody. And it’s very interesting. Other people paid billions. They paid 5 million because they got in early. And that helped General Magic because it, it, we had some co licensing and some other stuff. And General Magic went from being worth, you know, $100 million to being worth $1 billion, partly because that license put General Magic back on the map as a public company. And they said, well, if Microsoft is licensing stuff from something’s going on here, I don’t know what it is. And that’s what was going on. We were inventing the virtual assistant.
Dr. Jeremy Weisz: 40:33
Nowadays, how do you determine we should spend the money and time to get a patent around something? Because I think right now you have like over 95 worldwide patents at this point. Yeah.
Kevin Surace: 40:47
Look, it has to be unique enough where you’ve got unique claims that are worth protecting, right? Most I mean, if people haven’t done patents before, what they think is patentable isn’t. Oh, I’ve got this idea for a remote and it’s going to be blue instead of black. Okay. No, not patentable. Right. You know, what people don’t realize is it can’t be obvious to those working in the state of the art, and that is up to the patent officer to decide, you know, patent examiner. Is that true?
And so if you’re just changing the color or something, you’re adding a little button or that isn’t patentable, you have to come up with something that is really unique and defendable. And at that point, an AI assistant was absolutely unique and defendable because there were no others, right? No one else could interact that way. We made a home phone also that never made it to market. But what we did is we, because of limited processing power on the phone itself, we converted the audio to vectors, the voice to vectors, voice vectors, and we sent the vectors off to the server and then the server would come back with voice. Okay, that’s how we did it.
Well, until the last couple revisions of the iPhone, that’s when you talk to the iPhone, Siri would say one second, please, and it would vectorize your voice. It would send those vectors to the server, and then the server would come back and answer, you know, so it was actually a pretty brilliant. That was one of, you know, 12 or 14 patents. But it was a pretty brilliant idea because the idea was we don’t have the processing power here and we won’t for 25 or 30 years. We have to send it to a server where we have the processing power and we can run in parallel, right? And that’s what we did. And that’s what Apple had to do for all these years until very recently, very recently.
So all this stuff got used en masse. And I will tell you when you’re inventing something like that, and I’ve invented stuff in other fields that I’ll tell you about, you don’t know how it’s going to impact anyone. You don’t know if anyone’s going to use it and you’re not doing it for that. You’re doing it because there’s a pain point and you’re just trying to solve that pain point for people in the car. Right?
Dr. Jeremy Weisz: 42:58
I’m going to, I know we only have a little bit of time left and so much to talk about, but I want to talk. Have you touched on Token Core, what that is and how that works? And I also want to talk about your book too. So maybe start with Token Core.
Kevin Surace: 43:14
Let’s do it. Yeah. Here’s the bottom line. Your MFA, everyone knows what MFA is or 2FA or phone codes or whatever. Or your auth apps are 100% compromisable every hour and get compromised at large companies, and they get compromised because of 15 different ways to compromise them. But the best one is a real time relay man in the middle attack. Basically what happens is you go to a spoofed site. It’s pixel perfect because AI made it. You’re logging into your site, your auth app comes up and says, is it you? You say it is you. None of it was ever you. The real person is getting relay that information. You just let the hacker and Russia in right?.
So this stops that. This is a biometric product. I have one on my finger right there. There’s a ring. That’s a ring. We make other form factors. This is a, this is a stick. You can just leave it on you. They’re all wireless. Basically it uses biometrics. It uses your fingerprint, not face, not voice, not usable anymore, as you know from Delphi. So use your fingerprint. And you cannot get into your application services systems, whatever networks without your finger. Okay. Within three feet of the logging on computer. So it has to be local because the things don’t speak cellular and Wi-Fi. Right. And to the original domain that you registered at. So there’s no way to hack it. It’s unhackable.
And the CIOs who have rolled this out across their companies, I say, tell me how it’s going, he says finally, Kevin, I can sleep at night. I know if Kevin’s in the network, it is Kevin. If Jeremy’s in there, it’s Jeremy. It cannot not be Jeremy unless someone’s got a gun to Jeremy’s head. It’s impossible. It must be Jeremy. It’s his finger. He’s within three feet of the logging in computer, and he’s logging in only to the original domain he registered at. So we’re done. That’s what this does.
