Ep # 152: Why AI Could Replace Your Sales Team ft. Dan Thomson (Founder & CEO, Sensay)

[00:00:02] Dan Thomson: We as many other companies also have that problem of too much noise, too many channels and just too many messages and just information overload. So I think it's, it is a difficult one to stay on top of it at all levels. [00:00:16] Taylor Kenerson: Welcome to the Hyperengage Podcast. We are so happy to have you. Along our journey here, we uncover bits of knowledge from some of the greatest minds in tech. We unearthed the hows, whys, and whats that drive the tech of today. Welcome to the movement. [00:00:35] Adil Saleh: Hey everybody, this is Adil Hyperengage Podcast. Keeping up on our discovery with with the agentic frameworks and how the capabilities of generative AI has been implemented across different industries we've explored. A lot of platforms in the climate change and manufacturing and, and, and neuroscience like HR people, management, psychology. And, and, and it's, that is, that is the best part about you know, getting these change makers onto our room and make sure they speak about you know, how they are leveraging AI towards you know, enhancing the capabilities of a human brain and how they're automating and solving problems. Significantly lower and cheaper cost enabling teams you know, to optimize the bandwidth and to make sure they, they do more with less. Today we have the CEO and founder of Sensay.io. It is sort of a hybrid platform, a studio where you can build your chat bot for different use cases. You can fine tune, you can specialize, for example, for chat for. Sales for growth, for marketing, and across different industries. The best part about Sensay, which I found is, is that they're open API, which is quite lean, and it is it is super powerful to, you know, integrate into your systems, a hundred percent secure, and and make sure that you built your own you know, AI agents, replicas, digital replicas to serve use cases in different. So, thank you very much Dan for taking the time today. [00:01:54] Dan Thomson: Yeah. Thanks for having me. I mean, that pretty much covers everything. I think that's, that's a great podcast. Done. No, thanks for having me. Obviously it's, it's, it's, it's nice to be here. Thanks for inviting me. [00:02:02] Adil Saleh: Yeah, my pleasure. Equally. And Dan, I know that when you started two and a half, two years back, it was still quite a big noise when it comes to building AI wrappers, AI powered platform. There are so many that came onto onto our podcast as well. The, I know that it's agent frameworks, like building agents, building copilots was still relatively new when you started. So, how did this all come together in the beginning, like the inception? I know that a lot of that has, has, has so much to, you know, you to do your, what you concurred in the beginning your own envision intuition. So how was that process internally? I know that standing alone is not easy, so what kind of people actually joined that moment? [00:02:42] Dan Thomson: Yeah, no, that's a great question. So I mean, the idea really came from a couple of books I wrote probably about eight, eight or nine years ago now, all around the concept of digital immortality and mind uploading essentially around the concept of actually building virtual humans as a way of, yeah, extending ourselves beyond our physical bodies and minds. And so when AI really exploded into space, I realized it was probably five, 10 years earlier than it was meant to be by, by most of the previous expectations. And so that's when, you know, it really prompted me to, you know, put, put my head down and actually build what I'd written about. And yeah, doing it by myself would've been a bit of a challenge. I come from a non-technical background, so yeah, actually building out the technical side would've been a, you know, a bit of a challenge. Vibe coding now makes everything a lot easier, and the app builders, website builders are great, but at the time they still were in their infancy themselves, so. You know, I found out, I found out a couple of friends that I knew would be great additions to the team, and that's how we started building the initial product with, you know, the three of us as co-founders. And we had our first couple of employees in the first, first couple of months. But yeah, the idea was always around building towards a form of digital immortality and virtual humans. And these, these chat bots, these hyper personalized chat bots we build now are, are a stepping stone towards that. [00:03:57] Adil Saleh: Interesting. And I know that, vision has not so much to do with what kind of capabilities the technology and evolution of technology at that current time. You still have to be absolutely married to your vision and you know, a lot of these founders, they're thinking, Hey we do have human in the loop for support for sales GTM marketing. But at the end of the. We need to also be very have a sort of a balanced approach towards like where technology is going and how we need to evolve with it. So how did you find it over course of last two years? Like, how did you evolve as technology? I know that you didn't start all by doing like Sensay studio where people can come and just do three, five minutes. They can create their own replicas, their own team, their own ai, SDRs you know, customer success manager. So, you know, what was the process? And I would say the thought process involved you know, keeping up