Phil Howard: We talked a while ago. All I remember is that I really just liked it. It was a very, very exciting talk. And I remember well, let’s talk about delivering on an ERP project, ahead of time. And you’re like, what do you mean ahead of time? Let’s just talk about on time. Yeah. And and, so I was like, oh, touche. So, so yes, yes. I don’t really know where to start. Why don’t we just start off with, because we wanted to talk about real AI use cases. And with all of the, I don’t know, I think twelve percent of actual venture capital money being spent out there or invested into AI, only twelve percent of it’s actually making money or doing anything worthwhile. And I don’t think we’re really replacing people or humans yet, even though we say we are. and that’s not happening. It’s just an excuse to lay people off. But, so we do need to talk about actual real AI use cases, but I don’t know. Give us your your background. How did you get started in this weird world, this weird world we lived in other than being born into the technology world?
Dima Syrotkin: Yeah, I was nineteen. I joined student organization called Isec, one of the biggest student run organizations in the world. And, they have one hundred and twenty thousand members worldwide something. And because it’s so large, and it’s student run, they have to educate people a lot, and there’s a lot of conferences and trainings and, most of them are functional. They just teach you how to do the job, which is they send students for internships abroad. That’s what they do. But,
Phil Howard: Gotcha.
Dima Syrotkin: Beyond that, though, there are some conferences that are more on personal development. And I went to one of those and it was, who are you and why are you here? And, what are your fears and what are your dreams? And they run simulations, and then they make you reflect on how you act in those simulations. Because typically, the way you act in a game is also the way you act in real life and the choices you make there. And, they had this small groups of twelve where you would share your life story and then become really intimate over the week with those people. And, and that changed my life. And I was like, wow, that’s very powerful. And so I started.
Phil Howard: Can I dig in on a little bit? I just, I got to know, I got to know what was because many people are afraid of a lot of things and that could run their life. And then people realize that they don’t need to be afraid of things, or they do need to be afraid of things and then just confront their fears anyways and say, screw it and do it because we’re all afraid of whatever. I don’t get this afraid of success thing. I think you don’t have success because you’re afraid and that cripples you. I don’t get this. You’re afraid of succeeding. But I think anyone would love to succeed. But maybe that’s just something I’m not getting in my head. But what what what was the fear thing? Or what was the what was this big driving factor? I’m just curious.
Dima Syrotkin: death, fear of death. I had some, challenges with, health, early on when I was, fifteen or something. and then I think, the urgency gave has some, good, positive sides to it. at the same time, if you’re thinking about it every day, it also gets a bit too much. yeah. So that that was on the fear side. and then but my big discovery, even bigger than that, was just that, I was like, oh, first of all, I like this leadership thing. Whatever I did in this organization and leading this team of eighteen people and founding an organization from scratch. I like all of that. And then I was also like. And by the way, I also suck at emotional intelligence. I didn’t even know this thing exists. And then people tell me, yeah, you can actually be aware of what you feel about other people.
Phil Howard: You can be aware that you’re a jerk sometimes. Exactly.
Dima Syrotkin: That’s me. Yes.
Phil Howard: I’m about fifty percent emotionally intelligent. Yeah.
Dima Syrotkin: Yeah, I think I wasn’t that zero, but,
Phil Howard: I was at ten. No go. I’m just thinking of what my kids would say. Where are you at? Let’s see. When I worked at Starbucks, my emotional intelligence quotient, probably, went high because, they. And was back way back in the day, back when Starbucks was trading really high. And it was the heyday of Starbucks. and we still walked into the store and smelled the beans and it wasn’t quite so McDonald’s esque yet it was still, it was still, yeah, it was still an experience. It was still an experience, I guess. And so they’re very big on on. They gave us a ton of training, they really they gave me probably the equivalent of an MBA bringing me in to teach me about PNL and EBITDA and flow through profit and all this different stuff that I don’t know if they really do that for a store manager now. I think they probably just you’re a meets expectation needs improvement type of thing. Here’s a book with some, maybe they still do, but I think they are investing a lot in their leadership back then. So I got a lot of benefits out of that franklincovey stuff courses. I remember some other they sent us to a lot of courses and it was really, really awesome. Yeah. And I remember reading Emotional Intelligence, and at the time I had maybe four kids so I could still teach and have, I was teaching my kids, let’s do goal setting and all that stuff. And then I ended up with eight kids eventually. So I think my ability to divide time equally went out the door and it became back to more of a carrot and sticking and mediocrity, I mean, meritocracy, a meritocracy of, so it I think it I think it ebbs and flows, however, when you have kids and you have girls and boys all with different personalities, you realize that some of them think you’re a really good listener and others think you’re a terrible listener. So I think trying to be rated high on the good listener scale with all of your kids would mean that you have a higher level of emotional intelligence because you’ve learned to connect, discover, and respond with various different personalities. Yep. Does that sound somewhat emotionally intelligent?
