#267 - The Father of AI Assistant on Why Joy Comes Before Success - Kevin Surace

[00:02:02] Introduction

Henry Suryawirawan: Hello everyone. Welcome back to another new episode of the Tech Lead Journal podcast. Today I have with me Kevin Surace. He’s known as the father of AI Assistant. So we’ll talk a little bit more about that. But not only that, Kevin is also publishing his book, his first book, if I’m not mistaken, called Joy-Success Cycle. So Kevin, welcome to the show. Thank you so much for your time.

Kevin Surace: Thanks, Henry, for having me.

[00:02:27] How Did Kevin Become the Father of AI Assistant?

Henry Suryawirawan: Right. Kevin, let’s start from this title of yours, Father of AI Assistant, right? I can see also behind you there’s this, you know, picture about Portico. I think if I’m not mistaken, that’s kind of like the first generation of AI assistant. So maybe let’s start from there. Let’s tell a story about how did you end up becoming like the Father of AI Assistant.

Kevin Surace: Yeah, that is right. Portico was Portico was the first fully AI assistant that you could argue with and interact with and interrupt. And she would answer your phone and book people on your calendar and things we can’t even do today. We did that work at a company called General Magic. General Magic was a spin-off out of Apple and developed three major breakthroughs.

First was somewhat the predecessor to the iPhone. And the second was a language called Telescript, so that we could create AI agents, and we did. So we had agent– We had the whole idea of agents came out of General Magic that long ago in the late ’90s. And the third was this idea of an assistant that you could talk to over the phone. And the importance of that at the time was that people had just gotten cell phones, not smartphones yet, like Motorola flip phones. And they had just gotten the internet, but the internet was something you had basically at your desk at work, and you didn’t have access to your calendar and your contacts and every stock quotes, whatever, while you were in the car or pretty much anywhere else, because there was no portable device. But we could get you access to all of that via talking to a virtual assistant. So that’s what we did. And we ended up having about three and a half million people on the system at the time.

So it was successful and fun and, you know, a big development project. I think one of the fun things for your audience is there’s no such thing as the cloud then. So you built your own data center, which we did. We had to build our own data center, and it was a voice and data center because you had to take voice coming in, and you had to have voice going out, and you had to process it in between. So we did all of that. And it was a great team, great effort, and ended up resulting in, oh, you know, more than a dozen US patents, several dozen worldwide patents. And those got licensed ultimately to Apple, Microsoft, Google and others, pretty much, and Amazon. Anyone who really wanted to do voice assistants.

Lastly, one of the big things that came out of that is something called post-training. Post-training is something we do all the time now with AI, with Gen AI models. And post-training is where you have literally rooms of people looking at how the model reacted and seeing if it’s correct or not, and then putting in corrections into sort of its background programming, if you will, or background prompting. And we were the first people to do that. We invented it. It was the subject of a patent also. And we had linguists listening to what was being said. They didn’t know who was saying it, but they were listening to that and making corrections in the model so that it would be more accurate each time someone interacted with it. So lots of breakthroughs there and, you know, very proud of that team and the work we did.

Henry Suryawirawan: Wow, so, so many patents. If I’m not mistaken, you have 90 over patents.

Kevin Surace: 95.

Henry Suryawirawan: I think you mentioned a coup- 95. Okay, yeah, some of those related to this AI assistant. And it– I think it’s really cool, every company who wants to, you know, invent their own AI assistant, you know, it’s kind of like having the license from yours. So I think that’s…

Kevin Surace: Yeah, and more than that, even when patents expire, you are building on all of the work that was done in the past. This is true with all technology, right? You’re building on the work of the past. Patents eventually expire, and there were some of these patents got extended for a variety of reasons. But most of those patents are probably expired by now. They’ve hit the 20-plus year mark. And– but still, when you look at the architecture of systems, you find a lot of what we did in terms of how do you interact with an artificial human, what should that look like, how should they respond, what’s the range of responses. You know, all of that early work had to be done. And, po- the, you know, the idea of post-training, that wasn’t obvious. We were the first people to do it. Cause people would look and say, “Huh, it doesn’t always respond right. Well, we have to do better in pre-training. We have to do better in pre-training.” I go, stop. Why don’t we just listen to what people say? I mean, it was a crazy idea one day. Why don’t we listen to what they’re saying and fix it? What do you mean?

Well, we’ll build an interface so that our linguists, without coding, can just go in and say, “No, the right… This is what it said, and the right answer would be this.” And you keep training it and putting weights on those new answers. And it turns out that was a brilliant idea, but we didn’t know it was brilliant at the time. We’re just trying to fix the thing, right? And today that is a stalwart of what we do in gen AI for sure and also in AI assistance. And, you know, people like Scale AI and others have tens of thousands of people doing post-training, right? We had seven, I think. It wasn’t that many, but they were busy all the time.

Henry Suryawirawan: Remind me again which year is that?

Kevin Surace: 1998, 1999, just before 2000, yeah.

Henry Suryawirawan: And I think these days people associate these kind of assistance with, you know, GenAI, right, LLM model, right?

Kevin Surace: Sure.

[00:07:45] How Did AI Evolve From Hidden Markov Models to the LLM Breakthrough?

Henry Suryawirawan: So back then, what was the AI technology that actually you leverage on?