with, with, with the technology that has really, really moved fast during the during the past two years. [00:04:49] Dan Thomson: Yeah. I mean, I guess we're, we're, what we're building is something that, you know, won't be possible for quite some time. So the, the, the on the stepping stones towards that, for us, it's a constant progression of moving towards that, that vision, those goals. Over the past couple of years, it's, it's partly been starting from the very basic of what that might, that might be where, you know, we started off with a, a little WhatsApp chatbot that was based off of a particular celebrity or a character. And then that's evolved into what it has now with the, the functionalities and the ability to, you know, personalize and create your own chatbot for, as you say, your own purposes, whether it's sales or customer support community management, that type of thing. For businesses or as a personal, you know, assistant for yourself as an individual. So, you know, there is a, a touch of patchwork on that when you, you've been adding layers of different complexities onto what we've been doing, but also, you know, a lot of just rethinking about how we do it. And as we've, you know, had to look at a couple of different industries 'cause this technology can be applied to so many different verticals and, and industries, how we can service those different industries and verticals while at the same time. Staying on our, on our own path and not getting too distracted. Which I guess has been probably one of the biggest challenges during that period has been around around not chasing the shiny objects as we, as we, as we call them and see them. And so that's the. You know, the, the, the main progress has been around, you know, following the, following the path we laid out, you know, making the updates to the technology, improving where we can, adjusting for the different industries that we are approaching and working with, and you know, hopefully making data-driven decisions. Also at the same time, what we've done is, as, as you mentioned, we've got our API, which is built to be an enabler of different industries and different people to access the, the core foundational structure of what we do to be able to offer our. That same service for their own industries and their own verticals, whether that's in healthcare or education, whether it's in networking or job hunting, matchmaking, you know, anything, you know, any, any application where having a digital clone of a person, a digital replica, can be used in some, in some form. Whether that's for B2B, B2C businesses, it doesn't really matter. Using the API enables you to, you know, not have to go through that, that whole sort of process of learning. Trial and error to get to a stage where you have a working product that actually has the same level of personalization. Mm. [00:07:12] Adil Saleh: Okay. So I, I do see a lot of a lot of these you know, I would say businesses that are capturing data at some level. Be it customer data, people public data. They're moving towards building their co-agents, co-pilots, agents you know, they're trying to enable customers to do or specialize or fine tune AI for themselves. How does. What's your viewpoint on a, on a, on, in a longer term view in terms of where this industry is moving towards building multiple specialized agents or enabling B2B, especially in the B2B segment B2B customers, enabling them to build their own AI agents, then just building products that are AI agents. So how do you see this you know, industry moving? This is a big shift, especially in the ai agent from you know, agent frameworks Gentech space. [00:07:56] Dan Thomson: I think the people who are, you know, early adopters and the people who would, you know, be good at building and, and using agents, I probably already are right. There's, there's two kind of problems to it though. The first problem is that the, the sort of term agent gets thrown around far too liberally. An agent right now is literally, you know, apparently anything, whereas the, the true form of an agent should be something that can actually perform a particular action for you or a series of actions. And I think that gets mistaken a lot in the industry, which I think is one of the biggest, I guess, blockers to people and their understanding, and therefore the usage of, of proper agents when it comes to the adoption as well, like people aren't. The vast majority of people aren't necessarily that, that creative or that that sort of, you know, open to this kind of change of way, way of doing something. So there is still a limitation to the, you know, usage of this kind of technology where, you know, it's, it's limited to the people who are more tech savvy, who are, you know, a bit more creative and would wanna build something to, you know, make, make their life easier. Otherwise, the vast majority of people waiting for a tool to become so popular that they, they can just adopt it. Like we've got, you know, plenty of friends who know wouldn't have used AI until probably about this year when the, you know, voice to voice becomes so good just so they can have a, a phone call conversation with it and just literally just talk to it as if it's a person. And I've been seeing a lot of that recently, and I think that's gonna be the same for agents. I think there's gonna be a few good builders out there who build a tool and know how to market it and distribute it and, and really. Now that, that sort