#240 - AI as Your Thought Partner: Break Boundaries & Do What You Never Could Before - Greg Shove

[00:01:27] Introduction

Henry Suryawirawan: Hello, guys. Welcome back to another new episode of the Tech Lead Journal podcast. Today, I have with me Greg Shove. He’s the CEO of Section, a company that is trying to train people to get up to speed with AI and implement that in their companies, enterprise or startups. So Greg also is a multi-time founders, co-founders. You know, he has successfully led seven companies as a CEO. I think mostly or not all are in AI, I’m not sure. Like maybe later Greg can clarify that. So welcome to the show, Greg. We’re really looking forward to talk to you today about, all about AI and how we can make AI rollout successful.

Greg Shove: Thanks, Henry. Yeah, those seven startups, now that was seven startups over 30 years, so there weren’t all AI startups. Otherwise, I would’ve been really busy the last two years. Now, I’m currently CEO of one AI company and chairman, founder and chairman of another AI lab, a development lab. And those other startups were all tech, uh, startups, uh, starting 30 years ago in Toronto, uh, where my first entrepreneurial venture in Canada.

[00:02:44] Career Turning Points

Henry Suryawirawan: Greg, I always love to invite my guests to maybe share a little bit more about you by telling us any career highlights or turning points that you think we all can learn from that.

Greg Shove: Oh, yes. So many. When you’re as old as I am, you know, you’ve got a few pivotal moments in a career. I’d say one was when I was in Toronto and I was talking to a mentor and about how I wanted to be… I was in tech already. I’d worked for a digital equipment corporation. Doesn’t exist anymore, and Sun Microsystems does not exist anymore. And I was, uh, thinking about a career as an entrepreneur. I didn’t wanna work for anybody else. And I was talking to this mentor and he said, listen, what are you doing in Toronto? He said there’s a grocery store in Palo Alto, California called Molly Stones. And when you go to Molly Stones on Saturday morning, do your grocery shopping, you’re gonna meet more people in tech than you’ll meet all year in Toronto. And I thought, oh, that’s actually pretty good advice. So I got lucky. I got into Stanford Business School in Palo Alto, obviously, and I stayed afterwards on a student work visa and eventually converted that, you know, into a H1B. And that, you know, that was a pivotal moment, meaning I put myself as close to the action as I could.

You know, other pivotal moments, really, the biggest ones where we learn our failures. And so I think that, you know, I’ve had at least a couple companies that I talk about, you know, not make it and probably more that I don’t talk about. And so yeah, listen, I think failure is a great teacher. And, uh, one of the things I love about Silicon Valley is that we don’t punish failure. We know that, you know, innovation, entrepreneurship, trying to build new products and services is really hard and it usually does not work. But we don’t, you know, we don’t blame people for that. We often want to back them again, right? We wanna try to help them a second time or fund them a second time and so on. So, for me, I’d say just the resilience, the pivotal moments are those failures and the resilience that you have to develop to survive, you know, those failures and take them in stride and not have them knock you too much off course.

I’d say the other is hiring great people. It’s, again, it sounds like a cliche, but it’s hard to hire people and it’s particularly technologists. But when I’ve hired great engineers, great developers, great product people, my businesses have always benefited disproportionately by the one hire. So really spending time and effort to make those one or two critical hires, especially if you’re building a new product, a technology product, you need amazing, you know, software engineer and you need an amazing product, kind of front-end guy, you know, guy or gal to help bring that product to life. And so when I really found that special person, I try to keep working with them. You know, again and again ‘cause I know how good they are and how transformative they are. So just being open to really having, uh, others are the reason you’re successful is how I think about it. And, you know, your success is really a representation of how well you hired and motivated and worked with other people who are likely more talented than you are.

[00:07:49] Cultivating Entrepreneurial Resilience

Henry Suryawirawan: Yeah, I like that last sentence you gave, right? Others, the reasons you are successful, right? So I think, definitely there’s a lot to learn about hiring great people. And I think you mentioned about failures. I wanna dig a little bit on this area, because I’m always amazed by someone, entrepreneurs who have done multiple, you know, companies, right? Not all are successful. Maybe some or not, like maybe all of, not all of them are like, kind of like failures, right? But like, one or two are big success. But I think in the points when you had that failures, I think that’s where your resilience, your determination, maybe some kind of your spirit as well, right? Because I think here in Asia, we are more risk averse, so we don’t like failures as much as possible. But I think from your point of view, having done all these, how do you cultivate that resilience? How do you actually motivate yourself to come back to it?

Greg Shove: Yeah, I think one thing you have to do, and I learned this the hard way, like I learned this later in life, you have to do a really good retro, right, retrospective on why you failed. Like really learn from your failures. ‘Cause when you really examine failure and understand what went wrong in the business, let’s say, or what went wrong in the product, what you’ll probably realize is it wasn’t all your fault. One of the reasons I think you can be resilient is you can realize that some of this was out of your control or some of this was circumstance. Some of this was timing. Some of this was, yeah, maybe you didn’t make the right decisions every time. You don’t need to make the right decisions every time. I think failure is so hard on us ‘cause we take it too personally. And I think that we tend to wanna move on from our failures very quickly. We want to sort of put failures in the past as fast as we can. That’s human nature. And I think that’s fine.

But I think you don’t want to miss a step. And the step is examine your failures. Like spend a few hours talk to the team, really, you know, talk to your partner, your founder, you know, your wife or husband, whatever, like really deconstruct and understand how did you get there, what, you know, what went wrong, what, you know, what did not go according to plan. And again, and when you do that, I think you realize, oh, I, you probably did a pretty good job, but it just wasn’t, you know, it wasn’t meant to be, right? The timing, again, the maybe the pricing of the product was off and that wasn’t, you know, that was it. Whatever it is, right? And again, I think this idea of resilience really comes from don’t take failure too personally and know that you probably did a pretty good job. So you’ll probably do a pretty good job the next time. You’ll likely do a better job the next time ‘cause you’ll have that much more experience, right? And maybe your timing will be better.

Listen, one of the reasons I pivoted my business, Section, to AI is that when I played with ChatGPT Plus on February the 1st 2023, really for a couple hours, I really sort of played with, uh, with AI, a generative AI chatbot, I just realized how amazing it was and how this was going to be a wave. And I’ve never made any money, Henry, unless one of my companies has been positioned in a wave. Like when you confine growth, you don’t have to execute flawlessly. You have to execute well enough. And then the growth, right, that’s outside of you. The growth that is happening, regardless of what you do, you, if you’re in that growth, you’re probably gonna be okay and you’re probably gonna find some success.

