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- [00:03]
A
Hello and welcome to the Bald Ambition Podcast. I'm your still very bald host, Mookie Spitz, and I'm thrilled to have what looks like the equally bald, but kind of facially follicled Chris Carolyn, founder of the Value first team. Welcome to the podcast, Chris.
- [00:27]
B
Thanks so much, Mookie. Happy to be here. Yep. This was in response to this at some point, you know, many years ago. So it's been working, balanced out.
- [00:39]
A
I try to do the same thing with my eyebrows, but it gets really out of control fast. So about the only. About the only work I do on my head is trim these caterpillars just so they don't unite against me and create like this overhanging shadow to the point I can't even see.
- [01:01]
B
That resonates for sure.
- [01:04]
A
If you're on audio, folks, then you can use your imagination. If you're seeing us on YouTube. Hey there. We are both bald and empowered here, and we can't wait to talk about SAS Mageddon. The sassopocalypse software as a service is going crazy. If you've got any stock in Salesforce, even in DocuSign, you've been wondering what the hell is going on with the market. And the answer is AI agentic technology. And in this flurry crazy AI stuff, everyone's wondering what's. What's the role of some of these players, for example, HubSpot. And a lot of these. These programs, these software as a service companies are going through changes because they realize that the bots can start doing a lot of the things that they've been providing. So Chris is here to lead us through the wilderness. And I understand You've been a HubSpot partner since 2020. That's where you do a lot of your. A lot of your strategy. Give us a little background. How'd you get into it? What are you offering your clients? And how have you adjusted? And really, it seems like busted out now that the AI revolution, the singularity, is here, here to stay, only getting more crazy. But we need great guys like you to help businesses figure it out.
- [02:37]
B
Yeah, no, my singular goal right now in life is helping other humans get to the other side of what I think is going to be a very abundant future for humans as long as we don't get in our own way, which is still very much on the table. And so I'm from industrial oil and gas space. Grew up through. I was a Lab Tech in 2007, moved down to Houston, Texas from Michigan, and at some point on that journey, it's like, well, you could go lead marketing and sales or you could stay being a lab manager. And I was like, well, it'd be really hard to teach somebody about all of our customers and all of our products. And anybody can come in and run this lab. So let me. I guess I'll go over there, right? What's best for the business. Met HubSpot in 2017 after a couple years using Salesforce and yeah, changed my whole outlook on life and, you know, implemented HubSpot at four different businesses, all in industrial manufacturing ranging from 2 million to 500 million. And at the end of that stint, which sounds pretty unsuccessful, as I was like, two went through two marketing leadership jobs in 20. First one was 23 months, next one was 10 months. And I realized that, like, the value of HubSpot or software and systems in general often has nothing to do with the systems themselves. There's dysfunction inside the org, right? And so as I, as I went out to be a partner, I quickly realized because on the inside I was like, man, all this, all these industrial manufacturing consultants, they make a lot of sense. Like, why isn't it getting through to anybody on this side? And then I went on the other side, I was like, oh, they're only speaking the language of SaaS, like, that's all they like. So their manufacturing page is just the SAS page with manufacturing on top. Right. But then I also realized that the infrastructure that SaaS is built on of lead, MQL, SQL, like managed services, all the things that everybody hates, right? AI is coming along and it doesn't like unnecessary complexity and it's smashing it to pieces. So all of the licensing fees and contracts that these companies have been been built on by what I, in my opinion, dehumanizing the whole process. Like, it's just AI is not having it. It's never been easier to build your own stuff, connect your own systems, and really use AI to be more human. To take us back to what it was before sas, where all you could do to communicate was go and say hello, knock on doors, show up at events. We all know that stuff still works. But SAS kind of, in my opinion, tricked us into thinking there was a better way or there's a cheaper way or there's a more scalable way. Right? Sassy. So that's what I'm. Every minute of my day right now is focused on helping folks embrace AI so that they can be more human.
- [06:36]
A
Let's deconstruct the problem for a second for our viewers and listeners. Isolate the pain points that have been explicit and especially implicit and show how your solution using AI makes obvious, intuitive sense. So if we look at Almost all the SaaS platforms, HubSpot, for example, they were designed to solve a problem, which is companies have a lot of different operations that are going on simultaneously with lots of different kinds of needs. So rather than handle these as separate platforms or separate programs, they're kind of cobbled together into one integrated platform. So, for example, if you've got a sales funnel and you're managing salespeople, then you plug in your HubSpot, you got everything in one place extensively. You got your lead gen tool, you've got your salespeople, you got their sales goals, you got your sales messaging and accountability, you've got your metrics and your optimization, and it's all cobbled together in this big spaghetti bowl of software with a user interface, a ui, and then you're putting the onus on the user to understand and use this interface, which was designed to integrate heightened efficiencies, solve all these problems. But it's kind of like football protective gear, causing most of the injuries in football that it's meant to protect. So it created its own set of problems, like, how do we use this software? How do we get from A to B to C without going to F and Q? How do I learn this stuff? How do I use this stuff? Because to your point, and I think this is where you're getting at, Chris, it's so counterintuitive. It's such a mess. It's such a, not to say disparaging things about HubSpot or Salesforce, frankly, if you've used these systems, they're super complicated, super expensive, and just difficult to learn and use. And compare that to our friend the bot, which is. Hello. And you can speak to it, you can type into it. Pretty soon it'll just look at your face and respond to your emotions and intuitively and in natural language communicate what the hell you're trying to do. And then AI, when it works well, does exactly that. And I have a hunch that's where you see this going and that's where you're trying to help your clients get to. Did I frame it more or less accurately?