of distribution chain to. Make those agents or swarms of agents actually practical and useful and maybe they'll end up being some kind of like hybrid network of agents or somewhere or master agent that as a controller type thing that becomes part of the interface. I think that'll probably be the way that it's actually most, that makes the most sense because having that. That tool, that interface to, you know, having all the agents on the backend, you know, so I think that's how adoption will be there when it's so seamless and normal to just talk to a person, you know, you talk to a person and they have agency themselves, and they can go and deploy different agents to get something done. In the same way that, you know, you could look at something like ordering a burger at McDonald's. You know, you're ordering a burger from an interface. But the actual reality is you've got several different agents in a line, in a process to actually produce that burger for you at the end and actually, and actually make it available for you to pick it up. So. I really think that, you know, whoever has the best distribution and the best interface and the best, you know, ability to communicate that to, you know, the, the vast majority of people who are afraid of technology and change will be the ones that actually, you know, reshape how we do it. But right now everything is, you know, too encoded in, in an and anagrams too. There's too much change and too many sort of technical aspects to it that make it very, very difficult, even though it is, you know, advancing so fast. Right now, it's still too difficult for the average person to even begin to look at what they can do, you know, with this. And we see that, you know, you, you ask around anyone you know, and you say like, how do you use ai? And most of them will say, oh, I just use it like Google. And it's just, you know, it's not, you know, it's not, it can be used like that, but it's, there's so much more that can be done with that, as we know. So it's really either a matter of education or just. Building an additional AI layer in between that helps you to, you know, mitigate that by, you know, making it ease, easy for anyone to use the more advanced features. [00:11:19] Adil Saleh: Yeah, adoption is a real real, real problem. Even you know, a lot of these B2B companies that are building in their, you know, like Gong and many companies and even crs, they have their own specialization. They have to invest a lot into customer education. A lot of them came into our podcast and shared that. So how do you invest, like what kind of initiatives are you guys taking towards customer education? Which is the bigger thing, especially for the industries you mentioned you know, doctor's, clinics and you know, wellness centers, shops, restaurants, how this this movement is going to be expanded into industry that are not so much tech savvy. They're, just using as, as it as an automated integration of any kind of like payment education on a base level. So how do you guys invest into customer education? What kind of mediums you have you know, for, for that level of education to be spread across different verticals. [00:12:09] Dan Thomson: Yeah, so from our side, we just try and make it as simple as possible. We really just try and make the actual, you know, user flow for us as quickly as and simply as possible. We're actually working on the, you know, the chat bot creation flow right now, which could be done in two minutes. You put in, you know, your, your, the person that you are trying to emulate or, or replicate as a sales agent. So for like your CEO or sales manager, it will find their Twitter or their LinkedIn, and the AI itself will actually create a chat bot based off the personality that it can extract from their information online already. So that takes out the whole layer of having to, you know, build out a custom personality. It takes out the you know, having to think about, you know, titles and, and writing style and everything else, and all that can be refined and added in. But from the very base level, you will have a great chat bot from, from just a few minutes into interaction with our platform. And then I say the API makes it easy, the, you know, the implementation of the website widgets, or even as a telegram or a Discord bot, you know, the, they're all no code and can be done in. You know, a few clicks. So while the customer education is important, I think so is good and easy design, easy ability to actually, you know, functionally use a platform. So that's what we're, we're focused on. And then, yeah, in terms of customer, you know, education for us, you know, where we're Target B2B, we're target, sort of e-commerce and real estate companies and, and some of these other companies that we, and target markets, we, we've identified through our research. We've, you know, been thinking a lot about, you know, how, how, how to sell 'em, the value, you know, what's more important to 'em? Is it cost saving? Is it, is it personal branding? Is it the personalization? Is it, or is it just, you know, increase in sales? And so it's about, you know, communicating with them that the, the ROI is, you know, 500 times the, the cost, or whether it's as simple as, you know, you are, you'll save 30% on your customer support time just by implementing a bot like this. So. I think that's more important still. I think that's just, you know, classic marketing 1 0 1. People wanna understand the true value