[00:01:00] Phil: What's up, everyone. Welcome to our first episode of 2025. [00:01:06] Today, we have the pleasure of sitting down with Austin. Hey. Co founder and co CEO of Clarify and martech teacher at Reforge. Austin started his career at Accenture before he left the Fortune 500 world to join a startup called Branch, where he became the fourth employee. Austin then created his own boutique mobile growth and generic consultancy. [00:01:24] Uh, he grew that practice to 1. 5 million with big names like Walmart, Jet, Airbnb, Foursquare, and a bunch of other ones. And his consulting practice was acquired by M Particle, a leading CDP solution where he would eventually become VP of growth. He later joined Runway as VP of business operations, and he also started building the martech Technology Academy, an online learning center for martech, which he would eventually sell to Reforge and become a partner and the instructor for the new. [00:01:51] martech course. He was also at a martech at ramp, a FinTech startup. And last year, Austin strapped on his jet pack and became a product founder at clarify [00:02:00] conquering salesforce. com HubSpot and building the first flexible intelligence CRM that people actually enjoy using. Awesome. Such an honor to have you on the show, man. [00:02:09] Thanks so much for your time. [00:02:11] Austin: having me, Phil. I'm so glad to be here. [00:04:26] Darrell: All right. And I've got the first question. I will say like we, like we were talking before on the pre call, like I'm, I've been a really big fan of the stuff that you're building, Austin. And, um, if I had to guess you're, you're kind of like me. It's, it's hard to sit still. You always want to do new things. [00:04:42] Um, but we could talk about that later. Uh, so the first question is, just from what you've said before, is that [00:04:49] AI Agents and the Hidden Promise of Ambient Computing --- [00:04:49] Darrell: you don't, you think that people are. wary or hesitant to be contrarians. Or to, to be haters. And, um, like for example, if someone launches [00:05:00] a new AI startup, you know, we have to be impressed and we have to think it's a good idea, but honestly, many of these AI startups might be vaporware. [00:05:09] Like it might be very little actual product. And maybe, I don't know, people just running really fast in the background. I don't know. So I'd love to hear like your thoughts on that. And I've also loved to hear, um, um, what you think about the new, this new concept of AI agents and if you think it's really going to get popular or is that also vaporware, what do you think? [00:05:28] Austin: I'll maybe start with agentic experience because I think it's actually easier to answer. AI is such a hot topic right now because It's really hard to imagine what's not going to be possible in the next few years for anybody who's actually dabbling with the technology. [00:05:43] They are very, very much, um, tuned into how quickly it's changing the way we work. Uh, it's not just a, uh, easy blog builder, which I think is what most people thought of it as a couple months ago. Um, it can answer intelligent [00:06:00] questions. It can do math. Um, it really has the ability now to be an extension of your brain. [00:06:05] But there's this element to it that's still very manual because you still have to input data. It doesn't have access to your screen. It doesn't have access to APIs in the context by which you work. And so what I'm very excited about and where I believe the hype is actually real is like You know, imagine a world where it has context to everything on your screen. [00:06:26] It has context to Notion and Slack, um, and it actually is authenticated to all those places because it's just read through at maybe even the operating system level, you know, I spend so much of my time going between tools, but imagine if that was possible and it could scrape the context of whatever is literally on the screen. [00:06:47] Um, it's, it's hard to have envisioned that because we think of it in the current UI of like me having to drab and drop context and then provide a prompt. But I, I think pretty soon we're going to get to the point where you won't need that. You can actually just talk [00:07:00] almost to your computer and it has the context it knows or you can tell it by either navigating to the screen on your computer directly or, um, or providing with that context by highlighting on the screen. [00:07:10] There was a great video actually today from Kieran Flanagan at HubSpot where he was using. Um, Gemini's screen reader to basically showcase how you could talk to an AI agent and kind of like highlight context on the screen and it could give you feedback. And it was a little slow and clunky, so you have to see past that and imagine that it's actually a lot faster and it doesn't do stupid stuff like take five seconds to respond and repeat back to you exactly what you said. [00:07:34] All that stuff will go away like that. I'm not worried about it. So it will become very quick. And, and then you're just left with, like, a, um, a machine that can do things 10x faster. Uh, so, so I think the, the, the belief that agents are, are here to stay is real. I just think, like,some people do not, um, uh, kind of view it in the same timeline as me. [00:07:54] Like, I don't, I don't think it's going to happen overnight. I think it's going to be a five year play. And I think there is going to be a big [00:08:00] difference between what you can do on a single, uh, Software platform versus on the operating system level. And like, I'm most excited about the point in time where that inflection where it has full access to my entire computer, not just the program that I have in front of it. [00:08:15] So like, I'm less bullish on agentic experiences within a specific platform because then it's platform. agnostic, or I'm sorry, not platform agnostic, it's platform limited. It's not really able to get the context of the rest of your life. Um, but you know, for example, um, GPT has a desktop app and so is Anthropic and like those things are really interesting to me cause then it extends beyond just what's possible on the platform itself on like the actual web app that you're on. [00:08:41] Darrell: Maybe, maybe, maybe, and I'd love to hear what you think too, Phil, is because, so I think that there's this, this sort of narrative happening where [00:08:49] The Limitations of AI Agent Marketplaces --- [00:08:49] Darrell: people are saying AI agents, like there's going to be like this marketplace for AI agents and you know, they're just going to, you know, there's a, there's a bunch of point [00:09:00] solution AI agents that you can just hire to do your stuff. [00:09:03] I actually am not bullish on that. And I'd love to hear if you. Both think so. So in my opinion, I kind of think of that as like the, the Chrome extension store, you know, how you have like the, you know, with Chrome, there's a bunch of extensions you can, you can have to like do a lot of things. And I