- [09:21]
B
Oh, perfectly, yeah. What's interesting, like, natural language, right, that phrase. And I like to find these, like, I don't know if it's first principles or whatever you want to call it. These, like, core moments of, like, this is why SAS apocalypse is happening, like, at the end of the day, right? Like, it really has SaaS has really created an overly complicated, unnecessarily complex way to do business. And it's been deemed best practice. Right. And like, what's interesting though, and why I have, you know, why I've put my stake in the ground for like HubSpot and why it's like a little bit different in terms of ecosystem. Like, I was talking to a product manager yesterday that has been there for less, just about a year. Used to be at Salesforce. Used to be like a long time at, I'll say, the more traditional places. And he said the focus on usability is unreal. Like at HubSpot. Right. And that means the data model is different. And. But what. Like in. At the end of 2024, this is how I got to this, this message that I, I'm trying to share. I was, I was talking to Claude and I said, you know what, every time I hear, hear the word lead, I want to lose my mind. Like, it's always followed up or around really bad decisions, like being made. Right. And bad incentives, bad. Like, so, like, what? Give me your AI native approach. If sales and marketing didn't exist, like, what would an organization look like? Like, and it came back with something. I, I was like, I don't know, what are you talking about right now? So I knew I was on the right track, but the premise that the principle was do not get in the way of value. Like, find a way to just let it flow and enable more of it. Right. And from there I was like, okay, there's a trap here. Like, so leads get more leads is supposed to create more revenue. Why is it a trap? Well, in the year 2000, Salesforce introduced the lead as an object in the system that's different from the contact. That was the moment of dehumanization of the sales process in these systems. Why does that matter? Well, that allows us to just go grab a bunch of data, get it in the system. We've never met these people before, so now we got to qualify them. Okay, let's hire a whole brand new part of the organization, sales development reps. Because our salespeople can't be bothered, you know, with this. They're, they're, they're, they might be garbage leads. We don't want to talk to those. Like, we need somebody that doesn't know what they're doing, that doesn't have expertise to go and vet these people out. Oh, well, how are we going to manage that? Oh, we need a system. We need a super complex system now to build. Right? Oh, well, who's going to build that system? Like Salesforce can't do it. We don't really know what the customer wants. Okay. Managed services industry, and it's literally that simple to get to the point where we are making decisions where I need help to build the right thing, but I got to make this calculation of do I have enough hours left in the scope to do it the right way? No. Okay, we're going to build a bunch of workarounds or we're going to settle for a system that we paid for that still doesn't work for us. Right. And that has happened for the last 25 years. And if you listen to leaders from Oracle, from Marketo, I love sharing these kinds of podcasts. They say out loud, it certainly doesn't work anymore. This whole lead, mql, SQL, that whole thing, they're not even sure it was right back then. Like, if you ask them. And we built an entire software ecosystem which is now at like 17,000 apps or something like that. And when you. The moment it was super clicking for me, because value first is all about, maybe we can use some simpler language that we don't have to explain. Every time that we're talking to marketing and sales. Every time I've Talked about lead, MQLs and SQLs with AI, it's confusing. It would get confused. It didn't even. It doesn't automatically say marketing qualified lead with mql, it would get it wrong. And right away I'm like, of course it's not language. It's not natural language. How about words like audience and researcher and hand raiser and buyer and oh, by the way, those are words that we already use. We just don't label anything in the CRM with those words.
- [14:39]
A
Well, it goes beyond changing nomenclature. Right? So let me rephrase this as I heard it and let me know if I got this right. I'm bald, Mookie. And I have a living, breathing profile. And by that I mean I have predilections and behaviors that are measurable and communicable. So I have buying habits that are demonstrated by prior behaviors with metrics associated with them. I engage with my digital environment in certain ways which are also measurable when I interact with a salesperson, hypothetically, or actually, that's another whole set of metrics. So I'm this living, breathing person and I am exhibiting all of these qualities with just really petabytes of digital exhaust. Everything I do, everything I say, everything I buy can be understood and analyzed through the lens of how potentially Viable I'll be as a prospect. I'm not a lead. I am a human with a complex profile. And what we've done with the SAS systems is shoehorn people like me with these complex multidimensional profiles into these buckets. And in doing so we've committed two errors. One, we've forced all of these complex behaviors into these narrow boxes that we then try to analyze independently. And the other one is we've created a framework which just doesn't make sense for other human beings to understand me as a human being. I have become this funnel with lexiconography and analytical engines that don't have anything to do with me in the real world. And what you're recommending is let's reinvent this system so it's reflective not only of me as this real person in the real world, but of the sales team and the sales managers and the company in terms of how they naturally relate to me also. Is that right?