to them make and have that spelled out as clearly as possible. But when it comes to, you know, people who are a bit more afraid of, of, of ai, I think it's very easy to explain like, you know, what it can do, how, how it does it. And, you know, people have the same concerns around ai, around hallucinations, around, you know, all the, all the sort of negatives we've heard in the industry over the last couple of years. And those fears are still in people. Or what if it says the wrong thing? I'm like, well. You know, you have, you have staff, don't you? And what, what if your staff says the wrong, wrong thing to someone? You know, people forgive it 'cause it's human. But for some reason we, we have a much higher threshold of acceptance for, for ai. And it's nice 'cause we, we can work with that. You know, we've built in a hallucination checker, we've built in different systems that. Stop the stop that, stop the sort of key issues from happening and everything's encrypted and secure. So all the data's private. We're working on a super powerful like sort of data analytics dashboard for each of our customers that you essentially shows them the usage and really shows them that value directly back to them instead of them having to kind of calculate it for themselves. So I guess. Yeah. For us, it's, it is just about making it simple and easy to create and also to understand what, where the value comes from and, and how we provide them value for our service. [00:15:14] Adil Saleh: Yeah, absolutely. I, I love the way that you explained the, like every, everything should have you know, the co some sort of a comparison with the RY, like the return and, and time to value is, is the biggest thing. You know, you, you mentioned about having a seamless onboarding, just two minutes, you can execute it and then you know, the fastest route to delivering them value is going to be the key. And then of course you know, this follows with the retention and expansion so. How do you you know, measure success around those? I know that when you started. There was less noise two years down than so many you know, platforms that have you know, the internal specialized agents that, you know, they probably have like more funding too to acquire customers. So how do you, how do you you know, see through this competition and make sure that you retain the top line revenue and make sure that your product is sticky enough for those, let's support success marketing. The real estate brokers, all these industries that are using your product is sticking up for them. You know, to be able to pay and increase the lifetime value of the customer. [00:16:11] Dan Thomson: Yeah, I think, I think you've nailed it there. There are a lot of AI platforms out there that have got, you know, quite a lot of funding that, you know, are also struggling with adoption and distribution themselves. There are loads of platforms that can do everything for everyone. And I think the, the biggest way around that, both for stickiness and for and, and just for, you know, value and actually, you know, building the business is about having that hyper focus around particular niches and understanding where that market is and understanding the customer. And that's, you know, that's, that's a, that's a problem we've also battled with over the last couple of years. You know, when we, when we talk about creating virtual humans and, and building out these like hyper personalized chat bots. The ability for them to be applied to. And we've identified 50 different, 50 different industries alone that we could apply our, our you know, chat bots to as soon as it becomes that broad. And even within those industries, there's niches within niches, right? So, and, and then where in the modern world where everything's global, like which even demographics you target, so it becomes. Almost a challenge to actually focus. And that's what we've, we've struggled with a lot ourselves and it's been, you know, a very difficult challenge for us to take that big, broad dream of here's what we wanna do and here's all the applications we see possibly through the future. And really just keep narrowing down. We're still not there. I don't think we're, think we're still really working to really hone in on what that final, you know, niche where we, we can take a large chunk of the, the market. And I think yeah, we're, we're still, you know, working on improving that ourselves. And so that's for me is yeah, and, and there's plenty of, you know, business stories about how you, you should start the other way, and I completely agree, right? You should start with understanding ve niche and understanding how having the customers lined up before you build anything. And, and we, we'd be lucky to, you know, have enough funding to, you know, experiment quite a lot. But we, we've learned that the hard way. And so now, you know, we are really narrowing down into the industries and the type of people who need need what we build to, you know, really really take up a large market share of that and learn from them and grow from there. And so that's, you know, for us, that's a. It's, it's, like I said, it's been a massive challenge and I, you know, I think we're, we're a lot better at it now. We're still not anywhere near perfect, but we, you know, we know that's a big focus for us and that's what a, a big chunk of our team is dedicated around is really like honing that in to refine down everything from the, the wording, the pricing, the. You