feel like it is useful, but it, at the end of the day, it doesn't become like core to the way that you work. [00:09:26] It's more of like a nice to have. Um, I really think that the platforms of the future will have AI integrated to the point where you don't have to get. You don't have to go out and buy these tools from an AI mark, AI agent marketplace, but I, I'd love to be proven wrong or like debated with that because that's kind of how I think. [00:09:48] What do you guys think? [00:09:52] Austin: I mean, I mean, this is like I think a crucial part of what VCs are betting on right now is the, is the future, um, a [00:10:00] world where you have. Robots that go out and perform tasks for you, or is the future a world where robots are listening and performing the tasks without you having to ask them explicitly? [00:10:10] Um, and, and this is not necessarily a plug for, for clarify, but like, we think about this problem a lot in the CRM context where, you know, I, like, I think it's actually, you know, Not ideal to take 20 years of history on how sales operates and what sellers are expected to do in a tool and throw that all at the window for an agentic experience where they log into a tool and don't know what the hell to do because, you know, they just see a bunch of random bots doing stuff for them. [00:10:34] My belief is actually it's it's a merging of those two worlds where like you have. The primitives of the old world. So just in the, in the context of A CDP or A CRM, it's like, if you're working in A CDP, you expect to be able to see a persona view of a, of a person, to see their user and the profile attributes to be able to see the events they perform and like there's an expectation that. [00:10:53] There's this mental model for how a CDP operates, and if I were to go into, like, a next gen CDP, I would still expect some of those primitives to exist. Same thing [00:11:00] for the CRM. There's, um, there's contacts, there's companies, there's deals or opportunities, there's tasks. And, and I think, like, sellers expect those things to exist in some format. [00:11:09] Um, so then there's this question of, okay, well, what is the agent doing? Is the agent, are you clicking on the agent and giving it tasks to go perform? Or is the agent just always running and doing the things that you expect? And I think this is where, like, some platforms are betting on more of a generalized experience where you set the agents to particular tasks or you kind of create the workflow. [00:11:29] It's more like a notion or air table like experience where it's like a jack of all trades and you can do lots of stuff. Yeah. Um, but I mean, there's a lot of benefit to saying, actually, let's be very bespoke and specific about what these agents should do. And let's, like, maybe not give as much control to the user, but have them always running in the background, doing the things that users expect. [00:11:47] Because at the end of the day, the tool is very specific. And And I brought up the CRM category, but I think this applies to, like, lots of different industries and spaces where, you know, the more specialized you are in understanding what the user is [00:12:00] doing, you could build a very niche and specific agentic experience that just happens in the background without having you define it. [00:12:07] Um, but that's the bet is, like, are people gonna want that? Or are they gonna want, like, the clay like experience of having a tool that's very flexible and you can kind of create anything you want? [00:12:18] Phil: Yeah, it's hard to predict for sure. I feel like it depends on the tool and the, like in some companies, it's not as complex like the, the regulatory industries and like all the PII data, like those, those companies have access to different tooling. And I feel like there are some certain use cases where I could see myself, you Not having to give specific instructions to a list of agents to go out and do stuff like enrichment, right? [00:12:45] Like new records are created. I already have a process where agents are like enriching those, making sure that it's categorized properly, some of the stuff that you're building. Um, but if we're thinking about like, Longer term life cycle, journey [00:13:00] building, knowing when is the right time to like trigger a discount code email or a push notification that's going to reactivate someone like all of that nuance in the historical data and the propensity models required to try to predict what is the right next best action. [00:13:17] Like that feels a little bit more foreign to me, but. Maybe, maybe we'll get there faster. Um, but I love the call out about Curie and, uh, I watched that video this morning also, and I found it funny that like some of the comments were. It's like, Oh, those recommendations, even though you asked it to be, uh, like in the style of David Ogilvie, they were super shitty. [00:13:36] Like the first one was like, unlock your growth. And like every H one is like unlock, but he was like, that was, that's not the point of it. Like I'm showing like the early. Signs of what's coming. Like, imagine if before I was doing this, I fed it a bunch of context and a bunch of documents and a bunch of personas. [00:13:56] And then I was going out and doing that experience. Like that's, [00:14:00] that's where things are getting a bit more interested where. Yeah. Like you said, like it's more of like an operating system where you're able to let it plug into your life, have access to a lot more data as opposed to just like. The, the, the standard template stuff that you're getting from using your basic LLM today, [00:14:15] Austin: Yeah, yeah. [00:14:17] Phil: I'm curious to ask you about, um, the primitives of martech and GTM. Like, one thing you talked about a lot is that people are getting really hyped up about AI without. Considering how well the tech actually works now, um, plus like could work in the next like five, 10 years, but we're not putting enough focus on the primitives of GTM and martech software and how there needs to be a transition period. [00:14:42] Like we're talking about, uh, agents and a lot of folks aren't even using chat GPT yet. Uh, maybe not less, maybe less than tech, but like, what do you mean exactly by primitives in martech and why do you think it's critical to preserve them during this pace of innovation? Um, [00:15:00] Um, Uh, [00:15:02] Austin: a butchered definition of primitives. I mean, some people are, um, Uh, I would say, uh, not uptight, but like very, very opinionated about what a primitive is. And I think in my mind, for the sake of just describing what I'm talking about, um, I just think there are these core concepts, largely objects, in the martech and RevTech space that define how the systems and tools work. [00:15:34] And if you come from a martech background, it's very obvious in the CDP space. You have users. Um, or people with user attributes or user traits. This is all marketing language or jargon specific to the platform. You know, segment has traits