And so, you know, I’ve only ever made money, meaning I’ve only ever been able to sell my companies when I’ve been able to grow them. And the growing is because I’ve been positioned in something that is growing. So the first was e-commerce, the second was cloud, you know, and then mobile, and now AI. So when I really understood AI, personally, I realized, okay, this, you know, this is going to be obviously big. I’m not sure how big. I’m not sure you know, when, but it’s gonna, it, this feels really big. And that’s why I, as I said, that’s why I pivoted the company. And that’s worked out great for us, right? We’re growing now at a 100% a year. You know, and that’s just, that’s ‘cause we’re executing well enough. But the growth is there.

And the inverse of that, the opposite of that is if you’re in a small market or you’re in a market that is declining or is maturing, you really have to execute flawlessly. ‘Cause you’re fighting over, you know, a slice of pie that is shrinking. You’re fighting over a market that is not growing. And so it just makes it that much harder. You really have to execute perfectly to get growth when you’re in a market that’s not growing. So I try to avoid those markets, you know.

[00:12:29] Understanding the AI Wave: Scale and Transformation

Henry Suryawirawan: Right. The interesting point you mentioned about the timing, right, and the waves. So having gone through multiple waves, right? Like what you mentioned, e-commerce and internet, and then the mobile and then, um, now AI, right? How, how do you think AI wave is different than others or is it similar? Or how much potential do you think this wave is gonna be?

Greg Shove: Well, I think we’ll know in a couple years, first of all, meaning we will get, we’ll get a clear answer in a couple years. It looks huge, obviously, it’s also obviously overhyped. It looks huge because this is technology that I think is horizontal, meaning it crosses the whole organization. It crosses almost any knowledge worker job or role. That’s one reason.

Second reason is it’s highly democratizing in terms of AI allows us all to be software engineers or to be writers or to be creators or to be data analysts, right? It is a horizontal technology that moves up and moves down the org chart. It opens up access across the organization, if you will, allows people that are siloed to get out of a silo, right?

Think about a management consultant. Management consultant relies on a data analyst, typically. Well, now a data analyst can be a management consultant with GPT-5 deep research, right? And frankly, a management consultant can be more self-sufficient and do their own data analysis now using GPT-5. So, you know, it’s just this really powerful technology ‘cause it allows us to flex in so many different directions as individuals and as teams or and, or companies.

I think about it, Henry, this way. It’s one of the few technologies, maybe the only technology that allows us to jump capability boundaries. All of us have capability boundaries, right? We’re bound, we’re constrained by our capabilities. And that makes sense. We, you know, we can’t do everything well, so we’re a marketer, or we’re a software engineer, or we’re a product leader, right? We’re typically not a marketer and a product leader, right? And organizations, companies have the same boundaries. And that’s how we compete. We compete in our, within our boundaries, right? As an organization, as an enterprise.

AI breaks those boundaries. AI allows us individually and organization to jump boundaries. So it just, it seems to be where, whereas, you know, Slack, your communication software doesn’t really do that, right? Productivity software makes us more productive, but it doesn’t really allow us to jump capabilities and so on. Other enterprise software is very valuable. But this feels like a really transformative capability. And by the way, I don’t think it’s software. It’s not really software in a traditional sense.

And I think that one of the reasons that large organizations are struggling with AI and why AI is such a superpower to small organizations and small teams is because large organizations struggle with it. And one of the reasons they struggle with it, Henry, is they think this is like another software deployment. They buy AI. You know, an enterprise LLM, ChatGPT for enterprise, Microsoft Copilot Pro, you know, Google Gemini. They buy it like software and they deploy it like software, which means they turn it on, everybody gets access. Maybe they do a training or two. You know, they do, you know, a month of workshops or something. And then they expect like other software like an ERP or a CRM or a, you know, project management software. They expect everybody to use it.

But this is not software. This is like co-intelligence. This is like a cognitive service. It doesn’t behave like software ‘cause it’s not reliable, as you know. It hallucinates, you know, which is Silicon Valley jargon for AI makes shit up, right? So it, you know, it makes mistakes, it makes up stuff. It’s not reliable. It’s really powerful. But it’s also kind of stupid at the same time. And it scares employee, about their jobs. You know, there’s a lot of anxiety about AI when you think about particularly larger organizations. But you go talk to a startup CEO, you go talk to a software engineer on a small engineer, a software team, they can’t live without it, right? They can’t imagine, you know, working and living without AI, especially here in Silicon Valley or anywhere that’s a small team, because small teams don’t have enough resources and small teams are always behind on the roadmap. Small teams have already always have too many tickets, you know, to clear, whatever it is. And so they want the assist. You go to a big company, that’s not their world. Their world is about protecting their job and kind of doing things the same way they’ve always been done, which is why it’s tough for bigger companies to deploy AI. We really have to break down this into small teams and get small teams to be AI-enabled like a startup would. Like today you would not start a company and not think about, you know, you’re gonna turn on AWS, you’re gonna turn on email, turn on, you know, document sharing, and you’re gonna turn on AI, and you’re gonna start your company.

Henry Suryawirawan: I think there are a lot of great points that you mentioned just now. I like in particular, you mentioned about this capability boundaries that we can break through simply by using AI. And I like also the nature of AI, right? It’s like using natural language for you to actually interface with it. Unlike other software probably is more technical, slightly more clunky for some software, right? So I think this feels a little bit different.

[00:17:57] Pivoting to AI: Section’s Transformation Journey

Henry Suryawirawan: And your company as well, right? Section was not originally doing stuff on AI, right? If I’m not mistaken, you’re doing more like, you know, executive or education, you know, online kind of training, those kind of stuff. And then you pivoted to doing full AI. So tell us, you know, the pivot experience that you did, right? First of all like what was the rationale behind it? And secondly how do you make that pivot actually successful? This comes to the learnings that maybe other organizations can also do in terms of, you know, making them implementing AI successfully.

Greg Shove: Sure. Well, as we talked about, the pivot was inspired by my realization that this was the next wave, right? This is something that would provide growth. Also, you’re right. The original business of Section was management education, online management training. ‘Cause we feel, we felt and we still feel that management training, teaching people strategy, teaching people better management techniques and so on, they, those are accelerants. They help people’s career. They accelerate careers. Great, you know, business schools, right? MBAs, executive education from business schools. You know, those, partly it’s the credential, but partly it’s the actual knowledge, right? The upskilling that you get, they are career accelerants.