know, the target demographic, the, the locations, the marketing, the, the, the target person within companies and really just, you know, hone in on that because what we can do is so broad. But you know, unless we can identify those, those key markets that are, you know, I. Build us that stickiness and that sort of almost monopoly within them, that's where that's what will be the foundations to enable everything else for us to grow on top of. And so that's, you know, that's a challenge for a lot of people, like finding Yes. It's, it's so easy to build anything. So finding that gap, finding that space, finding that. Opportunity is such a challenge for AI when there are so many mm-hmm. Gen Generalist AI platforms out there and, and also just pre-planning for the future, thinking like, what is future proof against the next update from open ai? What's company, right. So there's, yeah, there's a lot of, lot of consideration in there that we just mm-hmm. Keep, keep an eye on the future while, you know, really focusing on, on being on a target market. Who needs what we do and we can offer the most value to. [00:19:32] Adil Saleh: Yeah. Interesting because you know, having this sort of like self-awareness is super important. Like more than 90% of the AI first companies three years down are still pre-product market fit. A lot of them claim that they have nailed down the industry. They want to scale, they want to go up market. They got some logos but it's still it's still pre-product market. If you talk to their founders, they'll, at the core, they already know that they're exploring and they're trying to find the right target audience, find the right segment. That's I segment, segment. For [00:19:58] Dan Thomson: people to understand that. 'cause a lot of, a lot of the time you know, when people see, oh, the X company raised 10 million, or they've, they've just, they've got this customer, that customer, and you know, there's a lot of just marketing bullshit in there. As you, as you go along, they might have a thousand people sign up to test their platform. One of them might be someone who works at Mercedes-Benz and all of a sudden they'll say, oh, Mercedes-Benz is a customer. Right. At the same time you. There's a lot of, especially around Silicon Valley and the US and, and I'm sure it happens everywhere in the world, but you know, when they talk about number of customers or number of revenue, it's often cyclical. It's you know, you, you might. Spend. You, you, yeah, you might get $50,000 worth of revenue from a customer, but at the same time, you might be spending $50,000 as a customer for them. So yes, it looks, it looks good on your, on your, on your revenues, but in terms of actual profitability, it's not there. And that happens, I think, a lot more than people come to realize. And I think there's a lot of that in the space, and especially around ai, where everyone is trying to like, you know, position themselves as a leader and as an expert. Mm-hmm. The I think that the numbers are often quite skewed that, you know, you've got to assume that AI is like any other business. You know, 90, 98% are gonna fail. The difference with AI is it's gonna be a lot faster. So out of every Yeah. A hundred businesses you see, that get a post on LinkedIn, TikTok, Instagram, wherever, you've got to assume that 98 of 98 of them are lying. Right. So, or bullshitting somehow, or, and I think it's, you know, it's, it's really. I think that's a cut. That's, that's, but that is the game, right? That's, that is the, the investment game, the building game. Everybody's an [00:21:32] Adil Saleh: expert. Everybody's influencer. Everybody's thinking about founder led growth and you know, having dedicated teams you big content. [00:21:39] Dan Thomson: But you also, you also made a good point about how people you know, for the first year were slapping on AI onto their product. And it was just a tragedy BT wrapper, and I think the same thing happened with Agent over the last year. Suddenly everyone has AI agents, but again, this is where I come back to who's actually building something that's genuinely useful for you as a and actually building that sort of automation and integration and, and autonomy in their agents to actually do things for you. And it's actually very, very few out there who really have. For like true agency in the in, in the platform. I think it's getting better. That's definitely coming through as it's, it's still in its infancy, but it's maturing very quickly as an industry and with everything from m CCP servers to, you know, agents being created through GBT Cloud, wherever. And you've got all the website builders and app builders. It's a lot more of it coming through now, finally. But for the first, for the last year, I think it's just been a lot of smoke and mirrors. [00:22:34] Adil Saleh: And one thing that made me so interested is is how these, there is a gain and traction for local networking talking about real estate businesses, getting together, talking about ai, how they can automate their processes, shopkeepers they're getting, getting along together especially in the US like there are so much of local businesses talking about ai. Previously it was different. You know, and, and they're trying to make sure that how they can automate, like chat bot is, is the first thing that they have integrated. Like a lot of doctors that I know. They already have like chatbot system that completely automates the, the initial