Kevin Surace: Yeah, great question. We used hidden Markov models, so we didn’t have an LLM. And that is a very traditional type of AI model that does learn and it can learn every time something happens. And so you had a combination of itself learning and getting better and in terms of responses post-training to make sure that we could tell the system that even though it thought that answer was right, it wasn’t the appropriate, you know, response. And again, that even with Gen AI, that’s what we’re doing because you have all this pre-training of a trillion or more tokens or trillion or more phrases. And yet still it gets some things wrong, you know. It– we say hallucinates. We never called, Mary was her name, the first AI assistant. We never thought she hallucinated. She– You know, we never used that term. We just said that that wasn’t the, the right response, you know?

So, you know, you always have to have these breakthroughs at the beginning. And obviously, I’ve been part of this all the way along. I run an AI company today, so I’m still very busy in AI and, you know. But the frontier models have gone down a path because of, one, the work that Google did in 2012 to, you know, put out in the public how you build a deep learning model, basically very deep. And then by 2017, they published a seminal paper on the transformer. And once you had that, you could build LLMs. That is almost ten years ago now, right? So we’ve had ten years of advances on the transformer and it’s still giving us paybacks. I mean, these models are getting better and– But they’re also getting better because of post-training. They’re also getting better because they can self-code. So they’ve got, you know, reinforcement learning. You’ve got, now basically self-coding, where a lot of these models are being coded by the model itself to improve itself. I think, you know, a lot of people never thought we would get there.

And I would say, in this space from a coding perspective, we weren’t there till early 2026 when Claude finally had a release that literally could build an entire application. If you remember a couple years ago, yeah, we were all using coding tools, and they were a little bit of a help. About as much of a help as me, you know, searching for some open source code. But then this breakthrough happened that was like, oh, I can get up and leave, and six hours later it wrote the entire application front-end, back-end, and it works. Once you got to that level of competency, it changed the game. And it changed it psychologically, where we’ve had programmers going, you know, for two years on LLMs, “Oh, they’ll never get rid of me ‘cause I’m still doing eighty or ninety percent of the work,” to, “I don’t write a line of code anymore.” And, all– certainly all of my coders that work for me, all my developers, they don’t even look at the code anymore. They, it… Because this Claude will write code so fast. And it’s written so many lines that, you know, you say, “I need to build this, and here’s the ins and here’s the out, here’s the API.” It goes and does it, you run it, and it works. There’s 2,500 lines of code in there. You’re not gonna look at them. You’re not gonna try to dissect what’s going on. You just ship it. You know, you gotta test it and ship it.

And so, so I think that’s really a fascinating thing and a real impact to developers who, you know, who thought that their reason for living was to write lines of code. And maybe that’s not gonna be the case anymore ‘cause the people at the frontier of this are not writing any code at all, and they’re not even reviewing the code.

Henry Suryawirawan: Yeah. I think putting aside coding, you know, I think I can also see in the past one year, you know, all these AI chatbot, you know, the, for example, ChatGPT, Gemini, you know, even Claude itself, right? I think they are quite good in terms of replying, you know, answering, brainstorming together with you, coming up with solutions, right? I think less hallucination, at least from my experience.

Kevin Surace: Yeah, that’s right.

[00:11:51] How Were Siri and Alexa Built on Kevin’s Licensed AI Technology?

Henry Suryawirawan: But I think it’s quite fascinating how, yeah, quite fascinating how this, you know, AI goes. But before then, also you were involved in these two so-called revolutionary AI assistant as well back then, which are Siri and Alexa, right? So, I think maybe people might have forgotten about those technologies simply because of the current AI chatbot. But tell us also these breakthrough that you went when you work on Alexa and Siri. I think Alexa back then when it was, you know, first time, you know, revealed, it was like quite fascinating.

Kevin Surace: I didn’t work directly on them. They licensed our technology and our patents to build them. What I can tell you is that they were built very much leveraging the sort of the models that we put forth. This is before LLMs, right? So they were all based on what we called traditional speech recognition, that did use hidden Markov models. A lot of those came from a company called Nuance. And so those kind of became the best models in the industry until LLMs came along. And they used a variety of text-to-speech, and we got– we kept getting better at text-to-speech. Early on, our text-to-speech, was that is conversion of – say, email, read my email, right – was very crude. In fact, it was often based on concatenating syllables recorded by humans in a studio and putting them all back together, and writing the algorithms to put them all back together. Because without that, they sounded very mechanical. And you’ll remember, a lot of those mechanical things. “Hi, this is the train. It is leaving for the next station.” And go, take, what? Can’t you just record that? You know, this is terrible.

So now it’s really perfect because we can build models on an actual human voice. And as you know, we can build a model on my voice or your voice in a matter of minutes. But that technology didn’t exist. And so, you had to concatenate all these things and, or record real human voices and, you know, put them back together. And a lot of people did that. We did that. You know, Siri did that for the longest time. Alexa did that. That’s what everybody did. And we had laid out the process to do that. So everybody, you know, licensed, those two big systems licensed that technology. And today, you know, everybody’s moving to an LLM backbone, if you will. And, but still many of the kind of human interface issues that we had to deal with are still used today.

[00:14:25] How Should Software Developers Evolve in the Age of AI?

Henry Suryawirawan: Right. So you mentioned about, you know, software developers, you know, their job these days will change a lot, right? So, no more writing the code, that’s for sure. Even reading the code probably is kind of like a very tough job these days because of the amount of code that AI can produce.

Kevin Surace: Yeah, it’s too much.

Henry Suryawirawan: Yeah, so what do you think the developer’s evolution should be, right, maybe from your point of view?