- [17:10]
B
That's exactly right.
- [17:14]
A
And that's a systemic foundational problem with to your point, tens of thousands of applications have been engineered back ass words. Instead of looking at this as humans trying to connect with other humans with intuition and language and even technique that humans have been interacting with other humans for millennia, we have imposed this artificial bullshit construct and force fed it into our customers face. And we've reduced efficiency. We've created more confusion than benefit. And now that AI is here, AI is literally telling us that none of this makes any sense from a neuroprogramming, neuro linguistic programming point of view, nlp. And it's not going to take that much to just re engineer this, at least in a way where we can intuitively relate to each other. That's effective.
- [18:15]
B
Right? And all we have to do is learn how to talk to AI. All we have to do, right? For humans and businesses that are often not great at communication or asking for help. Right? And that's like belief number two, empowerment over learned helplessness. It's an epidemic what SAS has done. And it was 2021 I think we were getting the buy in for HubSpot and like I had to play the game of like, yeah, we're buying HubSpot for this marketing, get more leads. But I know these teams over on service, they're dying. They're dying over there. They just got an upgrade to the ERP and now everything takes twice as long. And I have to sit through this training where they're all like, so wait a second, I have to, I have to attach three things instead of one thing now. Like, all their questions were like, so the system just got worse. Is that right? And it was a forced upgrade. It literally breaks people's minds. So we finally do the work to, you know, be allowed to introduce it to this other team. And she's having issues, like, with HubSpot stuff. That should be easy, right? I go over there, I'm like, let me just go over the desk and show me what's up. Like, the different pieces of HubSpot are taking, like, five minutes to load. And I'm like, how old is your laptop? She's like, oh, about six years. I'm like, that's. No, no, no. Why haven't you asked for a new one? Like, well, I have, and I get told no. And that request and answer is so common that they just stop asking for what they need and they stop asking for the help. And that it, like, takes us to, like. Part of the reason it's so hard to leverage AI in these places is because they haven't been allowed to ask for help. Like, they know they're just going to ask it. It's like, okay, maybe we get to it. Like, it is in charge of making sure the system works, not that it works for humans. And now that's being transferred to AI, where it's like, let's figure out how AI works. Like, no, that's probably. Let AI tell you how AI works. We gotta figure out on how AI works with humans, how humans work with AI. That's the question that we need leaders to be asking. Inevitably, the way that SaaS has created revenue is in the promise of what could be, not what is. It's like, everybody knows they only use 10% of the system, but we don't have time to figure out how to use the other 20, 30, like, 80%, whatever. And what I do when I, like my first engagement, I'm like, all right, you gotta tell me about your process and your goals, and you're not allowed to name any of the tools that you use, and it's gonna be hard. And that's okay. But even if it makes sense and it's like, you're a great user of the thing, it takes us down a path towards. We're gonna start arguing about something that does better for the process. And. But. But don't worry, we'll. We'll talk about that stuff in session, too. And because we have AI alongside us, I can get every. I can get all of the impacted folks, like, sharing their voices much sooner, and then serve them, you know, Much sooner. And it's like 100% of the work goes towards, like just getting people in the same room, speaking the same language so that we can build trust about what the next steps are. Right? And so much of that's not automation, it's not building crazy AI agents. It is, are you comfortable putting the question you just asked me into the AI agent that's sitting right there? Like, if we can't get there, like, doesn't matter how much money you spend on these systems, right? So, like that, like, it just strikes at the heart of these SaaS contracts and, you know, these systems where if you're not a complete platform that's going to enable bringing the context together, bringing the data together in a way where that human is going to feel comfortable asking the question and getting a good answer and trusting that answer. You're not long for this world. Like, the point solution is asking AI the question now.
- [23:34]
A
Well, for years and years, MAP has been swapped with territory. And in all fairness, prior to the AI revolution that we've only been going through since pretty much what, like November 2022, and the beta version of ChatGPT blew everyone's mind, much to the surprise of OpenAI. They didn't even want to launch it because they thought it sucked. Ever since then, though, everything's been turned upside down. But prior to that, software companies put together these Rube Goldberg user interfaces largely out of necessity too. This idea of integrating everything on the back end and having this neural network being able to draw those connections, they didn't have that really. So it relied on the user to draw those connections artificially through the interface. And that's why it resulted in these super complex platforms. It takes weeks, if not months to learn. To your point, most users use, you said something like 20%. I'd probably put it at 5% of the available features. They use the same features over and over again because they happen to learn those. And it's just too much, it's too overwhelming. So they don't even get the benefit of the whole platform. And it's ostensible integration. And see, we've gotten used to that, that we're used to it being a pain in the ass. We're used to underutilizing it, we're used to hating it. And to your point, for the first time, because of this revolution, no, we don't have to do that. We can literally talk to it like we talk to each other. And instead of having to figure out this big spaghetti bowl mess of software links and pull Downs and outputs and inputs and, you know, no, you just type into the box what you need intuitively and out pops your answer. Or you could even say it out
- [25:36]
B
loud or speak it.