conversation, the qualification of the patient, and you know, gathering information, you know, making sure that they're, they're a good fit. And, and this, this has changed a lot in the, in the, in the recent times. What do you think about local businesses? Like a lot of these companies chasing, like big logos in tech companies. But I mean, do you think that they're under underestimating this, this industry that is, that is huge. [00:23:27] Dan Thomson: Yeah, well there's, I mean, there's lots of, obviously, you know, AI is a great leveler, right? So it basically means that certain mundane tasks can now be automated certain, you know, summarizations or posting whatever else can, can now be automated with ai. And so it's the great level up even in terms of like job applications, for example. Like suddenly everyone can write a perfect CV because they can use AI for it. So that doesn't mean that they're, and any better now, but it does level up a lot of basic tasks that we would've seen day to day. And that's that, that goes for a lot of local shopkeepers about understanding like how to use AI for, you know, sales or customer support or service, or whether it's simply helping them to understand accounts or legal documents or writing legal documents, stuff like that. Suddenly you've got this chance for them to, you know, have the same advantage there. A 10 person team might have by using AI for their, their social media, for their, I guess just their day-to-day understanding of different things, their, their, their business planning, pretty much everything really. And so. On that sense, it's the great leveling up because it means that anyone who's starting out, anyone who is a small business, has the opportunity to, you know, act like a big business. And that brings the whole sort of like base level of all business and all interaction up to a a higher standard at the lower end. At the higher end, you're still gonna get the, the individual expertise. You're still gonna get the unicorn, you're still gonna get the, the growing fast business 'cause of the creative, that's their ability to understand particular markets and their, and. Their ability to sell to that particular market. But what it does is it just helps, you know, the small, the smaller guys to compete and it helps 'em to stand out. So it's just, it, it brings that sort of leveling playing field, whether it's reducing the, the cost of stuff on the, the bigger teams or whether it's, you know, helping the. The smaller teams to actually, you know, operate in the same way. And so, yeah, I think it's great that, you know, small business owners and just anyone, you know, I think there's, you know, a huge value in this day and age where we are inundated with messaging on LinkedIn or, or email or Twitter, telegram, literally all of your social media and all messaging platforms. Mm-hmm. Constantly inundated with messages and sale and sales tactics to have that, that personal touch again, to actually push sales through. Because especially if you're looking at bigger clients having that sort of in-person connection time suddenly stands out a lot more. From the, the noise as you say. And I think that that's becoming important, not just in, in terms of sharing, you know, business ideas like education around ai, but even just, just common business practice. Just encouraging people to buy from one another and actually be in a network is ironically now gonna be more powerful than ever. 'cause I think everyone's already in network. Yes. Yeah. It's only really been six, well, six months or a year since the, the first real sort of like automated ai, like newsletters and, and outreach and stuff has been out. But over the last six months, I think everyone's, you know, already bored of it. You see it coming a mile away. You can, you, you read it and it's an instant delete. Like it's not helping these people to sell more. I think if anything is hindering. [00:26:30] Adil Saleh: Mm-hmm. Yes, a lot of, a lot of these platforms are struggling with with customer acquisition. Very few of them recently shut down as well. Of course the story that they share on the public is different. But you know, when you go talk to some of their C-suite and they'll tell you the truth, like it is, it is so hard to acquire customers. You have to invest into events, into networking and, you know, you need to make sure you yield relationships you know, not just like outbound or you know, automated messages using ai. So, love this conversation. Dan pick your viewpoint. I want to take take on now thinking about this, the capability of ai I know for product founders. Views such as with this lean pricing, how do you see it economically in terms of API cost for these lms? How do you explore at a, at a larger scale, like how it's, it's gonna make sense economically. I know that your price is like still pretty lean, but thinking about for scale how are you gonna manage the cost of the technology you know, to make some sort of some sort of economics for, from business standpoint? [00:27:30] Dan Thomson: So it's, well, we, we have a couple of new products coming up in the pipeline that, scale a lot, you know, a lot better than the, the chat bots, but we are, you know, I think this is actually one of the most interesting points of and changes in terms of recent business and especially online business tech companies. Over the last decade we've seen maybe long 15 years. We, we've seen it, we, it's been dominated by SaaS services and SaaS pricing and. I think that has changed. We're already seeing usage based pricing completely rev, you know? Yes. Not, not even revolutionized really. 