Kevin Surace: So we’ve seen this before, but very few developers alive today remember it. And so let me take you back to the ’50s and ’60s. Well, in the ’50s and ’60s there was something called machine code. That’s how you coded a computer. It was literal ones and zeros. Lit– And you had a table, and if you wanted to do this particular thing, it was one, one, zero, zero, one, zero, one, one, and that’s what you’d put in, either on a punch card or some other way, right? So we started with machine code. And later, I wanna say it was late ’50s or sometime in the ’60s, and it may have been IBM, developed an idea of assembler. And Assembly would be still an extremely crude language, but that language would convert itself, basically compile into machine code. Okay, great. All of a sudden, I didn’t have to worry about the one, one, zero, one, one, zero. I could say, move this register from here to there, and it would, right? And it would just put that into the ones and zeros. This wasn’t a very English-friendly language, and it wasn’t a high-level language. It was a very low-level language, but it works, and it’s very succinct, and it’s very much tied to essentially, each processor cycle, each processor, actual command on the processor. Okay, fine. So by the ’60s we had that.

And then later in the ’60s people started using the two first high-level languages, one business and one math, Fort– it was COBOL and Fortran. And that’s the first time, in essence, in English, I could do something. So early coders were coding in a language that went away because we had a higher level language called Assembly. And then Assembly basically went away for most people, and that became these higher level languages. And of course, by the ’70s and ’80s, we had very high-level languages that are really thoughtful, that are in English in essence, right? So we have seen developers move to higher and higher level languages where the language is producing, you know, thousands of lines of machine code for us. We’re not writing those thousands of lines.

Now we’ve progressed one more time to the actual English language of natural language. So if I can describe it at this level, it’ll write it in Python, which actually is compiling down to Assembly, which ultimately kind of converts to machine code. And we don’t see any of those layers. So my point is, we’ve given up seeing a variety of layers of computer programming over the years. Most people just have forgotten that because we’ve been in high-level languages now for thirty or forty years. And now we’re going to the highest level language, which is just the way we speak. And if we’re articulate enough and have a good enough specification, it’ll write all of that all the way down to machine code for us, right? Based on sixty years of effort, right?

And here’s what I would portend. Here’s what I would say, in talking to so many developers. At first, the developer has sadness and says, “All of my joy comes from or came from writing code, and I love writing code.” And so my supposition here is that you never really loved writing code. And by the way, you could still write code if you want. No one will pay you for it, but you can write all you want at home. Actually, what you got the most joy from is delivering that feature or that bug fix or whatever. And notice the person you were delivering that to, internal in a company or an external customer or whatever, never cared how you got there. What they cared about is did you do it right, was it on time, or was it even speedier? So they wanted speed and quality. Speed and quality. Nobody cares how you got there. And in fact, if you can get there without writing a line of code, even better. Like, to your customer, even better. And so people have to wake up and realize the joy is from the delivery of the output.

And I see developers now with essentially a screen of, you know, eight agents, and each one is kicking off some feature upgrade, some bug fix, some, you know, etc. And they’re just the robot overlord. They’re coordinating all of that. They’re getting it back. They’re doing some unit testing. They’re integrating it. Someone else probably will do full feature testing or full functional testing, etc. And then they’re shipping it. And I watch people now, including in my companies, someone says, “Boy, at 11 o’clock in the morning, we got a customer that really needs this feature, and I, you know, I don’t know how many weeks that’s gonna take.” And at one o’clock after lunch, you know, the guy comes out or the gal comes out and says, “You know, during lunch I ran this agent, and it did it for… And here it is. Here’s the feature. You know, it’s done. It’s not fully tested yet, but it’s done.” That brings, trust me, so much joy to everyone involved in that chain of process there, right?

Lastly, if this was two years ago, all we heard is coders are gonna all lose their jobs. We don’t need them anymore, okay? That turns out to not be the case. Ignoring some companies who’ve laid off and said it’s all about AI, and it isn’t, that’s a longer story. Let me tell you why it’s not the case. Everyone I know is so excited about going so much faster to get rid of and reduce their feature backlog and their bug backlog, often is in the thousands, right? And now they’re starting to deliver those faster. They don’t wanna slow down again by cutting their dev headcount. And these devs know their product, so no one is cutting headcount that matters. They really aren’t. And so this just turned into, wow, I can deliver all of this so much faster. That’s what it turned into, and that’s really important.

[00:20:39] Should Developers Fear the Rise of Agentic AI?

Henry Suryawirawan: Yeah, so I think this narrative of, you know, we don’t need software engineers anymore, those frontier model companies keep saying that over, you know, the past, I don’t know, one year or so. That kind of like creates a lot of impact like layoffs, people are worried, juniors cannot get jobs as well.

I’ve been hearing it a lot, right? So I think I understand about the moving to the higher language, especially now people just use prompt. But the agentic behavior is something that seems, you know, kind of like really potentially can replace developers because they can do this looping and keep on building things until it can even turn out into applications. So what do you think these agentic behaviors, should it be something that we worry about or should it be something that naturally…

Kevin Surace: No. Because the people running the agentic behavior are developers, right? You don’t want your business manager doing that. You don’t want someone in accounting doing that, right? You want your developers doing that because they’re responsible for the product and the quality of the product and how the product works and did it meet the specs and all that is on the developer’s back. So again, what I see is no one that I know of is letting developers go. it would be laughable. And I know some big companies did it, and they checked the box, and they said it was because of AI. No one’s really doing that. The– I will tell you, the only developers that are getting let go are developers that say, “I’m not using AI. It’s, I don’t wanna use it. I don’t agree with it. I think it’s wrong. I think…” They’re never gonna work again, right? I’m sorry, right? This technology’s here. That’s like saying, you know, “I don’t wanna code in Python.” And then the company goes, “But we only code in Python.” “Well, I refuse.” “Okay, well then you don’t work here anymore.” I– you know. So, I’m not worried about it. I’m not worried about… I’m not seeing it.