When I used AI for the first time, my realization was this is the new accelerant. That in the short term, meaning the next five years, knowing how to use AI would be a personal career or professional accelerant. And I realized, okay, management training is an accelerant, but this is the new accelerant and no one knows how to do it. So if I go early and fast, I can be, you know, a school that teaches AI basically and provide that acceleration, you know, to millions of others. Cause the world always, it always takes a while to adopt these technologies. It does not happen overnight. It’s happening very quickly with AI, I would admit, you know, a billion users by the end of this year for ChatGPT is kind of an amazing number. More than 10% of humanity. It is happening quickly, but still a lot of people need to be sort of supported, upskilled. And frankly, the anxie- their anxiety has to be lowered, uh, to use AI successfully. So that’s really the inspiration for the pivot.

The lesson about pivots, and I’ve done a lot of pivots. ‘Cause when you do seven startups, you know, you end up doing a lot of pivots. Too many, maybe. But, um, the only way to pivot is to be all in. The only way to pivot, in my opinion, as a startup, you can test, you can experiment into it. Meaning you need to develop the confidence and the evidence that your pivot is the right decision, right? It’s, it is the right direction for the company. But once you’ve made that decision, so you can be cautious to a point to get to the decision, once you get to the decision, you personally have to lead from the front and you can’t go back. You might keep, and we had to do this at Section, and I’ve had to do it in my previous companies, in my previous pivots. You might have to keep the old business ‘cause you need the revenue, right? And you might want those customers as well for the pivot. So you might keep what you have. So this is hard for teams to keep what they have and then to pivot. But the pivot, my point about the pivot is you’re committed. You’re not gonna go back. You’re gonna harvest or wind down the old business if you have one, right? And we did at Section. We had a very good management training business and we wound it down over the last two years. We let it atrophy, and then kind of closed it down. And then, but you’ve gotta be committed. So once I was all in AI, there was no choice. And the rest of the organization had to follow my lead, otherwise they couldn’t work at Section.

And I had skeptics for sure inside the organization. You always do with a pivot. You always do. And you know, that’s your job as a leader is to win them over or ask them to leave. You can’t afford to have one person really, you know, on the team that after, you know, a month or two or three months depends how big your company is, but you can’t carry too many doubters or skeptics, you know, along for the ride. It won’t work. Cause people are gonna be anxious. People are gonna be anxious. They’re gonna be scared about the pivot. You know, will it work? Is this a crazy idea for my CEO? ‘Cause he woke up or she woke up one morning, you know, with this crazy idea or is it real? Like is this a pivot that you know that we’re gonna do? And so yeah, commitment is everything to me for pivots.

Henry Suryawirawan: Yeah, personally, I’ve been through some pivots as well. So always an uncertain time, especially for, you know, employees, right, who were probably not consulted or discussed, uh, in so many of those, uh, meetings where you wanted to decide to pivot, right? So thanks for sharing that. To be all in, right? So once you decided you wanna commit to that, to be all in.

[00:22:57] AI as a Thought Partner

Henry Suryawirawan: So you mentioned about skeptics. I think even though many people are raving about AI, you know, how great it could be. But there are also some skeptics, right, uh, out there that people who think that, oh, AI can still hallucinate, can make wrong decision, you know, make catastrophic, uh, result as well. Uh, we’ve seen it sometimes in the news or over Twitter, social media. And you, yourself personally have gone through this realization that AI can be a thought partner for yourself. And in, I think in one of your quote you mentioned, AI is like your testosterone to the brain. I kind of like that term. So maybe to remove some doubts that people have sub, from these skeptics, right? So tell us why you think AI is such a good thing as a thought partner and something that everyone should, you know, try to embed in their daily life.

Greg Shove: Yeah. Well first of all, I wanna answer the kind of the first part of your question. I don’t think we should necessarily be skeptical about AI, but we should be sort of clear-eyed. We should not drink all the Kool-Aid. You know, there is a lot of hype coming from Silicon Valley. You know, this idea of we’re gonna build AGI or SSI, super intelligence, right? And really there, that’s a story that they’re using to raise capital. Huge amounts of capital, right? OpenAI has just announced that they will lose over a hundred billion dollars by 2030. It’s a just unheard of amounts of capital and losses for a single company, single private company.

So, but listen, AI will have a lot of unintended consequences. AI will, uh, continue to hallucinate for at least for another year or two, as far as we know, maybe forever. AI will not handle every personal interaction successfully. So we will see more lawsuits related to, you know, self-harm and suicide, uh, when people using AI as a therapist and so on and so on and so on. We’ll see lawsuits probably from parents about how dumb their kids are because, you know, they went to, they didn’t go to school, they just used AI. We’ll see all kinds of crazy, crazy sort of, uh, lawsuits and consequences of AI.

So I think we need to be, as leaders, you know, smart about it. We should be optimistic, but we should also be pragmatic. And we shouldn’t just think it’s all gonna be great. Listen, energy prices are going up in certain parts of the United States, because of the demand that data centers are pulling from the energy grid. So there’s a real consequences here to our adoption of AI. So I think we should be pragmatic and we should be balanced in our view of AI.

What I do think is AI has superpowers. And when properly used, when we drive AI, when we steer AI, it can be really valuable. And you’re right. One of my favorite use cases is AI as a thought partner. I think it’s irresponsible now for any executive who works for me, any executive, if you’re making a medium to high stakes decision, you know, about, uh, hiring someone or a product roadmap or a pivot or a board meeting, anything, any medium to high stakes decision. And at home, parenting question or a health question. I think it’s irresponsible not to talk to AI. I’m not saying do what AI says. I’m not saying that. I’m saying that we all as humans have biases. We all have blind spots. We all have a set of experience that informs our decisions and our judgment. But the, those set of experiences are quite narrow when you think about all of human experience. We have decision frameworks that we rely on just because they’re the ones that work for us in the past. But we don’t use all the decision frameworks available to us. We use the ones that we know how to use, right?