'cause it kind of goes back to what was there before, like credit based systems were always the original usage for things. So going back to usage based systems in terms of will become more, more, more normal. So it's still a bit difficult and a bit, you know, half most people. 'cause you can't plan, especially if you have, you know, one month where something goes particularly viral. So we've got a couple of, you know, side projects that. Sometimes eat up a bit of cost because they just get a lot of attention for, for a few days. And, so that can, you know, be quite expensive. But, so planning for the actual cost and then how you pass that cost onto a customer is, is definitely gonna be a challenge. And I think the new, new exciting models will, will emerge. I'm no economic economist myself, so I, I dunno how that's gonna look in the future. But I, I think there's gonna be different ways that actually work better with the ai, whether it's usage based, whether it is, it does become a cheap enough overall that you end up with going back to fixed, fixed cost per month. But, you know, those fixed costs do all add up as well. So I think, you know, I think people are maybe a bit tired of the of the SaaS structure. Um mm-hmm. You know, if you, everything adds up, you can have something like, yeah, fig figma like what, $7 a month or 13 or whatever it's now and. After adding 20 people into Figma, you know, it starts to add up every month. And that's a big cost for small, small companies. And that's just, that's just one tool. And then you look at every single tool that you pay for a paper per seat on every single one. So in the age of ai, maybe usage is, is a better way to go. Maybe that does become the norm. I don't really have an answer in terms of what, yeah, sometimes it becomes a [00:29:30] Adil Saleh: challenge for a, for a data first company or a company that actually plays on data, the consumption of data especially the, the curries that you build. You know, actually you run at the backend with with lms. Unless you build some, some of your own intelligent large went off your own or maybe some Chinese playing coming in into the game as well. So how do you see that? Like I, I know that three weeks later, once the Deepsea came in and three weeks later, the OpenAI actually significantly lower on the cost on the API. Yeah, so, so that's, that's [00:30:00] Dan Thomson: the other thing. Keep mind that, you know, in theory the technology, the compute and the data processing should actually get cheaper, right? So the L end usage, everything else should, overall. Become cheaper and cheaper over the long term. But right now you're also in this, this difficult stage where people get so used to the new model so quickly that if you're using an older model that's cheaper you know, it shows and so the quality isn't there. And so there is a real trade off against understanding that the future costs against current prices and, and current usage. And I think that. That does take a bit more thinking about, and I, I, it would be a bit of a more of a challenge for our, our CFO than, than myself. But thinking about pricing is, has always been difficult, you know, for most companies anyway. And actually costing things up properly to make sure you are making enough money on top of it. But and also make sure you're getting enough customers into break even. But the. I guess the, you know, the, the, yeah, the main part really is that there is a, you know, a future element to include in this, which luckily we're, we're talking in a matter of months, if not years for these changes and these, these this cost savings to happen. So you can pre-plan for it a bit better, but yeah, it doesn't make it any easier to get pricing. Right. Absolutely. Okay. [00:31:13] Adil Saleh: One more. So now thinking about your team, I know that you believe in you know, and you, you preach a lot of optimizing the team and bandwidth and doing more with less than building your own AI replicas. How big is your team and how, what kind of formation do you have alongside you, like coach market team include success, marketing and sales and what's, what kind of you know, operating principles have you guys said? I know two years is not going a long time, but since a lot has happened. A lot that you have achieved as, as a crew. What kind of operating principles you guys have and what do you guys believe in that that is pretty much envisioned, instilled in inside you and your team? [00:31:49] Dan Thomson: Yeah, so we, we, we move fast. It's a, it is a fully remote team, but it's probably about 50 people now. Maybe 60 or 70 if you included advisors and sort of ancillary contractors. We, you know, we try and meet up a couple of times a year for offsites just to get to know each other. But everything else is, yeah, just build fast, build quickly. We've got the you know, a target of 80% usage of AI for each of our roles in, in, in ourselves. So, you know, there is a big target, big company target to actually use as much AI as possible. Yeah, the team split up is probably half on the development including ui, UX and and product. And then the other half on marketing BD sales geared around different Yeah. Communities market. We also have you know, we actually did a, essentially our own fundraising last year via crypto token sale. So