Dima Syrotkin: It does. It does, Yes.
Phil Howard: Or working or when you travel and other cultures, because I’m assuming you’ve traveled clearly. You do have an accent and or I have the accent. There you go. There’s the emotional intelligence it depends on from what frame we’re looking at this. Right. Yeah.
Dima Syrotkin: The I definitely.
Phil Howard: White American accent. you realize sometimes that other cultures you really have to decipher and figure out what’s going on. What do they find is rude? What do they find is normal? You give someone the middle finger and I don’t know, somewhere else. They they’re like, cool, man. What’s that like? Or people point with the middle finger and you’re like, in America that’s a no. But in other cultures you might do something with your finger that’s really offensive. So I don’t know, sorry, I digress, but that does have a lot to do with leadership and definitely technology, where many of the technology people are looked upon as drones and not emotionally intelligent and hiding in a server room, or a coder hiding in a dark room coding. And don’t talk to me. I’m smarter than you type of thing.
Dima Syrotkin: Yeah, yeah. And the interesting thing was basically I started a bunch of businesses in this, in this field. Right. So initially, a corporate training marketplace, then I worked on measuring effectiveness of corporate training. I worked on, matching startup founders to help them, help each other and coach each other. and I learned that, there’s a very interesting problem that is, multi-billion dollar problem, which is looking at it not from a individual perspective, but looking at it from the organizational perspective. So what happens on the organizational level. What what does development, emotional intelligence all of those things. What do they mean on the organizational level. And fundamentally, if we look at the job of the C-suite, I think of their job, I think there’s two, two, two jobs, basically. There’s a strategy creation and strategy execution. You need to know where to go and what what to do. And then you need to actually do it. And that whole change management. Right that you also put in the title today, that is the execution part, that is, managing change, managing that implementation of that new strategy, whatever that is. Right now most of our use cases are around AI adoption. So most companies are now like, hey, we need to implement AI. So that’s one example. But it can also be things like, okay, we want to be more innovative and, bring new products to market and things like that. it can be, M&A. We just bought some companies because we think that, it will help us accelerate and sort of increase. One plus one will equal three. But also notoriously most M&A fail. And that’s because of the execution part.
Phil Howard: Me. Okay, I gotta give a shout out to Alex because I flew out to Vegas to see him a couple weeks ago. And how was that? was, life altering. Thank you. Alex. You’re not going to listen to this? You’re not going to listen to this. You’re not going to have time. But maybe I’ll throw. What I’ll do is I’ll throw this out as a Google review for Alex Hormozi. And I’ll be like, we reviewed you on your podcast. Let me tell you about what Alex’s team is like. once you get there and you meet his team, you could care less about meeting Alex Hormozi. That’s how good his team is. Every single member of his team is best of the best. The absolute best of the best. And that’s one of his, hiring strategies is, you either hire, young and hungry and really, or you just have to hire the best. we’re going through a rebranding now. We’re not going to be dissecting popular IT nerds anymore. It’s going to be this massive reveal next year, but because of that, I hired the best. It was not cheap. But David Breyer will give you a shout out as well. Who was the guy that branded the company? No before? For anyone that knows the security company, know before is now going to be is is our branding expert and he’s, he did a great job making sure that, it leadership is really, really felt and and heard. And that’s a little bit of a foreshadowing. but but as far as Alex, the reason why I thought of this is when you said creation and execution, because one of the things that, he likes to go over, one of the things that he talked about is, solving problems and going, what’s your number one problem at this time? Right? So if a CEO’s idea is to, create this strategy and plan and then execute on it, and part of creating that strategy and plan might be solving a problem or solving a problem in the company, depending on if he’s come in and taken over or something like that. But one of the worst things that you can do is solve the wrong problem.
Dima Syrotkin: Mhm mhm.