So AI has none of that, meaning AI does not have blind spots. AI if properly steered or managed, AI can use any decision framework. AI can cross boundaries, as I already talked about, capability boundaries. AI crosses countries. AI crosses languages and cultures. AI crosses industries. AI crosses functions. AI can be a personal coach and a business coach at the same time, and so on. So I think that for any decision that has high stakes and that could be, again, as I said, what to do with your kid who has these symptoms, you know, and a temperature of 102 degrees, uh, as a parent or you know, how to prepare for a board meeting as an entrepreneur. I think you should be spending 10, 5, 10, 15, 20, 30 minutes talking to AI about it and uploading the business plan to AI or the board deck or the photo of the, of your kid in terms of, you know, the symptoms or whatever it is, right? The photo of the, of the house you, I don’t know, you might wanna buy.

Whatever it is, talk to AI about. AI is a very effective thought partner. Again, you’re not gonna do what AI tells you, but my guess is you’ll be able to improve or optimize many decisions. And at the very least, you’ll be better prepared to have a conversation with someone else about that decision. So that might be with a doctor, that might be with a board member, that might be with a partner or a co-founder if you’re having a disagreement or a difficult decision about the product roadmap or about, you know, a customer. You know, whatever it is.

So yeah, I think it’s the universal use case. And by the way, the data shows this. This, you know, this idea of AI as a therapist, AI as a coach or companion. Those are emerging as the, some of the top use cases for AI. I think it’s AI superpower, actually, Henry. I think it’s the surprise sort of hit, if you will, for AI. This use as a personal coach or a therapist or a thought partner. Uh, it’s someone to talk to who’s pretty smart and will listen to us. ‘Cause AIs are trained right to listen to us. AIs are trained probably to be too flattering. And that’s why they hallucinate, ‘cause they’re trained to give us an answer, kind of no matter what. So we have to learn to use AI the right way.

And we have to know that AI is really sort of playing us. AI wants to be liked by us. So we have to be aware of that. You know, I’m tired of how many times AI has told me how smart I am. You know, I’m not that smart, but AI just keeps telling me I am, right? So, you know, again, that’s why we have to be smart about this.

And we have to have a balanced perspective on it when, you know, we know that AI behaves a certain way based on how it is built, how it’s designed. But again, very useful. It’s a use case that I’m not sure people want to pay that much for. I don’t think companies want to pay for AI for us to use it as a thought partner, right? I think companies want to pay for AI to make us more productive, so we write more lines of code, you know. Or we, uh, create more marketing briefs or whatever it is, right?

But yeah, I think it’s a great use case and I think everyone should be using AI, as I said, as a thought party. You should be talking to AI. That’s a great way to interact with AI. When you think about AI as a thought partner. You know, do it while you’re commuting or you’re in your car or when you’ve got some downtime, right? Just get your phone out and use, um, you know, one of the AI apps on your phone. Advanced Voice Mode in GPT, it’s just fantastic.

Henry Suryawirawan: Yeah, so I think the key word here is a thought partner, right? So you’re kind of like not outsourcing fully, you know, the answer, the decision and in the end, you kind of like have to be the one accountable making the decision. And I personally also have, you know, used AI in so numerous scenarios, uh, for learning, explore ideas and all that. I think it’s great to kind of like open up your perspectives. And sometimes it could be just curiosity on a certain topics, right? And from there maybe you can learn something new and, you know, improve the ideas that you have.

[00:30:49] Practical Tips for Leaders Using AI Daily

Henry Suryawirawan: And you mentioned in your companies, um, you said that it will be irresponsible for leaders or the executives not to use AI. I’m pretty sure in most of the companies, apart from using maybe just a simple ChatGPT and all that, maybe many leaders are still not, how should I say, natural in using AI in their day-to-day work. Maybe what are some of your typical advice or scenarios that leaders can do now in order to use AI as a thought partner more and improve their decision making or improve their, you know, performance as a leader?

Greg Shove: Yeah, that’s a… Sure. I think it’s easy to get started. First of all, get the app. Like I’m surprised how many executives don’t have a premium account, first of all. So they’re using, you know, free AI is pretty good, right? GPT-5 freemium is or Claude or… they’re all pretty good. They’re free products, but pay the extra 20 bucks. It’s only 20 bucks a month. Get the additional features, you know. Get the mobile app, get it on your phone. In fact, what I did recently actually, Henry, is I put the GPT-5 widget on my iPhone. So now it’s occupying a good amount of my home screen, of my iPhone is the GPT widget, which is just more prominent, you know, on my home screen. I just use GPT more. So that’s the first thing.

Second thing is move away from Google. I don’t care which AI you use. You can use Claude, you can use Gemini. But just get out of the habit of using Google all the time for certain searches. What I call functional search, of course, use Google. You know, when is this restaurant open? Or, you know, the, those kinds of searches, very functional searches. Google’s probably still the fastest and best source of truth. But for a knowledge search, stop using Google and begin to use AI. And you’ll notice the differences, good and bad. It’s not always good. I’m not saying it’s gonna be better all the time, but again, change some habits, right?

Third thing, very lo-fi, very cheap. And this only costs like, you know, a few cents. Get a post-it note, write on the post-it note, “Ask AI”. Stick it on your monitor. Stick it on your monitor. That’s what I did for two years. For two years, I had, you know, none of us likely in this audience, your audience are AI native. AI native kids are in school right now, right? They’re in middle school. Maybe they’re in high school. Some the kids graduating from college right now aren’t AI native. They learned AI at school so they could cheat and get their homework done faster and submit more assignments. But, you know, it’s really the kids in middle school today that are, will be the first AI native generation. The rest of us grew up in a world dominated by browsers and dominated by Google and search, right? And this idea of a search results page. And so, uh, we have to really remind ourselves to use AI. So I used a post-it note for two years.

In January, Henry, I bought a monitor and I call it my AI monitor. So it’s on my desk in my workspace. It’s right next to my main monitor. It’s on the vertical horizon, so it’s vertically oriented. And I have one browser open with three tabs. And every morning I turn that monitor on and I’ve got Claude, uh, Anthropic Claude, Perplexity and ChatGPT. That’s all I have in that, on that monitor. And so I can see it all the time. I, you know, it’s right, just to the right of my main monitor, it’s in my line of sight. And every morning I can see Claude and Claude says, good morning captain. ‘Cause Captain is what I told AI to call me, right? Because I’m the captain, they’re the co-pilot, right? But it’s, it only costs a hundred dollars for that monitor. And it’s just a, it’s kind of a hack. It’s a cognitive hack, but it works. It reminds me to use AI. And when I have good work with AI, I cut and paste it from AI into my main workspace, which is my documents, my decks, you know, my whatever it is, right, uh, that I’m working on. So I like that.