we have a, a few people who work specifically on the Web3 side as well for us. So there's yeah, it's a bit of a, it's, it's a, it's a good, good balance. Yeah, that, that's probably Heather. And then a couple of people in finance and HR as well. So yeah, overall company operation principles? Yeah, we've got our values really the, you know, we try to keep everything simple. Move fast, use as much AI as possible be creative and just empower everyone else. So we try not to get too stuck up in approval processes and too many meetings. So everything's just, it's about finding the right people and probably one of my favorite. Aspects of our hiring procedure is actually finding people who you would be happy if they were your boss as well. So it's finding people that you respect and trust and are happy to work with or have them work for you because you would happily work for them at the same time. [00:33:20] Adil Saleh: Hmm. Very interesting. And you know, making sure that with this ai, a lot of noise using Yeah, it is good. But, don't you think that it's it, it becomes at the same time it becomes essential. It becomes a challenge to mean a cope up with a lot of the information overloading your brain. So how do you guys manage, is there any kind of process that enables or manages the information overload and, channel their thought process and thinking models while they're searching for their problems. They already know their problems, but like they're looking for solutions and all. And using different comparison of alms. I'm not talking about the programmers, talking about you know, growth marketers or researchers and you know, content sales success. [00:33:58] Dan Thomson: Yeah, so I guess, you know, we use our AI as, as chat bots, as ways of helping us to draft our emails and posts and just help us to gather our own thoughts. Our HR manager, for example, has a replica that interviews something like 50,000 candidates a month, which is crazy. So, you know, we, we do use the, the tools that we build ourselves to help that, but at the same time, I mean. We as many other companies also have that problem of too much noise, too many channels and just too many messages and just information overload. So I think it's, it is a difficult one to stay on top of it at all levels. And you know, I think everyone has their own mitigation, but we, you know, we we're at that lucky stage where we, we've, you know, been able to hire really good people who are quite good independent workers. They're remote. So, even though I guess. Time zones are a challenge at times. Myself, I'm, I'm in Mexico and most teams in Europe, so, you know, there's a big sort of time zone difference there. But aside from that, I mean, it's, it's just takes a bit of I just. I guess, in independence and just, I guess, you know, autonomy Yeah. Responsibility and make sure responsibility and how, how you deal with, with your time and just making sure that you ownership are getting the, getting the work done and, and communicating properly. Mm-hmm. And I think that's probably what it comes down to is just good, good quality communication at all levels. [00:35:19] Adil Saleh: Absolutely. And, and Dan, you know, it was I know that it's already a extremely insightful information coming out of you and you've been concrete enough and I love the energy. That's that's pretty infectious. One last question before I set you free, is that like we are about six, seven months down this year. What makes you excited? It could be business wise, product wise, sales even with personally writing some books in the past. What makes you excited? [00:35:44] Dan Thomson: That's a good, good, good question. Actually, I dunno, I'm, I'm, I'm very philosophical about this. I, I, I love the development ai, I love what it could find out for us. I love the, the advancements in what are coming up. You mentioned health tech a lot. You know, there's, there's huge like increase in what's capable with AI through health tech, through wearables. Beyond that, there's, you know, for ourselves, I mean, we've got quite a lot of, you know, big developments coming out. Like I said, a couple of new great products and features that are coming up in the next couple of months. Also, I guess chat GT five coming up was, is probably quite exciting. That always seems to be a big, you know, boost for the entire industry. So excited to see what that has. Yeah, many things this year actually. I think it's gonna be a, a great sort of round out to the rest of the year. [00:36:22] Adil Saleh: Absolutely. Okay. So Dan, thank you very much for taking the time out. It was you know, really highly, you know, informative conversation I had to getting to know Sensay outside of the web which we already know and always knew for the past one and a half years. Thank you very much for coming on and sharing all of this. See you soon. Appreciate it. Thanks for having me. Appreciate it. Bye bye. Thank you so very much for staying with us on the episode. Please share your feedback at adil@hyperengage.io. We definitely need it. We will see you next time and another guest on the stage with some concrete tips on how to operate better as a customer success leader and how you can empower engagements with some building, some meaningful relationships. We qualify people for the episode just to make sure we bring the value to the listeners. Do reach us out if you want to refer any CS leader. Until next time, goodbye and have a good rest of your day.