Phil Howard: So meaning that problem might not have any trajectory towards what you’re trying to what you’re trying to accomplish as a company. It might have. No it might not have no impact on the bottom line. It may have no impact on numerous numerous things. And then you go to solve this if you’re solving the wrong problem, then moving on to execution. Now you’re executing on solving the wrong problem. It’s this really snowball effect, if that makes sense. So I would love to ask you about from the creation piece. And the execution piece is, well, okay, if we’re executing, we might be executing really, really well on solving the wrong problem. Well, how do we know that we’re solving and executing on the right problem to begin with?
Dima Syrotkin: one of the elements right is so. I think that, if things go really, really well, if we look at, the current stock market, if we take out the Magnificent Seven, most big companies, old companies don’t really grow. They’re quite stagnant. and I think part of the reason could be their size. Right? At some point when they get to a certain size, they just, they stagnate. It’s innovation stops. There’s too much bureaucracy. Things don’t go anywhere. And I think the solution is not I mean, yeah, part of the solution could be just smaller companies. but I think part could be in the future is that you would have sea level and you’d have individual contributors. And the middle management in between will be AI and the coordination will be managed by AI. And so the question is, okay, what does middle management do? I think fundamentally middle management has a couple of jobs On one hand, it’s aligning people around that new strategy and telling them, hey guys, this is what we’re doing. Do you need any support? Let me coach you. Let me help you. This is where we’re moving. And what are your goals? Okay. Your goals are not aligned. They should be more aligned with this. So all of that, there’s the other side of it, which is, they also help sea level to collect information from the frontlines.
Phil Howard: That’s exactly what I was thinking. Yeah. Tracking.
Dima Syrotkin: Yeah, exactly, exactly. What is really happening in the company? And what are the best ideas that the people on the frontlines have? What are they saying is breaking? What are they saying? Should the strategy be. And of course, they might be wrong because they are looking at something very myopically at their part of the company only. But they could also be right. And they could also spot something that sea level would never notice. And so yeah talking about strategy creation and how do we ensure that we are actually looking at the right problems. I mean, I don’t think all of it is quantifiable, but I would just say one of the factors is exactly that, which is also what our product does. But helping the C level understand, what’s, what’s happening on the shop floor basically.
Phil Howard: And delivering on. Delivering on what? I’m assuming, numbers and reporting and feedback. Super awesome. How, this, it’s in parallel to what we’re talking about, but you mentioned being in an environment, the environment that you surround yourself with from a, from a creative business standpoint, whatever you were talking about, you mentioned moving and how a move really affected you. I just was hoping you could talk for a few minutes on that, because I just got off a plane yesterday. I’m in Morocco, so I did, maybe the opposite. Yeah, not although Morocco is in the top eight African nations that’s, has a whatever growing GDP or whatever that is. And I might disagree with you just because I don’t I’m not a, I’m not a Silicon Valley guy. But you are so but but I definitely, if I maybe you can convince me.
Dima Syrotkin: No. I think fundamentally, it’s just my experience has been that, first of all, it’s I, I like making friends and it’s easier for me to make friends in an environment where these people are a little bit more like minded. They don’t have to be the same, but they are also ambitious, a lot of smart people here. Creative. Native. also weird. they think differently. So so this, Yeah. And the Bay area was just the place where I, I found that concentration to be the highest. And I find that beyond just, enjoying my life more and, making more friends. I found that, italso was very learning experience being here. Because there’s a lot of people here who made it already, and it’s the way you travel to see Alex Hormozi. It’s, I feel I’m surrounded by Alex’s for Moses here.
Phil Howard: Yeah, I get it. Although I’m not going to Vegas. I’m not moving to Vegas. I should, God willing.
Dima Syrotkin: Vegas.
Phil Howard: He’s in Vegas. Oh, wow. That is, quite a place to be. Quite a place. I just, I mean, I just I can’t see myself moving my business. I mean, I’m sure there’s I’m sure he’s answered this before and, shame on me for not knowing, but I’m sure there’s, legal reasons and tax breaks or something like that. I’m sure there’s, some reason it’s, I don’t know. Musk moving to, where, where did he go, Texas or something. Where did he I don’t know.
Dima Syrotkin: But then he. Bought Twitter and came back. So it’s kind of that’s.
Phil Howard: Yes. I digress the so how do we how do we get on to executing and managing, the cost of change inside companies that’s really cost billions every year. And how could we say take an insane ERP project that is, I don’t know, through an M&A or something like that and actually deliver it on time and on budget? That is that’s a crazy, crazy idea. That’s what everyone’s told and everyone believes. Everyone starts off believing that. Everyone starts out believing we will deliver. I believe the vendor, he will deliver on time and on budget. And, there might be, some Five Percenters out there that do that.