Eventually, we, I won’t, we won’t need to do this. Eventually AIs will be watching our, you know, we’ll be sharing our screens real time with AI soon. And AIs will just be watching as we work and offering to help us. That is soon in the next year or two. But uh, for now, this is, I think, a good hack. And you can see where AI is going ‘cause as you know, AI now has better memory, particularly OpenAI, now Anthropic enabled memory, uh, recently for the Claude, you know, chat bot. And memory, I don’t see a lot of value yet, but we’re gonna see a lot of value from capabilities like AI memory. ‘Cause they’ll really be able to, you know, hold conversations for longer and remember things that they’ve, that we’ve talked to AI about and so you can see where we’re going here. Really, really powerful, sort of always on agent or, you know, co-intelligence.

But to get started, yeah, just get started and begin to move your behavior away from Google to AI. And that could be the Gemini, which is obviously Google’s AI. It doesn’t matter, I don’t think. All these AIs are, I think, quite similar in capability at this point. If you’re a software engineer, obviously, and for your audience, at least some of them, I’m sure they’re already using coding co-pilots and maybe multiple. Eventually I expect there’ll be one or two winners, you know, uh, in terms of coding and software engineering. I find it interesting that the AI companies, and for good reason ‘cause they see how many conversations are related to software, you know, software coding and writing code. So they keep improving that part of the product. But software engineers are a small part of the knowledge economy. When you look at the knowledge economy, it’s, you know, huge and a lot of other roles. You know, marketers and salespeople and finance and HR. AI is not as good yet for those functions, right? It’s still ‘cause it hallucinates and it’s not as easy to work with. But, you know, these are AI companies. They’re full of software engineers and so they keep releasing better features for software engineers, right? OpenAI just released, uh, GPT-5 codex this week, right?

Or retire and go play golf. If you wanna keep your head in the sand about this AI thing, you could try. If you’re 45, I don’t think it’s gonna work. If you’re 60, you know. What’s the, I don’t want the retirement. What’s the…. you’re in Singapore?

Henry Suryawirawan: Yes.

Greg Shove: What’s the typical retirement age in Singapore?

Henry Suryawirawan: 60, 62.

Greg Shove: 62. Yeah. So yeah, maybe if you’re 60, maybe if you’re 57 or something, keep your head in the sand, you know, just stay outta trouble and you can get to retirement and then you can focus on the golf game. I’m 63, but I wanted to keep working. I intend to work for at least five more years and I live and work in Silicon Valley. It’s a very ageist place. You know, if you’re not 28 years old and wearing a hoodie, you’re an idiot.

So, you know, when I used a GPT for the first time, I very selfishly thought for me this was gonna be great. I thought it would be great for the company and that’s why we pivoted. But my first reaction was, hey, this is great for me ‘cause I can maintain my cognitive edge, I can really keep working and at a high level. Because, you know, as we age, you know, our cognitive abilities do decline and that decline accelerates after the age of 50. Cause I asked GPT and that’s what it told me. So, uh, you know, I thought about it as this is a way I’m gonna stay cognitively sharp.

Now you already kind of referenced this, there’s a real risk that the opposite happens. If we over rely on AI, if we cognitively offload too much to AI, we won’t stay sharp. We’ll actually get stupid. And that is happening already. People are losing their minds to AI. And I would argue that this greatest risk when we’re younger - kids in school, in college or early career - where they are literally working with AI cutting and pasting the answer, sticking it into the document, the deck, the report, whatever it is, and submitting it as their work. And, you know, that’s not gonna end well for anyone. Uh, it won’t end well for the employee and not for the organization because you’ll have a lot of mediocre work being done by AI. And again, I worry a lot about this. I think that we are at risk of a whole generation of young people who over rely on AI. And really, like we have with, you know, the obvious example is GPS, right? No one can really, no one can use a map anymore and can, no one knows how to find their way in a city. They just use GPS on a phone. And that part of our brain has literally atrophied. That’s kind of spatial processing part of our brain uh, has atrophied in humans.

So yeah, I think that we need AI in some ways. We are overwhelmed with data, content, feeds, information, right? You know, our human brains have not changed much as you know, Henry, in 70,000 years. It really haven’t evolved that much. It’s the same three pounds of cognitive capability and we’re overwhelmed with inputs. And so in some ways, as humans, we need AI to help us manage the cognitive load that the average knowledge worker kind of faces. But at the same time, as I said, the real risk is we offload too much and we stop thinking.

And I have a, you know, we’re very clear about that at Section, at my companies. You can say it once, you can’t say it twice. You say it twice, you probably won’t be working at my company anymore. If you say, well, AI said we should do it, you know, it’s the worst thing to say. You know, I will lose my shit if someone says that in a meeting or in a email or Slack message. I will not tolerate it. Again, you can say it once, you can’t say it twice.

Henry Suryawirawan: Wow. Um, so many tips I think are really great. Uh, in the beginning you mentioned some simple hacks, in fact. It’s not something, you know that is grandiose, right? It could be as simple as remind yourself to always ask AI. Because it’s a new habit, right? I think most of the time, many people are very natural, you know, asking Google search. Um, so I think changing the habit into asking AI is one thing. And I think you also play around with different types of AI, right? So I think that could be another thing, right? Because some AI might be good on some particular tasks. And I think one other aspects about using AI is like experiment, right? Because I mean, as a start, you will be just asking questions, right? A lot of questions and answers. But then there are many other features that AI can also support. Like, I don’t know, like deep research, coding or whatever that is, right? I think just play around and experiment and get the feeling, right? So I think that’s a very important.

[00:41:30] Rolling Out AI Organization-Wide: Managing Change and Anxiety

Henry Suryawirawan: I wanna understand a little bit more about when you roll out this into companies, right? Because many companies now, maybe not many, like a few companies now are trying to roll out AI fully to their employees. Companies like Shopify or Salesforce, right? They even advocate use AI first instead of hiring more people, right? And I’m sure in, similarly it happens in your company as well, but many people are kind of like afraid about their jobs when thinking about AI. They think, oh, if I use AI more, maybe my job, it won’t be safe anymore. Um, so how do you actually create this culture to everyone that use AI, uh, how to make sure that they are still upskilled, they are like safe in terms of, you know, career. Um, maybe a little bit of tips here. How do you actually roll it out fully to the company, yeah?