and particle has attributes. Um, rutter stack has attributes. So, like, it's just a definition. [00:15:54] It's a key value pair structure for users. There's a key value per structure for events and events have [00:16:00] names and they have event attributes or event traits. And that's largely the way that programmatic deterministic marketing has operated for the last 10 years. Um, that's the way that CDP platforms are designed. [00:16:10] That's also the way that many platforms connected to those tools are designed. And the reason I think that's important to consider is because unstructured data is really cool. But guess what? Unstructured data is not cool if it has to eventually be sent into a structured format, and you don't have some concept of doing that. [00:16:26] And so the emphasis is not to be like the old guy in the room, like, you know, wagging my finger or shaking my stick at, um, at agentic experiences. It's just to say that, like, I think a lot of companies right now are innovating at the boundary of what's possible, which is really cool. But there will, there will be some time to catch up before. [00:16:47] Um, before that's fully realized. And I think that, you know, one of the stances that we take is that in the meantime, the original, um, kind of data structures of C. D. P. S. And C. R. M. S. Are really valuable. And people are still gonna be operating in that [00:17:00] way. The only case I can see where that's not true is like if you know, A. [00:17:04] I. Progress is so rapidly in the next five years that computers can effectively design their own A. P. I. S. And send data without any meaning any human intervention. And sure, you don't need any data structures at all, because you could actually just store everything in a data table and talk to your LLM or talk to your agent and say, Hey, I want you to give these types of data to this end point. [00:17:24] And as long as both end points have an LLM or an agent on either side of the end point, being able to decipher and structure it. But to me, that seems really far fetched and very far off. It seems like more than a three year adventure. So in the meantime, my, um, my belief is that, you know, some of the best companies are maintaining what's good about old data structures while allowing and importing, um, the ideas from the past. [00:17:49] You know, from magentic experiences. And just to give you an example, it's like, you know, and clarify we have a scheme that you can have on contacts, [00:18:00] but we automatically update fields for you based on on unstructured data. So we allow you to define the structure, but we're trying to take the action out of it by, you know, Updating that schema for you automatically, you know, and for people who use Salesforce, it's like, what happens if Salesforce updated itself based on your emails and calls? [00:18:14] You know, it's like you still define the schema. You're in control. You're structuring the data. You're giving context to the CRM and saying, Hey, these are the things I care about. But then you don't have to do the manual work of just like going and updating fields because it's listening for those fields then and trying to sort things into the right groups and update them. [00:18:32] So that's an example where I think like, Old where old world, uh, schema and like new world automation, I E. A. I. Intelligence is can be really, really powerful. [00:18:42] Darrell: Yeah. Yeah. Great. I think that like what I'm kind of getting. A sense of is it's kind of like one of the age old problems that martech has had for a long time, which is a lot of the stuff that's really going to move the needle is like this unsexy behind the scenes work. [00:19:00] And a lot of, uh, CMOs, a lot of marketers, they just want the fancy stuff. [00:19:04] They want like, you know, real time personalization and they want to push through all channels and that stuff. I think. In the boardroom gets people really fired up, but martech operators like us, we know that you got to fix the data for like, we need to spend like months fixing the data. We need to, we need to fix the infrastructure. [00:19:24] Otherwise, none of this is even possible. And, um, um, I, I, I remember talking to my, my coworker the other day and, and we were talking about multivariate testing and I, and, and, and I, and I told her, I'm ashamed. I was like, Hey, I found this platform. You could do multivariate testing so quick, so easily. And she, and she looked at me and she's like, Daryl, we can't even do AB testing right now. [00:19:45] You know, like, what are you even talking about? And I feel like that's maybe where we're going with, with AI. It's kind of like people want to do the really great stuff, but, but honestly, we kind of need the foundations, uh, first. Um, anyway, you know, we've got to move to the next question. And, and, [00:20:00] uh, Phil and I are, are, have been really bullish on warehouse native. [00:20:03] Um, I think that, that Austin, you, you, you have as well. [00:20:07] Modern Infrastructure Requirements for Marketing Technology Stacks --- [00:20:07] Darrell: I wonder if, you know, would you basically put a stake in the ground and say, like, that's the future, like all the, the all tools, all martech tools or RevTech tools in the, in the future will be built around a data warehouse and all of them will connect, none of them will have databases and they'll just be sort of like activation tools and there's just going to be this single sort of source of truth in five or 10 years. [00:20:32] Is that the tech stack that we'll be dealing with? Or do you have a different prediction? [00:20:38] Austin: Um, look, I wouldn't say it's the future. I think it's now. I mean, lots of businesses already understand that the warehouse first approach or the composability approach to building technology stacks is, um, is the right way to do it. Because eventually, if you grow big enough, you're gonna want control. And that means you need to activate that control to a warehouse. [00:20:58] Having said that, there are [00:21:00] tons of businesses out there where it does not make sense to own and maintain a warehouse. So do I think that tools are going to suddenly stop building databases and having the ability to work outside of a warehouse? Absolutely not. Because there's lots of businesses that grow on platforms that are surprising. [00:21:16] I mean, one of the things I've learned from consulting to so many businesses over the years is that you would come across very mysterious and random stacks. And then you hear the story about how they evolved and it's like, well, some growth. Guy or gal in the first year bought this tool and then the whole company kind of grew around it. [00:21:31] And then before you know it, it became like the central part of their stack. And that's not anybody's fault. Um, it's not necessarily even a bad thing, but I do believe it's going to keep happening because like when you're building a company from the ground up, You're not necessarily considering