- [25:38]
A
We're not used to that. And here's the other thing, and I want your opinion on this, too. The SAS companies themselves are disincentivized, at least for the time being, because they've created these contraptions that are like this. I remember the Jaguars back in the day. There were 12 cylinders and they had these long hoods and they were super cool and they accelerated fast, but they were in the garage more than they were in your street. They were being repaired because it's so complicated, it kept breaking. And when things keep breaking and you need training and you need onboarding and you need updates and you need new versions, and here's the thing, you need subscriptions. That's the billion dollar ticket. And when you have agentic technology being able to do all this stuff naturally, intuitively and rapidly and effortlessly on the back end, then your entire value proposition dissolves and so does your market cap. So the whole industry is like, whoa, hold on a second with this AI stuff. We don't really know. It's not going to say if it's hallucinating, it makes mistakes, it's going to take over the world, it's going to take your job. So, no, no, no, no, no, don't do any of that when the reality is the opposite to your point. It's going to make your life easier and better. And instead of protecting the companies that have made billions, that your inconvenience and heartache right now's the time for the SaaS apocalypse, the SaaS revolution. And it's a tough hurdle to jump for all these reasons. And the last point is it. It impacts the user. So they're disincentivized to start talking to their bot and they're disincentivized to explore this new technology, which is, frankly, amazing.
- [27:29]
B
Yeah. And like, and either way, like, whether you have access to software that has figured out, like, how to enable humans in this way, or you're just talking to your LLM chats like Claude or GPT, like the context fire, like, you still have to figure that out and that's where there's still space for. The companies that will survive are the ones that do that effortlessly. Just give us all your context. And even if we do that, the true context is often in a human's head and every single human has expertise related to that. Right. Who's going to get that out. And who's going to get that out in a way that doesn't make the human feel replaced or that they're about to get replaced. You see companies already like, oh, I guess we shouldn't have fired everybody. Let's bring them all back. And one thing I've been playing with, and I would love your thoughts because it very much turns a negative into a positive in a way where we always thought it was this, but now that AI is here, it's become this. And it was caused by SaaS and the point solutions because it's easier to sell a point solution. What's your pain right now? Okay, we can handle that. Here's the product, here's a subscription. In between all these different SaaS products, there's tribal knowledge everywhere. And when you sit down with somebody, you're like, okay, tell me about your process. Like, oh, it's really easy. Just this step and this step and then I do this thing and send the email and like, okay, show me. It's like 25 steps. They've got four different browsers open, they're calling into the other department to make sure they've got the contact. The amount of like, I laughed when, when the concept of an AI focused context engineer came out, like, oh, we gotta hire context engineer. That's what humans have been like on the front lines. They are grabbing at any context available to them to be able to serve the customer. So you already got that handled. You're calling it tribal knowledge and what if that person gets hit by a bus? Oh shit, we're going to be screwed. So let's try to replace them with an AI bot. No, let's put them in a position to train the entire system because you won't be able to do it without them. And as they do that and don't have to do the bullshit data entry and everything involved in just herculean efforts of context and customer Service. They've got 10 ideas off the top of their head to make the customer experience better. And when you say as a leader, you know, that's the battlefield we need to win on. That's how we differentiate those folks that have been on the front lines. And I only know this from working with those folks and watching like while they can. They often hold value and identity related to being the person that answers all the emails very quickly or answers all the calls or being Johnny on the spot, no matter what the customer problem is. So don't take that away from me. But you know what, like, if we start if we put this like welcome package together, if we could do that for every customer, you know, I had this idea, but I don't know, we don't have time for that. I don't, I don't even know how we would get that done. Those ideas are all over the place. And we can do it now. We've got time, we've got unreal capability that any human can unlock if they're allowed to do so, if they feel safe to do so. And what's being missed right now is I kind of. I'm all over the place here. Like, I, like I normally am, is like, AI ROI is a huge struggle. Everybody knows how to cut because this is what SaaS has told you. Save time, save money. That's been the SaaS like they've never known how to differentiate off of those value props. Now, we can do it at scale with AI, but that only provides, bottom line, if you fire everybody or you make 10x more stuff, which you don't know how to do. Meanwhile, this capability is sitting right there. That a large part of my focus is how can we define value now? Like, do you know what value looks like? Because you can use AI to. You can do a bunch more, you can make the experience better, but what are you doing with that? Are you creating any value? And you are, but it's stuff that doesn't fit on a dashboard. Like, I've never had more fun doing my job before. Like that gets said. And guess what? You get a lot more productivity and efficiency and just creative value out of people that have never been having more fun in their life.