Greg Shove: Yeah, great question, Henry. And listen, I’d say in the United States right now, almost every organization that I talk to is rolling out AI in some way to either a large part or the whole workforce. And certainly to the soft- to the engineering and product development teams, absolutely. And to marketing, to sales, and maybe the whole organization. And it’s a struggle. I would also say that very few companies that I talk to are doing it well. Most are failing or stalling, really struggling. And it is for some of the reasons you said.

First of all the training is one time and that’s not enough. You must be continuously upskilling with AI because the AI capabilities are changing all the time, always improving. This will be good. This will keep going on for the next several years, right? AI is getting better and better and better. This idea of take, you know, taking one class and giving employees one, you know, one class, it’s not enough. That’s the first thing.

Second thing is, I think if you go back to the beginning of this, like why are we doing AI as an organization? I think CEOs, and you referenced Shopify, Tobi Lütke, CEO of Shopify, who published his memo to all employees why you have to be using AI. And you know, he also said in that, why are we doing this. And you need to have a why of AI. Because if you don’t say to the organization, why are we doing this? Then all they’re gonna think is what you said. They’re gonna think, oh, efficiency, which is code for layoffs, right? Like if you don’t tell people why AI, then they’re just gonna assume, well, you want the robots, you want the AI to do the work. And by the way, the media, that’s been the narrative that the media has been feeding us for three years, right? The image we have of AI is AI is coming for our jobs, and we’re gonna need, we’re gonna be unemployed, or we’re gonna be sitting on a beach, you know, picking up a universal basic income check. I don’t think that’s gonna happen. So… But this is what the media’s been telling us. So of course, employees are anxious.

Here’s how I think about it. So establish your why of AI. What is the mission of your business? How does AI make that mission more possible? Whatever your mission is, if you’re a hospital or a financial advisor or, you know, a retail company, it doesn’t matter. What is the company’s mission and then link that company mission to the AI, and that becomes your why of AI. It’s what I call the AI manifesto. Everybody has AI rules and regulations, what not to do with AI. Don’t do this, don’t do that. You’ll get fired if you do this. Okay, all that’s gonna do is discourage usage. It is so stupid for CEOs to be talking about AI rules. I know you need them. You need them. And your chief legal counsel and your security officer, you know, you need to have rules. So you need to publish them. But you also need a manifesto. Why are we doing AI? How do we think about AI? Do we reward people for using AI? Do we celebrate people who use AI or do we accuse them of cutting corners or cheating? You know, you need to be very positive and affirmative in the use of AI if you want people to use it.

You also need to be honest. So my point of view in this, Henry, is there will be job loss. And not talking about it I think is naive and inauthentic. And I don’t think your employees are that stupid. And by the way, your employees are probably using AI maybe at work even at, you know, unsanctioned or they’re certainly using it at home and they’re realizing it’s pretty powerful. It’s not that good. Frankly, the people who are most scared about AI are the people that use it the least is my experience. The people who use AI a lot can see its value and can see its shortcomings, and they don’t think they’re very worried about losing their job. So it’s kind of this ironic, right? The people that don’t use AI seem to be the most scared about it. But I think you’ve gotta be honest with employees.

Here’s what I tell my team, and this is what I coach other CEOs. Go all in on AI. Pay for AI for everybody. Don’t have people paying for it for themselves. That’s dumb, right? It’s not fair. You’re gonna get the productivity benefit as the employer. As the CEO, you’re gonna get the gain. Pay for the AI. That’s the first thing. Do the upskilling and do the change management. Encourage the adoption of AI. Encourage best practices, right? Watch out for hallucinations. Don’t cut and paste the AI answer into the document. Think about it, you know. How AI is, what advice you’re getting from AI, and then add your own judgment. And the final thing is tell your team, tell your company, your organization, what’s gonna happen.

And here’s what I say. In a year, if we keep using AI as much as we’re using it now, probably more, I want more AI in the company. I want all of us really optimizing ourselves with AI. If we do that, I think there’s four different outcomes and all of them will happen. Here’s what they are. Some teams will be the same size, they’ll be doing more work. Okay, that’s one. Some teams will be smaller and doing the same amount of work, meaning AI made people more productive. We did not need more of that work, so we actually reduced the size of the team. That’s gonna happen in some teams.

Some teams will actually be bigger with AI. As an example, my point of view is because the business I’m in, software engineers and salespeople, ‘cause I’m building and selling a SaaS platform. Software engineers and salespeople are the two of the most valuable people in the organization. If AI makes them more productive, I actually want more of them. I don’t want less software engineers. Talk to any CEO and what will they tell you about their roadmap? They’re always a year or two behind on their roadmap. I’ve never found a CEO, right, in Silicon Valley who says, my roadmap, I got everything I wanted today in my roadmap. I never heard that. Never going to. All you ever hear from a CEO is or a product, Head of Product is my roadmap is behind. I have more features, I have more roadmap I want built. If coding co-pilots or coding agents makes software engineers twice as productive or even 15% more productive, I’m gonna want probably more engineers, right? Salespeople, the same. If AI makes salespeople more productive and more salespeople can hit their targets, do I want less salespeople? No, I want more, right?

So some teams will be the same size, some will be smaller, some will be bigger. And the last thing is we’re gonna add some jobs that don’t exist this year, right? And that’s happened to every year the last two years at Section. We’ve added new jobs that did not exist the year before because of AI.

So those are the four, in my opinion, organizational outcomes that will likely happen because of AI. And I think the best thing is just tell the team we don’t know yet. Like this isn’t, this is a new thing. So I can’t tell you the marketing team will be smaller or bigger. You know, it might be the same size, might be smaller, it might be bigger. We just need to go in this together, quite frankly. It’ll require some trust. And I’m gonna upskill you, so no matter what happens, and again the company has to pay for this my opinion, I’m gonna upskill you. And so if I do have to lay you off, if I do have to shrink the size of a team, at least when you go into the job market, you’re gonna be an AI-enabled employee. They’ll be the most valuable employees, the most valuable candidates for a job. So that’s how I think about it.

And what I would say is if your employer is not doing that, then it’s your responsibility. If your employer doesn’t pay for your AI, pay for your own AI. And if your employer’s not paying for your upskilling and your training, do it yourself. There’s no excuse at this point. Do not let your employer determine your AI future. If they are clueless or they’re hesitant or they’re scared, that’s not a reason for you to be. You own your future. You own your AI future.