That’s a new, that’s called the node. That little thing. It’s about the size of —
Dr. Jeremy Weisz: 45:14
If you’re watching, if you’re listening, there is a video piece around the tokencore.com/products because like, I think software is hard enough and now you’re doing hardware with software. So good luck, you know, but yeah, go ahead. You were speaking, there’s a node that says by the computer.
Kevin Surace: 45:29
Yeah, yeah, that’s a node. It just slap on the back of your phone or put it anywhere. It’s small. So we’ve got a wearable in the form of a ring. We’ve got lots of different form factors. So it’s something for everybody.
Dr. Jeremy Weisz: 45:41
Yeah. It’s interesting because like I’ve tried to do this on my phone and the phone is terrible. Like it won’t read my fingerprint. And I’m like, oh, screw it, forget it. Like I’m not even going to do it because it doesn’t work properly. Right? And so this is interesting.
Kevin Surace: 45:57
Ours works. But more than that here, here your fingerprint is never stored in the network. It’s stored inside the device in what’s called a secure element. So nobody can ever suck it out. Right. The problem with storing it somewhere in a computer or a phone or something like that is someone could get at it. But there’s no way to get this out of here, even if you take the device apart.
Dr. Jeremy Weisz: 46:16
So like, you know, Kevin, you know, big cyber security companies, MSPs, are they reselling this to their clients? Like hey, I have a law firm of like 50 people. We need to get 50 nodes for everyone or something like that.
Kevin Surace: 46:35
Yes. Yes. MSPs, MSPs, large companies, universities, everyone. There have been about 100 000 successful hacks compromising your MFA and auth apps, known hacks in the last two years, 100 000 and the biggest ones Qantas Airlines and Stryker just recently, same thing. That was an identity attack that compromised their auth app. It’s you know, so this is not compromisable. That’s the.
Dr. Jeremy Weisz: 47:05
Striker is like the medical device company?
Kevin Surace: 47:07
Stryker medical device had 200,000.
Dr. Jeremy Weisz: 47:09
Yeah. And that’s, that’s an issue, right? Like anyone in health care, like you all of a sudden compromising everyone’s health information, right? They share everything with the doctors, hospitals. So yeah. All right. Well, we’ll have to send this to some of I’ve had a bunch of cybersecurity companies on the podcast. We’ll have to make sure they see tokencore.com. I love it. So this is cool. The book. Why don’t we have three minutes to. But talk about the book for a second.
Kevin Surace: 47:40
The book is the.
Dr. Jeremy Weisz: 47:41
If you want to check it out, we’re at the joysuccesscycle.com. You can check it out. It’ll be linked, but go ahead.
Kevin Surace: 47:46
Yeah, no, the just joysuccesscycle.com. But yes. But maybe I should get the. Also look, the bottom line is people asked me why I have all this energy and all these different fields and keep inventing. et cetera. et cetera. And I, you know, I said, all right, I must be a nutcase or something. But I actually started to write it down. And I realized that I begin my day with joy. I end my day with joy, and I have joy in every single task I do, including being on this podcast with you. And you can see that probably. And so everything I do is a joy moment. And because it’s a joy moment, the science says my mind is much more open to find problems and solve them. And so the science supports this. And so this is 176 pages or so on exactly following all the kind of life joy hacks that I’ve had. And it’s a life changer.
You know, before this book, people are, oh, woe is me. Oh, the weather sucks. Oh, my knees hurt. Oh whoa whoa whoa whoa. It’s what we do. We complain to ourselves, right? Complain a hundred times a day after this book. You won’t complain one time a day. You won’t even do it one time. Because you know even that one time is taking away from your success. There is no need to complain about anything internally or externally. No one wants to hear you and you learn that you don’t want to hear you. It’s not useful. It’s negative energy. And so it’s changing the keynotes that I’ve given that even though the book isn’t quite out yet, the keynotes that I’ve given, I had calls weeks later that changed people’s lives at work and at home. So it’s exciting.
Dr. Jeremy Weisz: 49:24
Kevin, first of all, thank you. Everyone check out and we’re here. You can go to is he’s got a special, you know, separate page for if you are interested in having him speak KevinSurace.com to learn more. And we’ve already shared the other websites and I just want to thank you for sharing your journey, your story with everyone. And we’ll see you next time. Kevin, thanks so much.
Kevin Surace: 49:47
Thanks for having me.