- [33:21]
A
I love this. And this goes back to the first part of the conversation, which is where SAS went off the rails, was dehumanizing the human with systems and hierarchies and widgets and UI and bullshit. And what you're saying now is applied from the human to the lead. That was the mistake. And when we're looking at human resourcing and we're looking at optimization and bringing in AI, the same mistake is being made, which is we're dehumanizing the human. And we think that we could swap the human with a data set and an operational plan. So you covered a lot of ground. And let's see if I got this right. First off, the humans are a repository of so much information. They understand how the systems work, they understand context. That's number one. Number two is a big part of their job, isn't just rifling through the bullshit and wrestling with their SaaS it has to do with relating to other humans, which is it's a human humans providing value to other humans. That's really what a product and service ultimately is. And that's the sweet spot of their job. But what's in the way? SaaS is in the way, processes are in the way, so they understand the context, but they got to jump through all these hoops and they do it ad hoc anyway because most people don't know what they're doing and they kind of have to wing it. And SaaS sucks anyway. So round and round it goes, the cat chases its own tail. So the infinite wisdom of the overlords is we're going to bring in AI and we're just going to fire your ass because you're redundant. We're just going to automate everything with this agentic technology, which I heard is miraculous and can do everything, including your, your job. And then you're redundant and then you're on the street. And then within five minutes management realizes that all your legacy knowledge, the human to human contact and the essential purpose of why you were there in the first place has been fired along with your ass. So come on back. We have no idea what you did or why you did it. We lost the human element. And the agentic technology is only as good as the context and humanity are there for which it can serve. So that is the revelation. And it sounds to me like what you're doing is Time out, everybody. Let's do a discovery and figure out what the humans are actually doing. Let's introduce the AI and the agents to operationalize the shitty parts of their job. The redundancy, the logistical boredom, the ad hoc tedium and everything that's broken and that SaaS basically does a terrible job doing because it gets in its own way. And once you do that, this is your great point, all that extra bullshit and pain vaporizes in the prompt box and into the transformer. The agents are doing all that grunt work that opens up the humans in your own organization to do the human things even better. They've got more time to relate to the other humans. They have more time to do deep and meaningful customer service. They have more time to strategize and understand and optimize their own job. And the best way to do that is to train them not on how to be increasingly redundant and in the way, but train them on how to talk to these agents and bots so that their own humanity comes out even better than it did before. Did I get that right?
- [36:56]
B
Absolutely. Absolutely. Yeah. And it's for leaders. It needs to be as simple as that spot. Wherever you think the tribal knowledge is, like, think of it from human domain expertise sitting there and everybody, folks, everybody selling you intelligence, right? And it took, it took me a minute to get here. But like, because even as you describe these issues to AI, AI was trained on all of this bullshit. So if you ask it for, hey, what does a good funnel look like? It's going to come back with lead, MQL, SQL, like all of this stuff, right? I think in 25 years we're going to look back and like, ooh, SaaS, man, we really fucked that one up. At least it made, at least it made a bunch of data so that AI could happen like
- [37:55]
A
the training wheels for the actual ride. When we had big boy pants and we could, yeah, look, ma, no hands. We can actually do this, right?
- [38:08]
B
But since we have learned from sas, we're trying to sell AI and make money off of AI in the same way. And that includes some kind of intelligence project, right? And once I realized that I was working with this team, this diagram of like, okay, industrial age, like chaos, like everything's broken. Tribal knowledge holding everything together, like, but in this world, AI, we've got unified views, we've got context that we need, we've got intelligence. And when I first added that intelligence layer, it's like, okay, that's where AI goes. Yeah, yeah. And I looked at the other side and the only thing that made sense to match against that layer was subject matter, expertise and key person risk type. Things like outsourced third party that knows how to do it, we're beholden to them. And I was like, wait a second, intelligence, that's not new. We've had that. That layer has always existed, it's just. But humans. So of course it belongs in that layer. And you can rally around human plus AI, that's the layer and it flows through it, connects everything else and it's required. And this is the one spot where you just, if you can understand how AI works. And again, I know this is a divisive spot, but this is why I choose to humanize AI as much as possible. Makes everything easier when you can just say, hey, this is the partner that's helping me get work done. I'm going to humanize the hell out of these agents so that when I call on them by name, I know what their job role is and it's going to just make everything easier.