Henry Suryawirawan: Yeah, so in the end, I think our growth, our personal growth, you know, our upskilling, it comes back to us, right? I think we are the only driver. Obviously company can support, right? Great companies with great culture, I think will uh, be able to support our growth. But I think, yeah, we should not kind of like rely on just the company. I think many companies still think AI as like an efficiency play, right? So you mentioned about layoffs. I think it was in the news a lot of times. You know, a lot of companies, including big tech themselves, AI providers, right, actually lay off people. And many people actually associate that, okay, AI means more layoffs, I’m gonna lose my job, less employees and all that. And thanks for mentioning those four possible outcomes that could happen when you roll out AI.

[00:51:01] AI ROI: Beyond Efficiency to Creation

Henry Suryawirawan: So I think for those executives now who are thinking of implementing AI in the company, I think most of them probably the ROI thinking is like, okay, if I deploy this AI solutions, I’ll be able to cut, you know, some costs or maybe more efficient in some areas, which is probably like the naive way of calculating that. But what do you think, um, you know, having worked on this area, how do you actually advise leaders, executives to actually see the ROI of implementing AI in their company?

Greg Shove: Yeah, I think that’s exactly right for phase one. So what I mean by that is McKinsey would use a language like efficiency and growth. My language is more crude. I say cut and create. Just ‘cause it’s more memorable, right? How I think about that is there are two modes. There are two strategy modes for AI. One is efficiency, one is cutting, and this doesn’t mean necessarily cutting people. It means cutting tasks, cutting workflows, cutting organizational inefficiency, and so on, right? Use AI to become more efficient. That is, I think, is the first phase of AI. And you’re right, that’s how most CFOs will justify it, right? CEOs are less interested in cutting. CEOs. CEOs want creation. CEOs want growth. So that is the… That is what happens next.

By the way, you can do them at the same time. You can become more efficient and you can find growth at the same time, or you can stage them. Efficiency first and growth second. Create. Create new products, create new services, create new revenue streams, create new jobs. Create new markets. AI will enable that as well. As a leader, my opinion is, you are responsible for both and you’re, particularly, you’re responsible for moving through the first phase, that efficiency phase or that cut phase. You are responsible for moving through that as fast as possible. The sooner you move through that, the lower the anxiety in the workforce, in your workforce, frankly the sooner you’ll get the efficiency gains. And then most importantly, the faster you’ll get to the next phase, which is creation, which is growth, and that’s what your CEO cares about.

So I want an efficient organization. Of course, I do. And we are using AI every day at Section to make ourselves more efficient. I’m most excited about growth. I’m most excited about adding new products and services faster. I’m most excited about accelerating our roadmap, so our software platform has more capability so I can charge more for it and drive more revenue. And so, you know, we’re trying to do both at once, but we did focus for the first year on let’s make ourselves more efficient and let’s eliminate, you know, work, annoying workflows. Let’s eliminate tedious workflows with AI and so on. That impacted a couple people in terms of jobs. Not that many, but it did. We did had to sort of the team changed because of that. Now we’re focused on growth, we’re adding headcount. We’re adding probably less headcount than I thought we would ‘cause based on our rate of growth, we are more headcount efficient than we used to be. That’s great. But we’re still hiring people obviously, and we’re hiring in some cases, I said new roles ‘cause we’re beginning to create new jobs, right? Based on creating new products and services.

So I think about this as two phases. As leaders, we wanna get through that efficiency phase as fast as possible. ‘Cause everybody I think will relax and calm down to some extent and realize, okay, it’s not coming for my job. In fact, I can use this. I can use this to start to create. You know, bring more value.

I talked to, today, Henry, some people who are responsible for AI for hospitals in the US and we talked a lot about doctor AI note takers for doctors and nurses. So, you know, when they’re in sitting with patients. Pretty much every hospital now is almost everywhere in the US is using these AI note takers. And the idea being that if we do that, the doctor’s not sitting at the keyboard, obviously typing notes. And so it’s just like elevating, the doctors didn’t go to medical school to type notes, right? The doctors went to medical school to learn how to, you know, diagnose and deliver care to patients.

And so that’s what we’re trying to move everyone up to the top of their capability. This is the potential. And I think it is happening in a lot of jobs, a lot of roles where we can see how AI can elevate us. And that’s what doctors are seeing, absolutely. And all these, I had four, I was talking to four healthcare leaders, AI leaders in healthcare companies, and they all said that universally doctors love these note takers. It’s drudge work to sit there and, and, you know, type up patient notes and it’s not great. And you’ve probably experienced this, I certainly have, where you’re sitting waiting for your doctor and your doctor comes into the room and the first thing he or she does is sits down at a computer and starts typing the keyboard. ‘Cause they have to start making the notes, right? And what a better experience, what a more human experience if AI note takers are running and the doctor can come in, sit down and look at you and not look at your patient record that’s on the computer and start typing. This has the opportunity to make doctors more efficient. It has an opportunity to make them more humanistic in their healthcare, right, which in the, uh, which is I think good for doctors and good for us.

Henry Suryawirawan: Yeah, I like your maybe slogan, right? Cut and create, right? So I think what you mentioned also, like cut doesn’t mean always cut the number of employees, the number of roles, right? It could be efficiency like workflows, tasks, mundane thing that you used to do maybe by hand or something like that. But now you can actually kind of like use AI to augment the capability, right? And I think I love the example you mentioned about doctors, right? Like simply because they need to type in the past, right? That kind of like burdens the responsibility of a doctor, right? And kind of like consume some, you know, cognitive load whenever they diagnose a patient, right? So I think that is a good possibility where AI can actually improve our cognitive ability.

And I think creation is also another thing that I find. Once people realize the power of them being able to create a lot more new things just by, you know, partnering with AI and all that, I think that will re, that will somehow feel the excitement, I feel, rather than fear. Just like what you mentioned, right? The people who play the least with AI is the one who fear the most about their job security. So I think by playing around and create more, I think you will get this excitement, which I find some people may need to try more in order to feel the benefit.

[00:57:53] AI-Powered Education: The ProfAI Approach

Henry Suryawirawan: The last section of this conversation, I wanna touch on a little bit about your mission to actually train leaders to be more like AI, you know, native leaders, right? And you have even the certification called pro-FAI from Section, right?