Dima Syrotkin: Yeah, I think that, all the old tools should stay in the box, but I would propose adding one more tool and basically buy all tools. I mean, things, yeah, consulting that helps you figure out if you should, if you should even do it. And then, it would be all the workshops and trainings and learnings and, emails, all of that is probably good. And probably should stay, at least for now. What where I’m contributing is saying, okay, so how do we, support the individual, right. So having this AI coach, AI consultant that can talk to thousands of people and provide personalized support that both takes into account their needs, but also organizational strategy. And so it helps them understand what the hell the company strategy is, how it relates to them, helps them set goals, follow up on them, educates them. So, for example, if we work with AI or ERP, what can I do and what it cannot do, what should they expect? And then helps them brainstorm, etc.. Even emotional issues, many people with AI specifically, many people are afraid of it and afraid that, they’re going to be replaced and things like that. So it could help them understand, okay, is that a valid fear and how should you think about AI? Could it be an opportunity instead of being a threat? So that’s level one. Level two is the group level and team level. And that’s where we’re not doing much yet. But we’re we’re really excited to do work in the near future. And that would be things connecting people. So I ran focus groups where I asked people in big companies and I asked them, if you work with your AI coach on a problem and it says, hey, besides you, there’s someone else who’s struggling with the same problem. Do you want to connect with them and see if, you could figure it out together? So a staggering eighty five percent of people said they would, they would press. Yes. And that wasn’t the case for every feature. This was the highest rated where people were like, yeah, I definitely would want to. And they told me they were like, look, often in the big company, I have no idea what other people are working on or what they’re doing or. And, and often, we’re repeating the same stuff where we often later realize someone else already did that job. And also, it feels lonely because, even though it’s a huge company, you have a lot of colleagues, but you don’t know most of them. And so you don’t quite connect, very, very frequently. And, this trauma bonding around the same problem could actually be one way to connect. And then.
Phil Howard: Just. You’re blowing my you’re blowing my mind right now because it’s has even from a sales so for all the CEOs that are not listening to this, the CTOs and the IT directors and managers, you could deliver something that could actually probably really drive sales success, which is how many salespeople deal with a very particular type of objection or block to a sale. And there’s another sales rep in the organization that has dealt with it very, very successfully. And the new guy doesn’t know how to deal with it. I don’t even know that other person exists or I mean, really from that standpoint or what? Emails. Imean, there’s a lot of things from sales and marketing that can get very, very, very tiring and exhausting. Split testing things, sending out different emails, all these different things that marketing people just throw up against the wall and just, hope things work. And I’m really hoping they can apply that to LinkedIn. So I stopped getting really, really annoying. Invites that are five paragraphs long. Yeah. Should be able to do that.
Dima Syrotkin: Yeah yeah.
Phil Howard: What have you guys seen that’s been very, very successful. That’s driven the needle. So what what AI what AI use case do we have right now? Working, breathing, living that’s actually delivering. That’s actually delivering.
Dima Syrotkin: We’ve helped the company, for example, to launch three AI products. So it was an AI transformation case. and by the way, one of the pieces, which is I could illustrate through through this use case, is also again delivering collecting data from those conversations and then delivering it to the sea level to inform them on what’s what’s happening. And so in their case as well, we helped to educate their people on AI, we helped them to think about potential new product ideas, do some sort of MVPs and then, distill that to the sea level and say, hey, here’s what’s happening. And then the sea level went in and empowered a certain certain groups and saying, oh, this is actually a super cool idea. We actually think this makes strategic sense. And then they ended up launching three AI products in the span of six months. And it’s a public company, so they don’t want to reveal everything. The, the breakdown of their revenue, but it made them quite a few millions. now that’s one example, which was very, very.
Phil Howard: When you say an AI product, can you just describe that for a minute? Is this like. Yeah. Because what some people sell as an AI. I have a lot of.
Dima Syrotkin: So they have very little tack before.
Phil Howard: I guess my point is we have a lot of CTOs, CIOs, IT directors because of IT being pressured to we got to go AI. We got to go AI. And every time they have a meeting with their their senior leadership, it’s, what are we doing with AI? What are we doing with AI? And so that can mean a lot of things. It could mean we custom built.