the long run. [00:21:45] You're just trying to stay alive. You're trying to find customers and make revenue and grow the business and keep people happy. And like your technology stack is like one of your last concerns when you're a 10 person team, you know, with a hundred K and um, you know, and burn every month and 10 K in the bank. [00:21:58] So like, I, I think [00:22:00] that's always going to be the case. Like that's, That's just going to keep happening, but I do think that, you know, teams crave to be sophisticated and they crave to be, you know, operate at the highest levels and operating at the highest levels. Now it's kind of connoted with, um, with operating a warehouse first approach. [00:22:17] And so I think like that is, that is the right approach for most teams. And then when you just, when you just consider like, what are people trying to do with marketing and RevTech? It aligns very closely with a warehouse first approach to a composable approach, because a lot of people are trying to collect event data at the top of a funnel and merge that with customer data at the middle of the funnel, and then activate that at the bottom of the funnel. [00:22:39] And some of the challenges of doing that with an all in one solution is you have a bunch of wires going in every single direction, And there's not a lot of structure and you don't have data control and I can list the litany of other problems with it. But at the end of the day, it's like this tradeoff between control, flexibility, cost and all those other things. [00:22:54] And, and I just think like as you grow, kind of grow and scale, the best [00:23:00] approach is a warehouse approach for most large enterprises. Um, and I think a lot of businesses take on that trajectory earlier in their lifetime and later. And we could have a discussion about is that, you know, is that curve kind of getting shifted sooner into a company's lifetime or later, depending on the size and context? [00:23:15] Um, you know, and I guess the last thing maybe to come back to, which I don't want to harp too much on AI, but like, I do think that we're, we're in this, this, um, this time frame where our concept of a best in class stack is not clear anymore. And it's going to be continually changing. Um, if you go back to 2017. [00:23:34] When I was starting my career, um, you know, around then and the two years before, when I was at branch, it was like, We kind of built what we consider to be a best in class mobile growth stack. And then I saw what was kind of the best B2B stack and it consisted of Salesforce and HubSpot with a bunch of other connected tools. [00:23:50] Um, but I think increasingly now with a warehouse first approach, there is no right answer. There's just like, there's lots of variation. There's lots of way to do things. There are [00:24:00] principles or design schematics that I think will make it easier for you. But, you know, a year and a half ago, Lenny asked me the question on his podcast, like, Hey, well, tell us the golden stack. [00:24:09] And like, I had an answer, but like, I don't really think there's a golden stack. I don't really think there's a one size fit all. Um, I do believe, though, that people are usually pretty silly in their choices for tools, and they, like, repeat the same, you know, they take something from early in their career, and they apply it without context to a brand new situation, which is a problem. [00:24:29] Um, but I don't think there's a best in class stack. [00:24:32] Phil: Yeah. [00:24:32] Historical Evolution of Customer Data Platforms and Composability --- [00:24:32] Phil: I feel like your perspective on composability is super interesting, Austin, because you were essentially at mParticle, a CDP, right around the time where composability, reverse ETL tools like Census and Hightouch were hitting the mainstream. Or was that like a couple of years before that happened? [00:24:50] Bring us back in house, uh, with like a mParticle Michael Katz days where you guys were like thinking about package versus composable CDPs.[00:25:00] [00:25:00] Austin: I joined Particle in 2017, and I think Hightouch and Census really didn't hit mainstream until 2020. Um, and, um, and I, I remember distinctively, though, when I was working with Postmates, they were doing effectively what we're doing today, but it was way harder and used really complex tools to do it. [00:25:18] Um, you know, we, Postmates, for example, was streaming data from their CDP back into their warehouse, and then they had a DAG running. To pull that data back into Braze and other places, and it was super messy. It was all done in code. We had a team of like, you know, five data engineers. Um, and, and so I think like the, the main thing I've seen come out of that reverse ETL, uh, revolution is that it's just, it's way easier now. [00:25:43] It has never been, easier to move data around your data stack than today. And I think that's only going to get easier with time. Uh, you know, yeah, you still have to have at least one data engineer. But I think, again, if I think back to Postmates, it was like a team of two to three plus and no visibility for marketing and no WYSIWYG [00:26:00] tools and no auditing and SQLs in lots of different places. [00:26:03] And there's like so many problems that I think are solved by, the reverse ETL category. Um, but what's what's fascinating about it is, you know, at the time, 2017, a CDP was defined by segment and mParticle And it was like a tool that collects data, federates audiences. Um, and, uh, and that's kind of it. [00:26:20] I mean, you could argue that they also had the ability to, like, roll SDKs. But anybody who's worked with segment or M particle knows that that's a little bit of a misnomer because, um, They have cloud SDKs, and then they have client SDKs, and they're not the same. Um, and, and so like, technically speaking, lots of tools are CDPs now, because they have the ability to collect data, they have the ability to federate data, and they have the ability to create audiences. [00:26:41] And audiences, I would largely say, are like, um, kind of table stakes for most tools now. Like, you can just create a list of users in almost anything, and either export it or send it somewhere. So, uh, yeah, I mean, my biggest reflection on that time is just like, the category of a CDP was so innovative, But it was fascinating how quickly it became monopolized by [00:27:00] like every other category and at the same time that that was happening Lots of people were doing this without necessarily entering the CDP market because there was there's a period of time in like I think late 2019 we're like it was very confusing what a CDP was. [00:27:14] Nobody really knew Um, companies that I would classically call like marketing automation or marketing capability tools were calling themselves CDP because it was a wild, wild west. There was no definition. It was lots of things. It was none of these things. Now, the way that I like to describe it to people is like a CDP isn't