- [39:57]
A
As a strategist by trade, I do consulting mostly in healthcare, but in Other areas too. It's good to begin with the end in mind. And when I'm hearing you illustrate this ideal future state, it actually reminds me of the transition from the early search engines to Google. And I think that's a meaningful paradigm. And here's how I see it. Back in the day, let's do hot tub, Internet time machine to like 1996, 97, 98. The number one traffic website in the world was yahoo.com. this is when Mr. Mark Cuban was on fire. This is where he made his big bucks. And it consisted of this portal with a million links on it. Because no one really knew how to navigate the Internet. If you wanted your email, or you wanted to check sports, or if you wanted news, you didn't interact with it. You basically knew enough how to move your mouse and click on a blue link and then it would take you to a website where shit was happening related to what you were asking. And in the upper right hand corner, this area no one really looked at and hardly anyone used, there was search. If you were bold, if you were brave, back in the early Internet days, you could actually type in your keyboard and look for your own website. And then all of these search engines started sprouting up. Ask Jeeves, altavista. There was a whole zoo of search engines and most of them sucked. You type in, you know, chimpanzee panda purple, and who knows where you got right? Or even pizza in the neighborhood. Good luck with that.
- [41:46]
B
Good luck.
- [41:47]
A
Larry and Sergey developed an algorithm and spidering technology and then they plugged it in to the ad context engine, right? So they basically cobble all together their, their unique algorithm with this entrenched ad words kind of platform, and they transform the Internet. So, long story longer, here's how the UI evolved and I'm getting to my point. You have this horrible Yahoo.com website with a million links all over it, which is analogous to a SaaS platform. If you look at Salesforce, if you look at HubSpot, there's a million links, there's a million things you can do. It's covered with gadgets and it runs reports and you don't know where you are in it. And what you're getting at, Chris, is the end state, which is an employee of any company with the engines of AI and agentic technology, with all the legacy tribal knowledge, will have this blinking little box and they might even just have, I'm getting it here, a little microphone that they just talk into and make their request. There's no ui. There aren't A million blue links, there's a box and you just express what you need when you need it in its simplest kind of format. And that's where I think we're headed, where you think we're headed. And the thing that's in the way is decades of this SAS clusterfog. Did I paint a picture from a historical context that's relatable and that might help describe where we are and where we should get to?
- [43:39]
B
Yes. I love the way you painted that picture. The one tweak I would love to make because we're seeing this AEO movement now from all the folks that made a lot of money off of SEO. The difference between that box is that you need to be ready to have a conversation with it. I am not a developer, but now I spend my days in the command line, which I loathed. I didn't even want like code, like give me whatever the no code solution is. I'm looking for that. Right? Well, AI said that I don't have to do that anymore, but am I a coder? Am I developer? Nope. I just use AI to get my work done and it happens to use code to do that. So when I put this big old scary black screen up for folks, it's like, this is folders like Windows or, or Google or Google Drive. That's all this is over here. And this command line is the Slack dm and AI is on the other side. Right? And as soon as you can get that connection, like, oh, okay, this is not crazy, right? So that moment, and this is what I think, like, you know, while I feel like not owed, but I am very loyal to what HubSpot has allowed me to do. And I'm probably biased in terms of how well I think they're positioned, but when you get to watch the founders and how they think and Dharmesh specifically, as soon as he said the words agenta Customer platform, right, where I've been trying to say customer value platform, like that's what, that's what businesses want. They want to add, they want to create customer value. I don't know why that's been so hard to get to, but I guess we can't assign the word value to any of the systems we use. Agentic customer platform has to get to that where it is just here's the input bar. Have the conversation you need to have. Maybe some UI pops up around you, but you don't have to configure anything anymore. All you're configuring is the context that the system The AI folks that you work with has to do that. But when you start to learn how to talk to it, you don't even need to think that hard to start shoving context in and be ready for the conversation. Like, when people ask me, oh, what prompt did you use to get it to do that? For the past couple months, my answer is like, I had a conversation. That's how I got it done. Like, there was no specific prompt I used. I don't know what the prompt looked like, the system prompt, whatever. At the end, I had a conversation, and that's how I got to the result. And so, like, this world of prompt templates and prompt engineering, like, just learn, literally natural language. Coming back to that, that's what they are, that's what they use to help you. So that means when you give them natural language, you get the help that you need,
- [47:18]
A
a hundred thousand percent. And I go back to the Google example. Another advantage that Larry and Sergey had over the others is that their algorithm was a little bit more intuitive and it had auto complete as well. It would analyze the beginning of your query and it knew predictively, in a sense, like the predictive AI mechanisms now, in a very crude way, based on prior search terms, what you were looking for. It anticipated that. And that's the essence of the transformer architecture, which is its predictive architecture, right? So when you're speaking, thousands of other humans have begun sentences in a similar kind of way, and the transformer, through its weighting and using matrix math, is anticipating where you're headed, and it's gotten better and better. I remember when AI first took off, to your point, there were people putting up seminars and lessons on prompt engineering. And even at that time, I was like, get out of here with that. You just need to clearly understand how you communicate, what the hell you want. That's prompt engineering. And as the bot gets better at even personally understanding the way your mind thinks, it gets better and better. So you do less and less work to even express your desires. And I think that that's absolutely correct. And it's an end state, which is glorious. You can say that AI is going to take away all our jobs and exterminate the species. And both might be true eventually, but in this moment, in this singularity, it's a golden age of the bots learning about us. And here's the point you're making, which I think is really wonderful. We're not really learning about bots at all. This doesn't have anything to do with AI. This has to do with you understanding the core needs that you have as a human, how to connect better with other humans and operationalize your job by being clear as to what you need to get done. That's it. And the rest is handled by all the agents and all the technology. And that's the way it could and should be. And for the first time in human history, the capability is there to make this happen.