Dima Syrotkin: Yeah, they’ve done a lot of trainings and consulting and things like that. And then now, besides those trainings, they they’ve built those AI follow ups on top of them that help their customers to actually practice what they preached during the training. And basically, instead of just doing this one time workshop thing, it’s, yeah, this one time workshop thing. But then we also have this automated but personalized at the same time, support for the next six months. so it’s very simple. but. It, it. Adds a ton of value to what they do because, yeah, the retention from workshops traditionally is very bad. So that’s an example.
Phil Howard: Yeah. Is this a bot that sits on a desk or something or. Okay, what’s the most practical way someone could implement AI in their organization right now? Is there even a is there a. Pathway or a. From from creation to execution. To go back to the beginning. Is there a place to start that someone should start? If they’re just getting pressured, we’ve got to be an AI, we’ve got to be an AI. Is it, is it? Why don’t we just deliver some really, really good? I don’t know, like.
Dima Syrotkin: Yeah. So I mean, what our, So if you look at the MIT report, on AI, they say that, companies are twice more likely to be successful, actually, if they buy versus if they build in-house, which does make sense to me because most of them don’t have the expertise to build in-house. So, you can build some, small things in-house, but, yeah. And so our basic AI adoption track, it basically starts with, understanding what AI can and cannot do. So it’s, okay. Let’s. Let’s develop accurate beliefs about, how you should think about this thing. For example. Right? you could say, okay, suddenly AI is actually really good at reading a bunch of qualitative data, a bunch of text and summarizing it, and it’s, okay, that’s good to know. And now you can think about, where could you apply that? How does that work? So that’s that’s number one then would be okay so let’s then identify what are the actual high impact AI opportunities in your workflow. Let’s map out what you do every day. And are there any pain points. Is there something we could automate or do better etc. and give you some insights on that. Then step three could be looking at AI tools. So there’s a lot of AI tools out there right. And back to buying versus building in-house. Sure. You could. build something in-house, but would it be easier to look at what’s already available? and there are certain things I was, talking to our bots, talking about, okay, we want to, screen our code for vulnerabilities and increase security using AI and it it, it recommended me a couple of tools and and one of them is a public company. The other one is done by Microsoft. It’s, I don’t know if I would have wanted to, do this in-house, I would rather just get a tried, tried and true solution. So.
Phil Howard: Use AI to buy AI. First of all, yeah, use AI to buy AI. Crazy.
Dima Syrotkin: It’s it’s AI. All the way down. Ironically, yes, but our tool is very specialized, right? So it’s not just this ChatGPT thing. It helps you specifically with this thing. So, I think.
Phil Howard: That’s also. Someone has to build. Yeah, someone has to build.
Dima Syrotkin: Yeah, yeah, yeah. Exactly, exactly. And then I think what’s also useful is, understanding what’s what’s your vision. How does this apply with your personal, organizational goals, personal values. What’s your, six, thirty, sixty, ninety day plan to make this real. So we’re also helping people with that, taking first steps. And then, yeah. So this is, this is some examples of types of we call them exercises that can be very useful for, for people, or going through AI transformation. And then imagine you sort of aggregate all that data and you have hundreds and thousands of people using this. And then you aggregate that data to the C level and you’re like, hey, you people identifying this issues in their workflows. And this is. Where AI. Seems to be most useful potentially. And this is some of that they’ve built. But they might need resources if, you want them to go further with this. And these are the things you might want to empower because they seem to be they got the most traction just from building some MVPs. And, and they, they seem to be most frequently mentioned by, by the people in the company. As biggest challenges.
Phil Howard: Fascinating. With this idea of getting to the the root of the real real problems around around change. Yep. And what’s the. So there has to be some guiding principles. There has to be some guiding principles, even behind any software or. Yep, artificial intelligence. What are these guiding principles in your in your opinion or what should they be.