Now the junior developer thing is an issue because what’s happening is companies are not hiring as many. They’re hiring some, as many developers right out of, coders right out of college, right? As they go, I really don’t need this entry-level person because my staff here is now handling everything and delivering things so much faster. I don’t have this backlog to do." It’s not about, well, AI is better than the junior developers. Like I don’t have this backlog of things that keeps growing. The backlog’s finally shrinking, right? Finally catching up. So I don’t have a need for more people. That said, there’s an overriding macro situation, which is there are 18 million people leaving the workforce over the next five years, and there’s 13 million available to come in. So we are going to be at a workforce deficit, in the United States anyway, workforce deficit for the forever, right, for the foreseeable future. And so we need AI to increase our productivity or else we won’t have any company at all because there’ll be no one to work. So I think overall it’s gonna work out quite well.

Henry Suryawirawan: Right. So what can developers do to kind of like, yeah, I don’t know, improve themselves, live in the current AI era, especially for those juniors, how they can survive in this…

Kevin Surace: You have to be an absolute, absolute expert on using Claude and agents, period. And you got six, eight agents, and they’re all, you know, running coding tasks for you. And that’s your job. Your job is to coordinate these. Now there’s a lot you have to know, right, because we always think of, “Oh, I’m gonna go build an application.” Developers rarely build an application. What they’re building is an additional feature that has to bolt in or a bug fix or something else. And that has to be well-described. The APIs have to be well specified, you know, the range of data inputs. So all of that has to be done and done thoughtfully. And you actually have to be a good developer to do that. Otherwise, you can’t even read an API spec. You don’t know what an OpenAPI spec is, right? You don’t know what it is. But so you have to know what it is. You have to know how to use it in these specifications so that when the code is delivered that interfaces with that API, it actually works and it makes sense.

So that’s why I think it’s still… This is a technical field that requires technical people, that know the process of now DevOps probably more than Agile, but understand that process. I think we’re all moving from what was a two-week Agile process to more of a DevOps process, which is like one hour and very small things. I’m gonna just fix this one bug. We’re gonna put it into a build. That build might become a release. And then we do that again another hour or two from now and everybody contributes, right? So I think we’re gonna move more to DevOps, finally. I mean, we’ve been talking about DevOps for 20 years, 15 years, Gene Kim. But I think we’re actually moving there. And so this is all good, and it’s gonna be fast, and it’s gonna be furious, and people are gonna get great joy from being able to deliver product much faster and have happier customers of that product.

[00:25:25] How Does Appvance Use AI to Find Bugs Humans Miss?

Henry Suryawirawan: I think currently you also are still working in a company that builds AI for testing, right? So tell us what kind of revolutionary thing that you’re doing with testing.

Kevin Surace: Yeah, so, Appvance is the name of the company. Appvance has a, a test platform that is AI-based. It’s alway- it’s always been AI first. Obviously, there’s, you know, LLMs, transformers all over the thing today. But for, since 2017, that technology pretty much by itself, you have to be a really a developer or a really good QA person to set it up. But once you’ve set it up and you told it what your business requirements are, it goes off, writes all the tests, writes the scripts, literally write, codes the scripts, runs the scripts, and it will do thousands of them, many more than you could ever think of. And people say, why do I wanna test 12,000 user flows through this application as an integrated functional test? Why don’t I just do the 100 that matter? Because actually 12,000 matter, because your users are not going to go to just one state to check that particular outcome. They’re gonna go to whatever states they get to. Hundreds, thousands of states maybe, right? And so you wanna test that way. And that’s something called AI Script Generation Bug Hunter. A long title, but it finds bugs that nobody else finds.

And so we’ve been doing that since 2017, and it’s very, very good, and it’s gotten better over the years. It’s gotten easier to set up, right? It can also generate your test cases, just base level test cases, and turn those directly into scripts and run those and, you know. So, for years we’ve got customers on this that the vast majority of their test scripts were written by a machine. They were not written by the humans. They did not have a team of three hundred writing these. They had a robot overlord of one or two people.

So what’s interesting is you’d say, why doesn’t everyone use this? This is a breakthrough. You mean AI finds all my bugs?" You know, it’s kind of like the Mythos for every application. And the answer is yes, it does. But here’s what you, here’s what you have to know. A lot of people have ingrained culture, ingrained teams. They’ve got hundreds or thousands of people writing scripts. How do you tell them the machine does their job completely? How do you do that? ‘Cause in this case, it really does. You need a manager, but you probably don’t need people manual testing or any of that. You really don’t. And so that’s been the biggest challenge there. And the companies, huge companies, you know, Stellantis, the largest car company in the world, this is their standard platform, and Liberty Mutual, and many other companies. Yet other companies, they go, “Oh, wow, that… What do you mean you found 282 bugs in our production system that we never found?” “Well, they’re real. Here they are.” “Well, I think we should think about this more.” You know, it’s very scary. It’s, you know, this is one of those technologies that to the CIO, they love it, and the lower you get on the totem pole, the less they love it, the more it scares them, right?

And so, look, I think that will pass, because in the end, technology always wins, just always wins. And unlike coding where you need those developers, you know, we employed millions of people doing simple manual testing across the world or simple scripting, writing Selenium scripts and things like that. Yeah, that’s probably gone. You know, those tasks are not needed anymore, and haven’t been needed for almost ten years. But it takes, a long… Sometimes change takes a long time.

Henry Suryawirawan: Right. And does it do… what’s the approach? Is it white box testing, black box testing, or is it a gray box thing?