- [49:58]
B
Amen, man. Amen.
- [50:02]
A
And again, I think it's exciting. Tell us about your role in helping to make this happen. I think we painted a clear picture about the problem and the solution, the mess we're in right now and the desired end state. But tell us about your, your work and how somebody who's listening will be like, Chris, I know what you're saying. Help me out, help my organization out.
- [50:30]
B
Yeah, ultimately. And this is like, you know, one of my favorite things about AI is it lets me lean into my adhd, like hardcore. So always lots of things, but it's in the face of when I was inside of businesses, I always heard like, well, we can't blow the ocean, Chris. And I was over the moon last year when I went to this AI summit that was focused on startups and not one person on stage the entire day said the word focus was important, which is a 180 degree change from where everybody was. Why didn't they? Because agility, speed, creativity, that's what differentiates now. So I lean into that always. Bunch of irons in the fire. But ultimately I'm trying to create space again to help other humans share their expertise, to help other humans transition. We're all in this, right? And if you are business minded, it happens to be the whole world that needs to do this. The total addressable market is every business in the world needs to figure out how they're going to use this brand new infrastructure that is just like electricity, except it's AI. And like, whether that's through coaching and conversations like the Value first team, which is like AI consultancy, AI native consultancy, or you kind of know your shit already and you just need other people to feel like you're not the crazy person in the room. The Value first collective is a group of Value first folks that are not in it for the margins and the point systems and the partner tiering and all these reverse incentives that have led us to where we are. And I do a ton of content value for studios. One stance I'm kind of building around right now is I think the only way to learn right now is to talk about it out loud or build Something usually it's both, that you cannot learn AI in any other way. So whether it's content or active, building workshops, creating a space for that. Meanwhile Moki, everybody's building amazing shit right now and it's hard to share it with other folks. So the PS de resistance right now is value first markets I'm working on that's trying to define value in a different way. Recently Elon Musk said he doesn't think money is going to matter in 10 years. I tend to agree with him. When you see everything easy to create and the costs go down, like what are we spending our money on? Well, that's going to hurt for some amount of time. But when you think back to how value was shared and exchanged, like the barter systems, all that stuff, can we enable that before the end of the financial system and say, oh, I really like what you did, but I did this thing and let's just share, let's figure out how to trade and not try to get over on each other and not be focused on all the things everybody told us we're supposed to be focused on. Ultimately it's creating spaces for as many of us as possible to get together, help businesses, help humans through this transition by defining what value actually is, not what the KPI says it is, not what investors tell us it's supposed to be. But like, what does that human like? Is the thing that I'm about to do right now going to create value? If not, why the fuck how are you going to do it? And the only reason I found is somebody told you you had to or that's how you have to use the system, that's how you're graded. And when you talk to humans and you know it in their face like this makes no sense. I don't like doing this every day. I don't want to see any more of that. And you don't have to do it anymore, like point blank. So, so let's go.
- [55:32]
A
So how do we define value? Well, it's personal, it varies individual to individual. Organizationally, organizations, when you get to their core, they're providing a value which ultimately is humans doing things for other humans to make human life better, bottom line. And the problem that's happened is so many steps have gotten in the way between what our value driven goal is and how ostensibly we're going to get there that we've shifted that focus, just like you mentioned, from the core value itself to the perception of value at these intermediate steps to get us where we're supposed to go. To ultimately provide the value that we've completely forgotten about. And your solution is cut that out. Thanks to AI. You know, all those steps where we've refocused our attention and shifted our value, we don't have to worry about those, because AI does that. So for the first time, we could refocus on our core value. And all we really need to do is have a conversation with ourselves and other humans, which is, what's the nature of my work? What am I really trying to accomplish? And most significantly, why? And if you can answer just those questions, everything else dovetails out of that. And you'll get better, too, at asking other humans for what you want and need. And almost as an ancillary aspect of that, you'll be even better at asking the bots to help you get there. And this is a perfect storm of awesomeness, folks. I think you and I are very Pollyanna about the age we're living in, because if we look at AI responsibly, but also through the light of exactly what you've been talking about, we're entering a golden age. It's going to be very disruptive. It's going to have its own kind of pain points. But it frees us up to do amazing things we never thought possible before. I'm a creative person and I'm working on an interactive audio book. Choose your own adventure. Now, before I'd have to hire a whole team, I'd have to start a little mini company. I'd need capital investment in the tens of thousands to make this happen. And now I'm just Claud coding this thing up. I'm vibe coding one of my creative aspirations. That's value. I want to make innovative, entertaining, thought provoking creative things. That's what's valuable to me. And now I can do it with great facility. And all my energy is in writing the script and thinking about the creative aspect, which is my sweet spot. And then I tell the bots to go build it, and then I work with them to make it better and optimize it. Why? Because I want that end state of bringing joy to people with a new experience in storytelling. That's what's important to me, and I can make it happen. And similarly, everyone else is empowered to do that same thing. And in an organizational point of view, take a look at yourself, take a look at your job, and realize that for the first time, you have all the tools at your disposal to make it happen without having to negotiate these pick lists and report generators from this horrific platform that's been driving you nuts
- [59:21]
B
since they plugged it in and yeah, so good. And what you said there and why it's such a problematic lens to view this from is the saving time and save hours and how many, like that interactive book you, you didn't, you're not going to do all that stuff that you said you would have had to do. It just doesn't come into fruition. It doesn't get created.