a category of tool anymore It's a collection of capabilities, and you can have those collection of capabilities spread across the entire stack. You can have them in one tool. You know, Braze can help you collect data and federate audiences and import data to your warehouse. So it could be a CDP. You could collect data in a traditional way with a tool like mParticle or Segment, and then you could federate audiences with a tool like Census or Hightouch. [00:27:54] Or you could use a tool like Census or Hightouch as both your data federation layer and your CDP. CDP [00:28:00] Um, so I think there's like lots of possibilities there. Um, and yeah, I certainly didn't predict it in 2017, that's for sure. [00:30:11] Foundational Technology Stack Decisions During Early Company Growth --- [00:30:11] Phil: I'm curious to get your take on how you've taken those learnings now from being in house, but also on the agency side, consulting, advising all these companies, seeing all these stacks, having different tastes of different setups. Now you're building your own company. And, um, not only are you building the tool itself and how that's being built, but the internal stack and having that. [00:30:33] The decision now in the early days, you know, like you talked about, like having to join a company and dealing with like, um, artifacts of like ghosts of martech's past people who like left the company, use this tool and like, everyone's just using it now, like you got to make that choice in the early days. [00:30:48] So yeah. Talk to us about like some of the early decisions that went into like the foundational stack when you were building this new product company for the first time. [00:30:57] Austin: Oh, man, I, uh, [00:31:00] I feel like it was a deeply humbling experience, to be honest, um, largely because what it taught me is that, poor decisions aren't made intentionally. You know, I spent a lot of my career like evaluating stacks and helping people improve their stacks. And I always thought it was like, Oh, man, like these people just didn't know what they're doing. [00:31:21] And I think a lot of people do know what they're doing now. In hindsight, it's just that. Building your stock in the early days is not a priority. And I know that's not what our industry wants to hear, but it's the truth. And I actually think like that's, um, it's important context as you navigate, um, martech as an early stage operator is like the most important thing at a series, a series B company is staying alive and making money. [00:31:44] And how you do that is completely up to the business. And you have to thread this needle between architecting a best in class solution that's scalable and flexible. while also being like well tuned into the fact that like your company could die tomorrow. And, [00:32:00] um, and the other thing that I've learned too is like oftentimes stacks are built based on, um, on usually the choices of one or two people early in the company's lifetime, whether that's the first growth engineer or the first founder or the first consultant, somebody comes in and just makes a decision. [00:32:15] And that usually sets the company down a course. And, um, and you know, like I, I have my own opinions about like what tools I want to use and why. And a humbling experience I've had to clarify is like, I'm not the only voice in the room. One of my co founders, Patrick Thompson, built iteratively, which he sold to, um, to Amplitude. [00:32:34] He is a well respected data leader. He knows the CDP space extremely well. Um, another member of our team is a guy named Ashish Pandey, who, um, has founded his own two companies and has used all these tools himself and is like a classical growth engineer. So like, I'm not the only one with opinions about what's right. [00:32:51] And so I think, like, that's where, um, you know, you also just have to have, I guess, the, uh, the patience and tolerance to let [00:33:00] things play out. It's like, look, you're going to choose a tool and it's going to work out or it's not. You're going to figure out how to build around it or it's not. And I think what's far more important than the tool you build is maybe just, like, the patience and understanding and decision making to course correct as the company grows. [00:33:14] And so, you know, we, we haven't necessarily followed a lot of the principles of an enterprise grade startup because we don't need that. We're connecting lots of tools in kind of jerry rigged ways because that's actually more important for me. I want to be able to connect and disconnect tools quickly. Um, I talked about this in the martech class, you know, like, uh, the Frick framework and flexibility and redundancy and interoperability, um, and coupling. [00:33:37] And I think like, As an early stage startup, you're willing to sacrifice on a lot of those principles, because what you care about is the ability to change tools quickly and operate. If you, if you enter, you know, an early stage startup or even a medium stage startup with the idea that, hey, I need to like choose the best in class tools and these aren't going to change for two or three years. [00:33:54] And I got to like set the order by which I pass data. It's like you're putting all this process in place when things are going to change in six [00:34:00] months. So I think really you got to be attentive to the moment in time when those things start to matter. And frankly, They don't start to matter until you hit scale. [00:34:09] They don't start to matter until you cross 5, 10 million dollars in ARR. Before then, you're just trying to stay alive. Um, so, so that's, that's been like, um, um, I kind of like, I knew that as a consultant, but to feel that now as an operator of my own company has been a really humbling experience. [00:34:26] Darrell: Yeah, 100%. That, when you said, I'm not the only voice in the room, that, I think, resonated with me a lot. I, I, uh, I can't share when this happened, but we, we at my job spent, like, I would say three, three to four months picking like the perfect tools to, to, to run our tech stack. And right at the end, and we're talking about business case, vendor selection, all the demos, and, and then, and, and just months and months of work. [00:34:56] And then at the tail end, the executives came in and just said, Hey, we're [00:35:00] actually going with this other platform. And it hurt everyone on the team just felt it right in the gut. And, and, you know, I think it hurt for a while, but then. Then, like you said, you kind of find a way to just kind of move on, and, and what's really interesting, or I think what, what, what I found, and what, what, what makes me think of this when, when you said that, is, is kind of like, this is what being a team player really is. [00:35:25] It's all about like, if you're, if you're working by yourself, things are, are much more simple, but we're never working by ourselves. Like it's business is a team sport and this is how you play. And it, and it's, and it's a, it is a very