Kevin Surace: No, It is complete fun– it’s a large platform. It’s functional, performance, security, mobile, web, API, etc. But true functional testing. So, you know, true at the UX and at the API, but usually at the UX, mimicking what you expect users to do and based on your business requirements and your data-driven outcomes, right? So if a user does this and this, they better get the number forty-seven out the other side kind of thing, right? And so it will create thousands of those flows for you based on, kind of heuristics based on what it thinks users are going to do, and based on what your business requirements say that must work, right? And that’s what it does. And that is the ultimate test.

Look, all I want in testing is one thing: visibility to the bugs. There will be bugs. There will be things that don’t work the way I expect them to. I just want that visibility, and I can still decide to release it, right? But I need the visibility. And our testing QA tools never gave us very much visibility. They gave us, at best, about ten percent visibility to all bugs. And then your users would find and report bugs, and then you’d go round and they’re very expensive to fix once the user finds them. So you wanna find them early. So, you know, the idea of leveraging AI to find all your bugs, you know, at the integration functional testing level. So this is way beyond unit testing. You’ve done your unit test. Now you put it all together. It’s talking to twenty-two backend systems. What’s the situation there look like? And, you know, the idea of using AI for that is a really smart idea.

It’s not a great use of human skills. It’s something that AI can do, and in a few hours it will deliver, even on your production system, more bugs than you’ve ever found. But your users have found them, I can guarantee it. They didn’t report them, but they ran into them, and they started over, or they did whatever, right? So yeah. I, you know, Appvance has been breakthrough after breakthrough, lots of patents. It’s a great company, great team, and huge customers, so I can’t complain.

Henry Suryawirawan: Just to clarify, is this based on LLM model as well or is this something different?

Kevin Surace: Ah, some are– Yeah, some is LLM and some is traditional AI and ML. It’s kind of a mix of both for a lot of reasons. Some things the LLM or transformer is really good at or frontier model, some it isn’t. But it’s a mix of all of that and– but frontier models are used where they are appropriate to use them for sure. And there– And more and more of that is replacing some of the older ML as the frontier models get better at very specific tasks which they might not have been good at just a year ago.

Henry Suryawirawan: So yeah, hopefully people can also check it out. So sounds really cool, right? Being able to find bugs, you know, independently, automatically, right? And yeah, so hopefully, it- the software gets more quality. So let’s maybe move on the next, conversation about your book, right?

Kevin Surace: Sure.

[00:32:18] Why Did Kevin Write the Book Joy-Success Cycle?

Henry Suryawirawan: You’ve been all doing AI, you know, more technical stuff, and you finally wrote a book not about technology. It’s called Joy-Success Cycle. So tell us what’s the background behind this book actually?

Kevin Surace: Yeah, for tho- for those actually watching, they can see the Joy-Success Cycle. Look… People have asked me for a long time, “Why do you have such high dopamine? Why are you always so joyful?” And so I began writing that down and writing down a method to be like that. And I’ll tell you, the… So the core of the book says that joy doesn’t come after success, it comes before. And if you have joy in everything you do, you’re more likely to be successful. Joy in everything you do will lead to more success. This is a very critical breakthrough in understanding. And there’s a whole chapter on the science that proves this out as well. So the Joy-Success Cycle lays out a method that allows you to look at every single task you do every single day and make it a joyful task, even if it’s firing someone. How do I bring joy to this moment?

And it turns out you can. You– and we tell you how to do that. And it looks at, you know, human, natural human behavior. Natural human behavior is humans tend to complain a lot, both internally and externally. In fact, we complain about everything in life. We complain the moment we get up, all the way to when we go to bed, and the average person in the United States complains internally and externally about 100 times a day. 100. And every time you complain, you take yourself further away from success because you have to dig yourself out of this hole of complaints, basically, which we call the positive quotient. It goes to zero, and then you have to dig yourself out and dig yourself on the way back. So one of the things we teach is the one-complaint-a-day rule.

And so you, tomorrow, everybody on this show that’s listening or watching, you will count up the number of complaints you have, and you’re gonna find it’s 60 or 100 or 110 or whatever. It’s gonna shock you, whatever the number is. You have to keep honest track. And these are internal complaints, too. And then the next day, you start to work towards the one-complaint-a-day rule, where you can only have one. And I can guarantee you’re gonna burn that one up first thing in the morning. You’re gonna get out of bed and say, “Oh, my knees hurt,” or, “The weather sucks,” or something. And then, you know, you’re gonna hear the buzzer in your head going, “Eh! You’ve used up your one complaint for the entire day. You have no more.” So it’s a way of gamifying this and getting your brain to start thinking, “I gotta get out of complaint mode. That is never gonna help me.”

By the way, no one wants to hear me complain. No one. And it turns out very quickly you don’t wanna hear yourself complain anymore. You think it’s a total waste of energy, and it is. And so then you start working towards, I’ve gotta find joy in this moment. I’ve gotta– it’s raining out. I was gonna go on a bike ride, but that’s okay. Instead, I’m going to get this other task done that I wasn’t going to do for a while, and isn’t that great? That’s going to bring me joy. So you need to find the joy moment in everything rather than, “Oh, this is awful.” This is actually a positive. I can turn it into a positive. And it’s not being stupid about it. It’s like, it turns out that’s what I do. I mean, I had to write it all down and say, what do I do? Why is it that I can see all of these pain points out there and things to work on and ways to solve them? Why is it that I can do that, right? And it’s because I’ve got an open mind, and I’ve got an open mind because I’m not complaining all the time. My mind is open and ready to, you know, ready to go solve the world’s problems every minute of the day. That is a– that’s a great place to be, and that’s where I want everyone to be. So the people who’ve… I’ve been giving, you know, I do about 40 keynotes a year, and so many of my keynotes have been the Joy-Success Cycle. And I have consistently gotten calls weeks later that it changed entire teams, it changed the work environment, it changed people. It, you know… And so, it was important– It’s an important book to publish.