Greg Shove: Uh, ProfAI. Prof-AI.

Henry Suryawirawan: Prof AI. Yeah, to actually, um, train people. So tell us about this, I don’t know, like certification or what kind of education that you think, uh, leaders need to take on in order for them to be ready to be AI native leaders?

Greg Shove: Yeah. Uh, so ProfAI is a good example, I think, of AI powered education and how amazing it is. So we built a course catalog, we built a whole bunch of AI classes, and they’re good classes. You know, we were early, you know, before LinkedIn and before Coursera and before, you know, Udemy, Udacity. We were fast to build out an AI curriculum. And that was great. It was good for us for the first couple years. But the reality is education, almost all education today is one size fits all whether it be at high school or college or, you know, upskilling corporate training. It’s like you make a course, you make a training experience, and then everybody experiences the same experience, which really is not very good, you know? It’s, it is okay, but it’s not great. AI powered education is mind blowing. It takes your breath away the first time you experience an AI powered learning experience. It’s amazing! Because if it’s a well built learning experience using AI, it immediately customizes the learning experience for the student.

So a year ago, a year and a half ago, I realized I needed to use AI to build an AI learning experience. And so we started building ProfAI. ProfAI is an AI application. It’s built on top of ChatGPT and Anthropic Claude. We use their APIs. So the experience is powered by AI and it teaches you how to become AI proficient. It teaches you how to find your own use cases. It coaches you on what workflows that you know you can use AI for. And it does all that ‘cause you tell it where you work. You tell it the job you’re in, the company you’re in, the location. You’re in Singapore, you’re in Hong Kong, you’re in London, doesn’t matter. By the way, ProfAI is already in eight languages, and we will soon have many more. Like we’re using that power of AI to teach people AI. It’s always available. It’s basically an AI coach for people who need coaching. And I think we all do need coaching. There’s only 1% of us who are AI experts. Uh, the rest of us need the coaching. So I’ll never make another video class again. Why would I? Anybody who’s making, anybody, anybody who thinks we’re gonna be learning the way we learn today in five years, really has no idea what’s going on right now. And they have no real appreciation for the power of learning experiences that are powered by AI.

So, uh, yeah, we love ProfAI, obviously. Uh, it’s free for consumers. So if you go to prof.ai, you can get ProfAI for free, as a consumer, as an individual. We are charging, obviously teams and companies have to pay for it, for their, you know, for their organizations. Again, I think, if you play with ProfAI, you’ll realize all of learning will move in this direction, meaning we’ll teach everything using AI assistants or agents. And the value of that is they will know who you are and they’ll be able to test you, assess your competency, and then only teach you what you need to know. And you won’t have to sit through a 30 minute video to watch five minutes that you care about, you know. You’re not gonna have to spend an hour on YouTube finding the, you know, the two best videos to watch. It’s such a waste of time. We’ll never do that again in the future.

[01:01:49] 1 Tech Lead Wisdom

Henry Suryawirawan: Right. So I hope you’re successful in your mission to train more people to be more AI kind of like savvy. So Greg, it’s been a great conversation. I only have one last question that I would like to ask you. This is kind of like a tradition in my podcast, which I call the question the three technical leadership wisdom. Doesn’t have to be tech, but it’s more like leadership thing. Um, so if you can give this advice to us listeners, uh, what will be the version of your three technical leadership wisdom?

Greg Shove: I don’t know if I have three. Uh, I have one to start. It’s all about doing what you ask others to do. And that doesn’t mean you have to be able to do their job. But if you want your employees to be empathetic, if you want your employees to be committed, if you want your employees to have care for quality, uh, have care for customers, if you have standards that you want your organization to meet, you must meet them. You must do all of that. You must treat them with empathy. If you want your organization to be AI enabled, you must be AI enabled. I see so much inauthentic leadership and frankly, our employees see that. And so, and that’s when the trust breaks and that’s when the, you know, the alignment breaks. We, as leaders, we have to live our truth as leaders and lead the way we want our organization to behave. So, um, you know, walk the walk.

Henry Suryawirawan: Okay. Anything else or that’s uh, that’s it?

Greg Shove: That’s it. That’s hard. Henry, one’s enough. Do that. ‘Cause here’s the thing. You don’t do it five days a year. The reason this is so hard is you have to do it every day. Leadership is not a, the- you know. We have this archetype or myth of leadership. Steve Jobs, right? These moments of high drama, these moments of high impact leadership, the product announcement or, you know, the that’s what sort of, that’s the myth of leadership. Same for military leadership, right? The single moment. That’s not leadership. Leadership is everything that happens every day that no one sees.

Henry Suryawirawan: Wow!

Greg Shove: So I only offer one piece of advice because it’s a very hard piece of advice to actually do.

Henry Suryawirawan: Very nicely put. I think it’s a great reminder for all leaders out there, you need to walk your talk, right? So it’s not like, okay, please do this, but you don’t embody the behavior, you don’t embody the thing that you’re preaching. We all can see if leaders are inauthentic, right? And that’s where probably the trust breaks and you kind of like don’t actually follow fully from the leaders. So I think, yeah, please be, try our best to be more authentic. Uh, walk the talk and embody the kind of spirit that you actually preaching.

So Greg, I think it’s a great conversation. I learned a lot about how to use AI more, uh, and people here I’m sure they’re kind of like inspired as well to try some of the things that you mentioned today. If people want to follow you or ask you more questions, is there a place where they can reach out online?

Greg Shove: Uh, yeah, sure. Just on LinkedIn. They can find my LinkedIn, Greg Shove, on LinkedIn. Or go to prof.ai to get their access to an AI coach. Or go to sectionai.com and you can find me. Uh, yeah, I’ll do whatever I can to help anyone prepare themselves to thrive in the age of AI.

Henry Suryawirawan: Yeah. And I wanna mention as well, Greg here is, uh, picked as like one of the top AI creators in 2025 by Edelman. So definitely you can follow Greg on social media or wherever you create, uh, including your newsletter, Personal Math.

Greg Shove: Yep.

Henry Suryawirawan: Right? So I find some great pieces that you wrote before. So I think, uh, definitely check out Greg’s resources. So thank you so much, uh, for the time, Greg. Uh, it’s been a pleasant conversation.

Greg Shove: Yeah, likewise Henry. Thanks for inviting me. – End –