- [59:53]
A
Not gonna happen, right?
- [59:55]
B
The early days of HubSpot building stuff for AI, I was having a conversation and that was at the, the moment where I was starting to, to do two daily shows, which I've been doing for a couple years now. One for HubSpot updates, one for AI. And like people asked like, oh, this, this, the HubSpot podcast tool, I think is what we're talking about. It's like, oh, how much time does it save you? And I'm like, I mean if, if I were to have done these two shows, like maybe eight hours total. But the fact is I don't do the like. And that's where the. You. It's so hard to measure the difference between doing two shows and not doing like two shows. And the value that I feel within myself being able to do that and this moment of the belief that you can get the thing done. So powerful. My favorite story right now, which should. Anybody that's been in this space, like I do a daily morning show with Casey Hawkins and I've been able to activate her on the command line, which again is not the easiest part. She was using AI, but not in the way I was suggesting she could. And she had to watch me do the command, watch the thing get done, have the realization, oh, that's easier than I thought it was going to be. It's like, yep, after that she has to miss a day of the episode, right? And there's a website that has the clips. Like since she's been activated, she's got, the clips are getting done every day, the articles are getting done every day at the same time. We do an hour long show, right? And it happens within an hour after that show. Well, she had like a tree branch fall on a roof and didn't have power like for a whole day. So she didn't, she didn't join us that day. And then I'm coming back to the site on Friday. She still got that, that stuff done that day because she knew it would only take an hour and that she didn't have to sit there for that hour. It was just this prompt and Come back, look at it. Yep, good to go. And the power of that, like, that would not have gotten done at all. Like, it'd just be like, oh, I guess we missed it that day. And she would have had all the excuses like, yeah, deal with your house. Like, what are you doing worrying about these articles. But because she believed it was going to be easy and that she would be able to get done, it still got done. And there is just so much value locked in there that I'm sorry, that doesn't fit on a dashboard. But CFOs help us figure out how to measure that, how to make that quantifiable without making us make really bad decisions on the way there, which is usually what happens. So as much as I would love to say just feel it. You got to feel how powerful that is. I know you want your dashboards. Help us out. Whether it's. And again, AI is there that we just get to ask AI, hey, what could this look like on a dashboard? Like, we just, we just did all this cool stuff together, like, ask me how I feel at the end and then document that. And then when everybody looks at the end, oh, everybody's feeling amazing. Oh, look at this. Our revenue is in good shape too. How about that? Maybe we can just accept that, like that picture, because that's what AI is doing for us right now.
- [64:04]
A
I love it. It's very human, it's very pragmatic. And adoption doesn't come from forcing someone to sit through a two hour training session in your new SaaS. Platform training comes from in the doing and in the realization that the doing is easier and more fun. And when the doing is easier than more fun, you do more of it and you do it better. And when you do more of it and you do better on your job, then the company is going to do better and profitability goes up almost as an afterthought.
- [64:38]
B
Leave the door open for serendipity and it will arrive.
- [64:44]
A
Thank you for making time, Chris, Carolyn.
- [64:48]
B
My pleasure, man. Thanks for having me.
- [64:51]
A
Value first team the link in the description below. It was really wonderful to have this conversation because it turned the whole AI bubble on its head and burst it in a way that's healthy for everybody, which is stop being scared of it, dive in swimming and see what it can do. And just keep your mind and heart open and realize that when it does what it does best, it's just bringing humans. Here's the thing, it actually brings humans closer together instead of keeping us further apart. If it's done right it does and responsibly. Thank you, Chris. Like comment. Share, everybody. Bald ambition. Take care, Chris. You're the man.
- [65:35]
B
Thanks, everybody.