Lastly, the timing is right. Because the one thing I hear across the board, you know, something like fifty percent of the people in the US anyway, believe that AI is bad, it’s dangerous, and they don’t like AI data centers, right? Well, let me start out with this. They’re wrong, right? And AI is not going away. So how do you find the joy? They say, it took all the joy out of my life. Okay, stop. AI didn’t take the joy out of your life. You misconstrued what your sense of purpose was, and you misconstrued what was bringing you joy. You thought that was it because that’s what you were doing. But now we’ve got to look at it in a new era where AI is going to take away a lot of the joyless tasks. And that’s what you have to look at.

When you really step back, really step back, fussing around for a day to fix three lines of code that you can’t quite get the logic right on, we’ve all done this, any of you coders, you know. And you really, the whole day goes by and you go, “I got nothing done. I can’t get this little teeny, you know, set of logic to work.” It’s a, it’s an if-then else else else else or something. You know, it’s one of these things, and the logic isn’t working, and you, your mind isn’t figuring it. You no longer spend time doing that. That is a waste. There is a machine that does that. And we should not spend our time doing anything that we don’t add maximum value to anymore. You add no value to fixing that logic. A machine can fix that logic in one minute, literally a minute. As long as you can describe it, it will fix it. And so this is fascinating, right? So I can guarantee you you’re gonna have more joy because of that, not less joy. And that’s what we want. And so this Joy-Success Cycle hits at the right time and allows people to find their sense of purpose and where they can get joy. Even though the work they were doing is being taken away from them, they’re doing more important work now, work that they really add value to, and that is very exciting.

[00:38:20] How Can We Reclaim Positive Emotions Amid Global Crises and AI Anxiety?

Henry Suryawirawan: Yeah, so I think you said it, I think this is kind of the right time, because I think it happened if I- from my experience at least, right? It happened since the pandemic, right? Where when people started to feel more anxiety, you know, more sadness, right? Feeling kind of like depressed and then so many layoffs, then political situation, war and all that. Now AI coming, right? So obviously we are in kind of like, I don’t know, like doom and gloom kind of a thing, and the news doesn’t help as well. So I think maybe from your perspective, right? Because it seems like our positive emotion is kind of like eroding day by day, right? So how can we actually bring back our positive emotion regardless of what is happening in the world?

Kevin Surace: Right. And I think The Joy-Success Cycle lays out a, you know, lays out a process to do that. And it’s only 200 pages, so it’s not a big read. It’s an easy read. It’s available on Amazon and Barnes & Noble. You can order it today. It comes out September 1st, so you can pre-order it. You know, there’s a lot of pieces to this process. For example, we have a whole chapter on the joy killers and things that take away joy from your life. By the way, this could be a family member that you don’t want in your life, you didn’t ask to be in your life. Could be people at work. It could be work that you’re doing. It could be a variety of things and how you either have to turn– you either have to find joy in them or you have to get them out of your life, right?

There are things in all of our lives that were never gonna bring you joy, and I’ll give you an example. You’re at the office, if you work in an office, you’re at the office and every time you, you know, go to fill your thing with water, you know, Betty’s there, and Betty’s just complaining about every, “Oh, I hate the management. I hate this person. I hate that. I hate this.” You know, buy Betty a copy of the book and bless her out of your life. You don’t need to see Betty anymore. She’s not gonna help you succeed at all. You know, all of this kind of talk of, oh, let’s just talk about how bad management is. Really? Is that gonna change it somehow? No. You have two choices: to never participate in that talk anymore or– and just do your job and do a great job and get joy from it, or leave and get a job somewhere else where maybe you like the management better. You already have two choices. But the third choice of let me just complain about them doesn’t allow you to attain your highest level of success ever. It brings you down. It brings them down. It brings everyone around you down. It pokes holes in the boat when you’re all trying to cross the river at the same time. It’s just bad.

And so that doesn’t say that all management is good. It certainly isn’t. It just says you complaining about it isn’t the way to deal with it, right? The way to deal with it is to leave or to ignore it and do your job. I mean, tho- that’s it. That’s all there is. You know, so there’s a… I’m picking on that one, but there are a hundred examples of these kinds of things, right, where this is the stuff that happens and it just takes you down. And once you’re spiraling downward, you can’t even think. You look at a blank page. You can’t do your job. You waste all this time. You’re not moving towards success. You’re not looking at the next pain point out there and going, “Huh, I wonder if I can build a virtual assistant. I wonder if I can have AI find all the bugs in my software. I wonder if I can retrofit the Empire State Building with energy-efficient window.” Like I’m thinking of those things because I’m not dwelling down in the gutter. I don’t need to be down there. Let someone else be down there, right? And so, you know, joy breeds success, which gives you more joy, which gives you more success. You need to have joy every minute in every task in everything you do. Forget Betty at the water cooler, and my apologies to someone named Betty. I am not– I just grabbed the name out of the air. It’s not you.

Henry Suryawirawan: So, another thing that I think from my experience, is like the source of joy killer is actually news and social media, right? So if you’re always following the news.