humbling experience. [00:35:39] Transitioning Leadership Styles Through Organizational Growth --- [00:35:39] Darrell: I have a personal question, like kind of a personal question, but you know, you were more of like a martech leader, technology team leader in the past. [00:35:48] Now you're like the founder. And, and co CEO of a company, like has, has the way that you worked changed? Like, do you find that you you've had to like [00:36:00] change the way that you do things? Or is it very much the same with just a different flavor? Like, what's your experience moving now into like founder? [00:36:07] Austin: you know, maybe this, this piggybacks a little bit on what you said before. Um, there's like a, I don't know who this is attributed to. It might be a proverb, but it's like, If you want to go, uh, if you want to go fast, go alone. If you want to go far, go together. And, um, and, uh, I think particularly in technology spaces, martech, RevTech, Operational Tech, IT Tech, um, applied engineering to operational roles, like that is a very incredibly succinct and important, um, mantra to carry with you because there's lots of times I think depending on a company's size and stage and the role you're in. [00:36:46] Where it makes a ton of sense to go alone, like you're trying to go as fast as possible. You make the best decision. You move forward. You kind of, you take a scorched earth approach to building and and that's, that's great. But particularly [00:37:00] for more collaborative parts of the organization or ones where there's risk or ones where there's not a clear answer. [00:37:06] Being right is not the outcome. Actually getting people aligned to the outcome together is far more important. And, um, And I, you know, I think that is actually a lesson that I've had to learn maybe a little bit more harder than I would have liked over the years, is that Um, there's usually not a right answer to a lot of things in business building. [00:37:24] There's just, you know, there's a feeling and there's an, there's, I think of it a little bit like a, um, if you guys ever seen the Kappa model, it's like for the optimal portfolio, it's basically a line that shows you how much your risk and reward is. And you kind of, you want to maximize the amount of. [00:37:41] Return you get while minimizing the amount of risk. And there's a tangency line, which is your kind of your return. I won't go into finance here, but, but the point is there's, there's like an optimal line of risk versus reward. And I think like a lot of people think very critically about that as like, Oh, well, there's an optimal outcome for most choices in life. [00:37:57] And I think like, unlike the [00:38:00] tendency line, unlike the optimal, um, You know, portfolio or the or the, you know, the frontier is, uh, there are lots of optimal returns or optimal outcomes that have low risk that you wouldn't see unless you work with other people. Um, and and and so I guess my my my punch line here is that as I move from being a martech operator to now being, uh, you know, founder. [00:38:24] I would say more than ever. I feel much like a product manager. And actually, this is a point that we didn't talk a little bit about in our pre dialogue. But like, I think martech and revtech at at the most technical level is a specialized form of product management. It's specialized because it's way more complicated. [00:38:42] Um, no, dis that all the product because product is a very specialized, concentrated and complicated role, but there's this element that is not recreated in product, which is called working across lots of teams that's forced upon you in a lot of organizations. The beauty of being a product is like you have a little bit of an elevated role and you can, [00:39:00] you can set direction under the guise of product management. [00:39:03] But I think particularly in martech, it's like you have the challenge of being a product manager while also catering towards multiple customers. Both your internal customer, your external customer, your marketing team, your CMO and engineers. And I think that extra piece, the marketing piece, as a martech leader makes it really complicated. [00:39:21] In the same way for a Rev engineer or a RevTech leader, you know, you have the same complexity. You're managing engineering resources, you have this customer, which is the sales org, um, and then you're building stuff at the same time, and you've got to keep the, the organization afloat. And, and so I think that, um, this experience has, has forced me to be, you know, a much better product leader and to think of my role and myself in a product leadership way more so than I think any role in the past. [00:39:49] Darrell: Yeah, one thing I'll just add to that is that I think that one thing that I've learned the hard way is that when you become a leader, martech or, [00:40:00] or a company leader, you find that you actually have a lot less authority than you think. Like, like you, for some reason, people think before they get into a leadership position that once you're there, you get to make all the calls. [00:40:13] And it's just not true. You know, you, you have, it's kind of like, you know, there are, there are other constraints that you have to deal with and people are, are one of the biggest ones. Um, [00:40:23] so [00:40:24] Austin: like a lot of people also, um, Uh, figure it out when they get married as well. [00:40:31] Darrell: totally. I like, uh, yeah, yeah. I just, [00:40:34] Austin: So if it doesn't happen in their job, it will definitely happen in their personal life. [00:40:38] Darrell: No, it does. It does. But I will say like, you know, we're, we're kind of, you know, shitting on it right now, but [00:40:43] Collaborative Decision Making Approaches in Technology Teams --- [00:40:43] Darrell: I will say one, one wonderful experience. And you probably both of you probably felt this is that even though it wasn't your way, when you co create it with somebody else, it's very rewarding to see it actually turn out better than what you initially envisioned. [00:40:58] And that I think is the beauty [00:41:00] of, of collaboration. And just like you said, you know, if you want to go, you want to go far, go together. Um. But, uh, go ahead, Phil. [00:41:07] Austin: Well, real quick. I mean, your, your point is so important too. It's not only that the outcome is better and you feel good about it, but it's also an incredibly great way of hedging risk. And I don't think a lot of people understand this, but like if you barge into a room and make a decision, you're fully responsible for the outcome. [00:41:24] And if it's the wrong choice, you are screwed. Um, now again, this is not a game of blame and great organizations lean into failure and learning quickly. But one of the things I like about collaborative approaches is there's a little bit of a hedge here. There's this belief that, hey, if we don't make the right choice, we made the wrong choice together, and there's no blame involved. [00:41:44] We can learn