Dima Syrotkin: Yeah, there’s a bunch. But basically, one of the big things is that, change is constant and rather than sort of, viewing this as a project, what we tell our clients is that, it’s everything is always changing and it’s more it should be more you building your adaptability muscle. And by you that basically means every. Every employee in the organization, there should constantly be sort of an awareness of, what’s going on? Where are we going? What does that mean for us? What kind of experiments can we run? And then evaluating those experiments and then scaling successful ones. So I think one of our favorite, I just talked actually to the author of a book, Lean Change Management. Jason little, talked to. Him just. Before talking to you, and, Yeah. So that’s, that’s his philosophy as well, that it’s, you sort of approach it in the same way you would approach sort of any lean process where you, you sort of run experiments, you measure, you learn, you repeat. And, and it’s not this, even if we look at, the ERP project. Right. So first of all, you would try to learn what are the different approaches that work, right? So okay, you tried that training program you measure the effectiveness is it working and if not, why not? If you, use our tool, then that’s embedded there because we’re constantly collecting the data on what is actually what are the challenges, what’s working, what’s not working. And then even after you implemented it, right, you need to still be aware of, okay, does it actually serve the needs? And how can we improve this further? And potentially if you keep improving that over time, then you don’t need to do this massive ten year or five year projects. But with certain things, you can just, constantly have things ongoing, with AI transformation. For example, I don’t think AI transformation is a project. I think maybe an ERP would be a bit closer to a project if you just, okay, we bought this SAP thing, we just need to install it. But most things innovation, AI transformation, etc., it’s not a project. It’s it’s a it’s it’s it’s sort of almost a mindset. It’s a process.
Phil Howard: That’s it’s going. It leaders call their end users customers. At least they should be calling them customers. So this is ongoing customer engagement.
Dima Syrotkin: Yep. Yeah. Absolutely. Absolutely. And, as if you stop innovation, if you stop AI transformation, that’s basically that. That’s the time the moment you start dying. It’s not a good place to be.
Phil Howard: How do we make people. Well, I guess we probably could. We probably could make AI agents that actually people like more than people. But how do we how do we bring back that or I’m sorry saying bring back. it’s already gone. But how do we make it have a personal feel people want to engage with this so they don’t think it’s just it has to be done, right? But how do we. Yeah. How do we differentiate? in the old stupid bot versus, an agentic AI type of experience?
Dima Syrotkin: I think there’s two things. And it’s back to the things we’ve discussed a bit earlier. So number one is I think a lot of it is about what does the bot know about you and the memory and the context engineering. It should be smart. That’s the answer to how do we not have a dumb bot. I mean, that’s a lot of engineering and ensuring that it remembers the right thing about you at the right time and that it knows your context, it knows your role, it knows your struggles, it knows your values. It knows what those discussed in the past. And it takes all of these things into account. So that’s number one. But number two is in terms of also the human touch specifically, I think that the bot could help with that too. Right. So back to what I was describing was connecting people. Right. Right now people are not connecting in these big organizations, but using those AI agents, you could actually you could actually have that effect where suddenly they, the right people can find each other and be like, hey, I’ve worked on this thing. Here’s the book that helped me. I recommend you to just, check it out or, hey, I’m working on this problem. Seems you’re working on it too. Let’s meet for a coffee and brainstorm how we could maybe help each other. how we could solve this, together. So, yeah, there’s a couple of answers that come to mind.
Phil Howard: Of the. Okay. Do you have any favorites? Do you have a favorite Lem, or does it change every week? I’m just curious. Do you have any favorites? Is there anything out there that we need to? I like, I like, I’m. A cloud guy. I’m definitely a cloud guy. I’ve gone back and forth. I liked ChatGPT for a period now. I really, really almost despise it. I feel it’s, really, I don’t feel it’s learned or responded to me or learned me. I feel it’s more I honestly, I just, I don’t know, people throw the term woke around a lot, but I feel I just can’t, I’m not really. I don’t really get to I don’t really get what I need sometimes. And, there’s times where it really knows my voice and it pulls stuff out. I’m like, wow, how did it know to feed me that? And I felt it knew to feed me that because I fed it. Yep. So I know that sounds stupid, but can it feed me anything that’s, I need to feed me stuff that I would have thought of, but I didn’t.
Dima Syrotkin: That’s what we do. And the way we do that is, and most llms, right. They are, pandering to you and it hasn’t. but it has a lot of disadvantages too. And so we that is why we have experts that tell it what to do. So rather than just, oh, Phil has an AI problem, let’s just tell AI to solve his problem. It’s, no, use this framework. This is tried and tested. Run him through these questions. Help him understand whether this is happening or that is happening, and then shift towards an action plan. So we sort of we instructed very specifically what to do. And that has that advantage of, actually uncovering your blind spots basically through through two things. One is the reflection. Right. So we help you we ask you questions rather than sort of just telling you the answer, which might or might not be true. And then second of all is by giving you frameworks that maybe you’ve never heard of about even an AI would not pick up because, it’s, it’s trained on the internet and, on the internet sometimes it’s hard to say what is real and what is not, that’s where the value of real expertise actually shines.