Kevin Surace: Yeah, doom scrolling. Don’t doom scroll. What we deal with that a little bit and, actually we deal with it quite well is you’re welcome to hear the news. I’m not telling you to never listen to the news and never… However, you have to stop worrying about those things which you can’t impact. Spend no energy on it, right? So today you open the paper and you go, “Oh, there’s a war and people are getting bombed, and people are getting…” Unless you’re going to go there and solve it, or you’re going to run for president or I don’t know, right? You actually have no impact on that. You can note it. You’re educated on it. You wanna be educated on world politics, world– that’s great.

But it– you can’t worry about it. And it’s the worrying about it that puts people in bed in a depressed state. I have met more people say, “Oh, because of this, I can’t even get out of bed.” I said, that, that’s going on, you know, twelve thousand miles away, and you can’t have any impact on it. “But I just can’t get out of bed.” Okay. So it’s having an impact on you where you’re no longer going to be successful today. And if that’s what you choose to do, I, you know, that is your life choice. It’s not the choice I choose to make. I wanna be educated on it. I can’t fix it. I don’t have the power to fix it. I don’t have the power to start wars or end wars. But I wanna be educated on it, but I can’t get depressed about it because… So stop worrying about the things you can’t fix. Do not spend any energy on the things you can’t fix. And that doesn’t have to be just a war. It could be something at work. It could be something in your family. It could be some religious thing. It could be a tree fell that you loved so much. “Oh my God, it’s just– it’s ruined my life ‘cause I love that tree.” It ruined your… It’s a tree. They all fall eventually, right? I’m– I don’t mean to be mean about it, but, like, you can’t have any emotion over that. That isn’t the place to sort of waste your time if you wanna be the most successful you can be. ‘Cause every minute you spend crying about the tree is a minute that’s not being– that not moving you towards the, your maximum success.

By the way, your maximum success could be money, obviously, could be career, could be family, could be religion, could be sports. I don’t know what it is, right? So whatever, however you define success in your life. Lots of people define it as a certain monetary freedom. I get that, and then that’s the most common, right? I wanna get to a point where I, you know, great, where I can retire early. I don’t have to work. I, you know, whatever. Good. You define it the way you wanna define it.

Every minute you spend doing something negative is a minute that doesn’t move you towards that, and you will never get that time back. I spent three days just worrying about a war. That’s three days you can never get back, and you didn’t impact the war. I spent three days protesting against this data center. Oh, okay. Well, the data center will get built somewhere. You won’t have had an impact. It might not get built in your town, but it’s gonna get built somewhere. I guarantee it. And that’s three days you won’t get back. Like you can’t move towards your success.

And, you know, everybody’s got their own drive. Maybe their sense of purpose is to protest, in which case, all right, I guess you should go do that, right? But, you know, the book just tries to say if you wanna be the most successful, you have to push a lot of that stuff out of your life, ‘cause you only get so many hours a day. And a lot of us spend those hours complaining, you know, bitching, moaning, arguing, all kinds of negative stuff. And then weeks go by and you go, “I didn’t get to accomplish a thing.” Of course you didn’t. I could’ve told you that. You can’t accomplish anything. You’re down in the gutter. You know, don’t do it.

Anyway, obviously, 200 pages talks about this in great detail and gives a great method. People have bought it for their teams. We had draft versions that I used with teams. It’s game-changing for teams. We’ve watched sales teams, you know, increase their productivity almost overnight by following this method. So it is coming at the right time where AI and other things have really impacted people’s psyche. And we’re gonna pull you out of that and move you forward and I hope make you rich with success, whatever that means.

Henry Suryawirawan: Yeah. I think it’s a great advice, right, to focus on really what we can control, right? Obviously, if we cannot control, we don’t care so much about it. I think if we dwell on it, I think we waste so much time. Yeah.

Kevin Surace: Yep.

[00:46:44] How Do Purpose and Curiosity Work Together to Guide Your Life?

Henry Suryawirawan: And I like the, I think I’d like to ask you the next question. You mentioned a few times about purpose. And there’s this, you know, like one line in your book that I really like, like purpose as the foundation and curiosity as your stepping stone, right? So tell us about this concept because I think some people may not even know what’s their purpose. They’ll just live in the motion, right?

Kevin Surace: Curiosity is your friend, right? I think, when we’re curious, we learn. And when we learn, we find pain points we can solve. And when we learn more, we try to solve them. You know, the most successful people, I– you know, Elon Musk, you can like him or dislike him, but he’s a trillionaire. So give or take, maybe a little less now. But the point is he’s curious all the time. He’s curious about, “Huh, I wonder if I can make rockets way, way, way cheaper.” Nobody ever bothered to really think about that. They just got the government contract and built it to the contract. And if the price went up, there was more margin, and then, you know, there’s more money for everybody. That was good, more profit. So I think, you know, someone rethinking these fields is fantastic. And Elon, if nothing else, is curious. You know, can I build a car out of existing batteries where I don’t have to make brand-new batteries? Can I build rockets cheaply? Can I provide internet by putting thousands of satellites up? Nobody’s ever done that before. Is it even possible? Well, if you drive the launch cost down, it’s possible. So staying curious is what keeps your mind open and allows you to learn your whole life.

So many people, they leave school, and they go, well, I’m done learning now. Well that sucks. What are you gonna do? I mean, you know, I love learning every day. I read voraciously, and I– you know, really information in our field, right? I need to know what’s going on and who’s doing it. It’s hard to keep up with everything going on. But stay curious on everything and, and you will continue to learn throughout your life.

Henry Suryawirawan: Yeah. So definitely curiosity, follow your curiosity, right? Even if you cannot find your purpose now, I think maybe the curiosity will lead you to there, right?

Kevin Surace: That’s right.

[00:48:49] How Can a Simple To-Do List Become a Powerful Source of Joy?