and move quickly if it wasn't the right tool. And I agreed with you. And I said, Hey, like, we're just going to move fast. Let's make the right decision. It's kind of easy. And there's no tension or activation energy to unwind that position and go make the right choice. Whereas if you have a really tough stance on something and you believe you're [00:42:00] right and you dig in now, it's really hard to unwind that. [00:42:03] Um, and so it's also just maybe a cautionary tale to a lot of people. young operators out there is like, I think there's a lot of risk and having strong, strongly held opinions that you're unwilling to unwind because you just did yourself in a ditch where ultimately, again, if you, if you have the belief that there's lots of different stacks that are available to you, then like go with the flow and see what happens. [00:42:22] You might be surprised. [00:42:23] Phil: Yeah, such a cool point. And just maybe think of one thing that you said in Lenny's interview. [00:42:28] Differentiating Leadership Qualities Within Technical Marketing Operations --- [00:42:28] Phil: You likened martech to a game of persuasion. Like on the topic of, uh, Collaboration and gamesmanship, right? Like martech folks are a lot like quarterbacks. I think everyone likes to make that analogy that every team is the quarterback. [00:42:43] But, um, I think it's just totally true with like, even what you said about the role of martech folks being a lot more like. Product managers and having to translate stuff between different stakeholders. I'm curious to ask you on that point, like what advice would you give martech [00:43:00] leaders or even like practitioners that are coming up in their career, um, who are trying to coordinate across teams and like call these plays and the constantly changing fields with AI and everything, like in your experience, what separates. [00:43:13] A good martech quarterback from the great ones. [00:43:18] Austin: Well, I think like in any role, having respect from your peers in your area of ownership or domain is the number one thing. If you're so in marketing technology, this is one of the reasons why I preach so often that, like the best martech folks out there are technical in nature, or they are interested in increasing that side of them, because I think that if you can't walk into a room and hold the attention of engineers alongside your CMO at the same time, you're, you're going to be in a tough position. [00:43:48] And so I think, like, the first thing everybody should do is say to themselves, how do I be the best, most technical? Version of myself. I can't persuade engineers. And now how can I also be the best, most [00:44:00] creative version of myself so I can persuade marketers? This is obviously from our tech. The analogy goes for revtech in the same way. [00:44:05] You know, how can I be the most technical version of myself to prove to people that I can hold conversation with engineers and product managers? And how can I also be like a very persuasive and good seller? to convince the CRO of why I think a choice should be made. Because oftentimes like the CRO and CMO are thinking the same way. [00:44:22] They don't often have a very deep technically nuanced understanding of systems, tools, technology process. They have an understanding of results. And, you know, here's an example from RAMP. I remember having a lot of conversations with our head of growth, um, around like SQL pipeline or the amount of sales qualified lead pipelines that we had. [00:44:42] And there'd be sometimes where like system outages Break our ability to ingest leads. And even though the leads like weren't lost, I'm actually remember this very distinctly. Like, even though the leads weren't lost, there was a reporting problem that would eventually trickle to our CEO, Erik. And I remember going through this with our head of growth. [00:44:57] Like I was trying to always explain like, Hey, [00:45:00] it's okay though, because the leads are not gone. They're still there. It's just like, there are, They're just not being tracked because something broke, but his point was like, I don't fucking care. Like it's it's still on the sheet and I need to ensure that these people are getting into our pipeline that they're getting demo calls. [00:45:16] Um, and if, if how am I supposed to, how am I supposed to have confidence and explain to our CEO that our systems are working when like, you know, 100 leads are just missing every month because of a system problem. And so that's also an example of like, you have to be willing to understand both sides of the equation. [00:45:31] You have to understand what the priorities of your CMO or your CRO are or your head of growth, wherever you're serving. And then you also have to have the understanding of the engineering side, because I do think like I was able to persuade, um, you know, him at times about like how there wasn't a problem. [00:45:45] And the engineering. basis for those things was useful, but it wasn't always as useful as being able to empathize with his concerns and be able to alleviate those. Um, so that's kind of the first piece. Um, the, the rest on collaboration is just [00:46:00] like, you know, you have a lot of different stakeholders. You have so many people who have varying degrees of technical expertise, varying degrees of understanding about the stack. [00:46:08] So knowing your audience before you talk to people is also a huge differentiator between good and great. Um, a good martech operator will. kind of talk in deeply technical terms with engineers and semi technical terms with everybody else. Um, a great martech operator will, um, be much more nuanced than that. [00:46:26] They will be extremely technical with engineers and they will catch themselves from being overly pedantic or, um, engineering in, in kind of voice and tone and scale with non technical operators like growth folks and marketers and CMOs and content writers. Um, and they're able to wield their knowledge of tools and technology in a way Not just to, like, you know, regurgitate random bullshit to people, but to really persuade and bring them along in the adventure and educate. [00:46:54] Um, that's why I often liken, like, a lot of the job of a really cross functional [00:47:00] operator in RevTech or martech is actually just an extreme educator. Like, you are an organizational educator. [00:47:07] Darrell: Yeah. I think too, like what I'm hearing is you really need to strike that balance between being able to communicate technically and then also being able to, to communicate to the business owners or to the, to the business stakeholders. Um, if for marketers, it should be creative maybe for, Salespeople or CROs has to be more revenue, revenue driven or revenue centric. [00:47:31] But I think that it's so, [00:47:33] Implementing Continuous Feedback Systems for Professional Growth --- [00:47:33] Darrell: it's so easy for operators to index over index one way or the other, you know, and I think that one of the only pieces