Phil Howard: Now, if we took these questions and frameworks and threw them into, are we taking these questions and frameworks and throwing them into any various different LMS, and are you getting different answers? So okay, so my my partnership company so app Direct we, we purchased devs AI. So the devs AI guys bought us a massive aggregator. As far as I know, we’re the only enterprise Soc2 compliant, whatever two thousand seven hundred GDPR compliant AI aggregator with all fifty plus some odd LMS all aggregated in there along with, private servers and being able to promise an enterprise company that these LMS are not learning on your data. In paperwork. So why? And in the we’re able if you’re smart enough. you said, you don’t want them to build it yourself. But you could have you can hire anyone else to build your agents for you. And I don’t know if that’s considering buying versus building. It’s outsourcing your build. Is that a buy or is that a build? I don’t know, That’s kind of I think. How do you feel about aggregating multiple LMS to into one agent? ChatGPT all.
Dima Syrotkin: I’m. Trying to do. Right. So if you’re trying to, do strategy creation, for example, coming back to our topics, then you typically can wait. So it’s it’s fine. You can aggregate them. You can compare different different ones. For us we sort of had to pick the best one because, we have instant communication for the for the AI coach. Right. So people don’t want to wait ten minutes for one reply. And so for us it’s we we have backups. So it’s if one is offline then we use another one. Things like that. But fundamentally, we, we just use, primarily cloud these days, as a primary one. But for some use cases, on the strategy creation, right. Where, yeah. for sure, you, you definitely want to. And I know some friends who use perplexity for that reason because you can easily. Pick the model there and have different tabs and ask them the same thing and just have different tabs there and not have to go to five different tools and pay for five tools, you just pay for one, basically.
Phil Howard: So how do you get around dealing with, getting different answers? Do we just know, hey, look, forty percent of the time there’s going to be a fail and people just need to know that.
Dima Syrotkin: I mean, you mean with our tool.
Phil Howard: Hallucinations results guiding people down the wrong path? Hey, we just guided forty percent of the end users down the wrong path. Are we connected? I mean, maybe we made the wrong choice or something. I don’t, I mean, I’m assuming you get different answers people get. They’re going to get different answers. I mean, that’s.
Dima Syrotkin: Yeah, we actually, so our answer has been creating this very constrained experiences. So rather than just, okay, we have the whole internet here, we are, no, this is specifically an exercise to do this one thing and do it well. And that tends to produce very good results. There’s very little hallucinations because we specifically tell it what to do basically. And the models are already good enough where they don’t, suddenly start talking about the weather, if you, set the perimeters strong enough. And that’s been our approach. And then when we have those constrained parameters, then a question becomes, okay, how do we forward the person to the right content and the right time? And so there we have a recommendation engine that also works quite well. So basically it just tells you that, hey, considering your problem, this might be the exercises that might be helpful for you. and that that so far worked super well for us. But that’s, that’s our approach. And, and it’s the approach of going very specific versus very general. So I think the cloud has an advantage of being very general, but also being a disadvantage of potentially hesitating a lot and, almost knowing too much. More.
Phil Howard: Constraints, more constraints. Baby steps. Baby steps from, from agent to agent to agent. Yep. Super cool. Okay. Where are we going? Where are we going in the future? Here. What’s going to happen is. Are we are we in a bubble? Are we in a bubble? Are we in a bubble?
Dima Syrotkin: Define a. Bubble. I mean.
Phil Howard: Massive amounts of money being invested into a new technology, with, yeah, only actually producing, twelve percent of the revenue that’s actually being invested into it. So, I don’t know, simplest way to say it, one hundred billion dollars invested in AI and it’s only producing ten billion. That’s not the real numbers, but it’s probably not too far off.
Dima Syrotkin: I think the worst case scenario will be the internet bubble type scenario.
Phil Howard: Yes.
Dima Syrotkin: And what I mean by that.
Phil Howard: Is will it. Really be bad? Will it really be bad, or will it just be some standing heroes?
Dima Syrotkin: Yeah, yeah, yeah. I mean I mean a bunch of companies will definitely go bankrupt, but they always do. So, I don’t know, but who cares? Yeah. Because I mean, to me it’s, I don’t know, I haven’t lived through the internet bubble. Right? But it’s looking at it now, the internet took over the world. It wasn’t the bubble.
Phil Howard: Exactly I lived through it. I lived through it. I thought it was pretty freaking cool. I mean, I don’t know, I mean, everyone else is like, oh, what are you talking about, Phil, you ignoramus? But no, I mean, yeah, I mean.