Henry Suryawirawan: Yeah. So I think another thing that is quite kind of like fun in your book, one of the chapter is called The Joy of To-Do Lists. I think many people may not feel joy when they see their to-do list. So us why this to-do list is powerful for your joy.

Kevin Surace: Yeah, so I do to-do lists every day. I do them by hand. And to-do lists are great for a lot of reasons. One, it tells you what you gotta do today or the next day or whenever you’ve done it, if you’ve done it the night before, you did it in the morning. The other thing it does is it gives you small wins during the day. You get to literally cross something off or check it off when it’s done. You go, “So I have to prepare for this podcast. Check.” I go, “Win!” Small wins are great. You need small wins all during the day. And by the way, every time you check something off the list, it’s a little dopamine hit, and it gives you more energy to keep going. And when you don’t make a list, you’re just wandering through the day just, you know, dealing with what comes, and that’s just not as satisfying.

So the other thing is writing a list with a pen is a great thing, and I write lists with pens. And I highly recommend doing that, pen or pencil. And it’s much better than keeping lists on a computer, which I tend to never get to and never do. So write them every day. Do your to-do list. I don’t get through my to-do list every day. Some things on that to-do list are a month kind of a thing. They’re gonna take a lot longer. That’s okay. But I know it’s there. I see it every day. I work out a little bit to try to make progress.

[00:50:20] How Did the Joy-Success Method Transform a Sales Team’s Attitude?

Henry Suryawirawan: Yeah. So maybe you said that you have been in kind of like this joy, I don’t know, like journey for many years. Maybe after writing your book or after spreading this in your keynotes, are there some inspiring stories that you can share with us, you know, about, you know, some people who have changed, used your methodology and really succeed?

Kevin Surace: Yeah, you know, there was a– this great sales reorganization that happened in a very big company that I came in and spoke to and spoke The Joy-Success Cycle. It was my keynote on that. They specifically asked me to come, because the mess they had was they had reorganized and everybody was mad. The salespeople didn’t like the new groups they were in. They didn’t like anything about anything. And all they were doing was moaning every single day rather than selling. And, you know, selling attitude is very important. So if your attitude isn’t good, you don’t sell anything. And sure enough, after The Joy-Success Cycle, and I customized some things in my– I customize my keynotes all the time.

So for them, I said, “Let’s say there was a reorganization,” which I know there was, and I know it’s very easy to be negative on all of this. “Oh, I liked my other team. I worked… Da-da-da.” Okay, let’s look at the positives. First of all, you knew everything there was to know about your other team members. There was nothing new to learn. Here’s a whole new group of twenty-eight people you don’t know anything about that you can learn from. There’s twenty-eight people that you can go and have a drink with or a coffee with or a tea with or whatever it is, or a lunch with, right? This is a whole new learning opportunity for you where you can open your mind, be curious about them and their experiences, and probably learn a whole new set of experiences, whole new set of skills, right?

And when you look at it that way, all of a sudden this is, what a great opportunity, rather than, “I hate this, I wanna go back to my old group,” which is what everybody said. “I hate it, I wanna go back to my old group.” And the second thing is, when you come in with that kind of mindset, then what’s great about it is that you go out to sell and you’ve got a great selling attitude ‘Cause you’re excited to be with this new group. You still love your old group, but you’re excited to be with the new group. So that’s an example of people who called me a few weeks later and said, you know, not everybody picked it up, but those who did are gonna be here a long time and they’re excited about it, and they stopped all the water cooler talk and it changed their entire attitude.

Henry Suryawirawan: Right. So Kevin, I think it’s been a great things. Any things that you think, can be also shared by you, like before we wrap up to the last questions that I have?

Kevin Surace: No, I think we covered a lot today.

[00:52:52] 3 Tech Lead Wisdom

Henry Suryawirawan: All right, so in that case, I’ll ask you this one last question that I always ask in my podcast. It’s called the three technical leadership wisdom. Just think of it like advice you wanna give to the listeners to wrap up.

Kevin Surace: Well, the advice, we probably covered all of it. One, use AI all the time, period, full stop, done. That’s at the leadership level, it’s at the coding level, and it’s everywhere else. If you’re not using AI five times an hour, you are behind your competition. It’s really important. And, you know, listen to that, right? It’s really, critical.

You know, the second thing is that AI isn’t taking any joy away. You thought it was, but trust me, it isn’t. Buy the book. It’ll take you through a method that I guarantee you, you and your workers are gonna be far more joyful about.

And lastly, this is the best time to be alive in technology ever. We are able to achieve and write more and produce more incredible output than we’ve ever been able to do in our lives. It’s unbelievable. And so this isn’t the worst time to be in tech. It’s the best time to be in tech. And it’s always how you look at it. And I know some people are gonna look at this and go, “Oh, you know, it’s change. I don’t like change. I don’t…” Okay, this is the best time to ever be in this field. You could not have come at a better time. And so how lucky you are.

Henry Suryawirawan: Wow, I think it’s quite inspiring, right? So I think the best time ever in the tech, if you always see it from the positive side, I think you can really feel that this is the really the best time ever in the technology world, right? Where things are kind of like being invented all the time, right? Every day. So Kevin, if people love this conversation, they wanna reach out to you, find more about your resources, your books, is there a place they can find you?

Kevin Surace: Yeah, my website is kevinsurace.com, and the book website is joysuccesscycle.com.

Henry Suryawirawan: Right. All right. Thank you so much for your time today. I hope people learn a thing or two about finding their joy, right? And hopefully that leads them to their success. So thanks again for the time today.

Kevin Surace: Thanks for having me.

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