Dima Syrotkin: It kind of means that. Investors would stop investing for a little bit, and then companies will. The main company, the companies, will grow a bit slower, and they would start just being more profitable from earlier days. And, yeah. So I think that is possible. I think it’s also possible that, that that we will sustain the bull run actually, because it could be that the gains would be so big that, yeah, that basically.
Phil Howard: Or. Be smart and know what you’re seeing be more aware. I think we’re probably more aware. Yeah. Yet people are still there’s still this frenzy. Yep. Going on. Okay. So that’s, that’s the that’s the internet bubble question. Well, how do you how do you survive that then build good stuff, get get acquired basically.
Dima Syrotkin: I mean the consumers are still going to be buying stuff, right? It’s just more about, the investors might be scared and there might be a shift in the markets. and then then what you do is you just you rely less on investors. That’s what you do.
Phil Howard: How about this? What’s your advice to sea level technology leaders, CTO, CIOs? Dealing with sea. What’s your advice to the CTOs and CEOs? The CEO is being pressured to I don’t want to say lie maybe over embellish on their level of AI integration in their companies. And what do you say to the CTOs being pressured to actually implement AI? What what’s the advice? Because a lot of people are just staring around, yeah, we’re thinking of buying, we need to do this. And they’re looking for the low hanging fruit. And I think you mentioned at the beginning, hey, we’ve got this thing that needs to analyze. We get these, I don’t know, government contracts that are thirty thousand pages long. And we need to know from a construction standpoint, how many Phillips head screwdrivers we need and how many bolts, and how many toilets got delivered and how many toilet seats. And we used to do this manually, and now AI can do that for us. I don’t know.
Dima Syrotkin: Yeah. I’ll need to go in a few minutes. But basically, I would say that, a lot of it is, the quality of the strategy which comes from, how much does the CEO actually understand AI? And so I think step one is educate yourself and really spend a lot of time on that and try to understand what’s really happening. How does the technology works, even if you’re not technical. Just it’s not that scary. Dive into it. Understand what it’s doing.
Phil Howard: Educate yourself on technology. That’s.
Dima Syrotkin: And then once once you understand. Where your industry is moving, where the world is moving, where you want to move as part of that. That’s your strategy, right? And then then a strategy Execution. Change management.
Phil Howard: Thank you very much. Been absolutely a pleasure having you on. Can you help me pronounce your last name again? I mean, we didn’t even do this at the beginning because we just jumped on so quickly, but. Yeah. Yeah. So that’s not too bad. I can do that. I can bang one out. Final last words. Final last words to any listeners out there and sea level IT managers. IT leaders.
Dima Syrotkin: Well, if you think about change management, you definitely need to hire McKinsey.
Phil Howard: Okay.
Dima Syrotkin: And. Yeah. No, I think, again, I think what we just spoke about, I think fundamentally actually beyond the change management, understand what’s going on, learn what this is and how this will affect you because I think, people are either overly, ambitious or they are actually underhyped, about about the, the the change that’s coming. I think it’s going to be massive.
Phil Howard: So it’s going to be somewhere, you’re saying somewhere down the middle. You gotta take the middle path, as always.
Dima Syrotkin: Yeah, but the middle path, I think is more ambitious than most people realize. I think I think the middle path is something Klarna that just said that they fired sixty percent of their people and they became profitable and the revenue grew. So that might be the middle path. And I know that most of it is bullshit when they say, oh, we fired this many people. But for example, with with Klarna, it seems real.
Phil Howard: What if they just needed to? What if they just wanted to? What if they just wanted to signal to the marketplace, investor growth. So we’re just going to lay off a bunch of people, regardless of whether it had anything to do with AI. We’re going to lay off a bunch of people. It’s going to signal we’re going to buy back stock, we’re going to do a stock buyback, it’s going to signal growth, and it’s going to increase stock. And then the CEO is going to quit and say, see you later. And then they’re screwed. Is it that how is it real?
Dima Syrotkin: But I think what makes this different is the fact that the job seems to still be done. So rather. Than, okay. We fired the people and, that’s it. They actually have agents that are doing customer service and that are doing marketing, and a lot of inefficiencies that they. Yeah, they automated.
Phil Howard: Awesome. Have a wonderful rest of your day. And thank you so much for being on dissecting popularity nerds.
Dima Syrotkin: Yeah. Thanks so much. Bye