of advice probably that I can give to the listeners, you'll, you both will probably agree with this is you, you kind of need to get feedback from people that you trust that'll give you that direct feedback. [00:47:53] In almost no circumstances will someone sit you down and go, Hey, you know, you're the perfect balance of technical and business. [00:48:00] I'm amazed. You know what I mean? So like, like, and, and I'm, I'm, I'm obsessed with the concept of blind spots for a long time. And, and it's just the concept that you just don't know. [00:48:09] That you're, you're off course, you know, and, and the only way, unfortunately, unless you like do a lot, a ton, ton of reflection is, is to get that feedback from other people, um, your, your coworkers or executive coach maybe is always, I think a good idea. [00:48:24] Austin: Oh, I mean, I ramp the first six months and every six months after that, I sent out what I would call a customer survey, which is, you know, to growth, growth, engineering, marketing, content, engineering. I'd send a survey and say, like, how are we doing across a wide variety of categories? Like, do you? Do you feel like the organization is better because we're here? [00:48:45] Have we made your lives easier? How have we helped you? How have we not helped you? Where, where's an example of something we did really well that you think benefited the organization? Where's an example of where we're a huge pain in the ass and you thought our process was stupid? Um, asking those tough questions is how you get better. [00:48:59] Um, [00:49:00] treating your peers as customers is really hard. It can be a little bit of a selfless odyssey. Um, but it's one you have to go on if you're really bent on being the best. [00:49:10] Darrell: agreed, [00:49:10] Technical Literacy Requirements for Effective AI Collaboration --- [00:49:10] Phil: would you add to your answer on like what makes a really good martech or RevTech operator? If we like harp on AI a little bit here, like what has AI changed in your opinion? Like you just said, like someone needs to be really good to creative side for the CMO, the technical side for the engineers. I feel like LLMs have bridged some of that gap on the technical side. [00:49:34] It is easier to pick up, uh, different coding languages and being able to like, um, translate some stuff and speak more eye level, but like what in your opinion has like AI been able to do to, to level set that and, and, uh, from like an operator skillset for martech? [00:49:52] Austin: gosh, so much. Um, and I, you know, I, uh, I kind of tell every person I come across now who's starting [00:50:00] their career. Like one, you should go get like a minor in software engineering and two, you should be using AI for everything you do. Even if it seems trivial because you'll find [00:50:10] Phil: Hmm. [00:50:11] Austin: some learning. [00:50:12] It's it's much like every other tool You have to learn what each LLM is good at how to give it information How to structure workflows to maximize the output for minimum amount of time And I think that if you're not doing that you're going to be left behind Specific to our kind of industry though. [00:50:30] God so many examples. It's like I used to go into Um Chrome tools and, like, write a little mini script to scrape website data. You don't have to do that anymore. You just go into OpenAI and say, Here's the HTML. This is what I'm trying to extract. Give me the script. Copy, paste into Chrome tools. But, again, you need at least a minor or, like, a little bit of knowledge in how software works to be able to, like, right click, inspect element, go into the console, and paste a script. [00:50:58] Like, you have to know how to do those [00:51:00] things. Now, In theory, OpenHack or, or Claude can teach you how to do it if you don't know. But you need some starting place to be able to piece those things together. So I think like, Taking things that would have taken in the past 5, 10 minutes, 15 minutes, and just doing them in 30 seconds in, um, you know, in GPT or CLOD should become an instinct. [00:51:21] And then I think the next thing is, like, effectively trying to spin together or piece together workflows that would have taken a normal person 5 hours, 6 hours at a time. That you can now do in an hour or less. I'll give you a great example. Um, when I first started at Branch, I wrote all of our case studies. [00:51:38] And I actually did a podcast at Branch. This was back, I'm probably still on the Apple store. I would be embarrassed if you listened to any of those. Uh, it was such a bad podcast, but I interviewed like Casey Winters and John Egan. This is back in the days. We're all young ones. Um, and it was before podcasts were really popular. [00:51:56] And I remember like cutting all those podcasts, taking like six hours at a [00:52:00] time. Yeah. We had a recording studio. This was long before DSL cameras were like the standard and all that stuff. And, but the point was, is like, content generation and curation and publication is a very manual experience. It does not have to be, though. [00:52:15] With LLMs, you can get 80 percent of the value very quickly. And then use that 20 percent of time an hour to make it your own. And so, as an example, I clarify like we, we've done all of our case studies with AI assistance. I mean, we will sit down with our customers and have an hour interview and talk about all the problems, talk about their feedback, the things they love, they hate, and we'll take that transcript and give it to Claude or somebody else and give them a very clear prompt that we've solved. [00:52:41] Kind of tuned over time, and it puts out a really good case study of exactly what we talked about. And so we've taken the production costs from 6 hours down to 1. And that's just 1 example where. I think a good operator, regardless whether you're a martech operator or a RevTech operator or an Ops operator, you should constantly be thinking about what are the [00:53:00] things that are taking time in my day, and how can I make those easier with the use of this assistant? [00:53:04] And again, back to the start of the conversation, that's what excites me about the future is that we will get to a point where you don't have to go into GPT to get help. It's just listening right there natively, and you can probably just talk to it and it can take control of your computer and do the things for you instantly. [00:53:21] Darrell: Yeah. I mean, here, the, I agree with that. And I think that especially right now, what the, probably the prime opportunity for AI is to accelerate, you know, um, time to market time to value and all the things that you, you don't want to do. I think the risk. And I think I feel like I'm one of the AI skeptics out there. [00:53:41] I think the risk is, um, Um, you know, I, I've said this before, Hey, a company has a couple of crappy blog posts on their corporate website, right now with AI, they're going to have 100 crappy blog posts on their website, you know, and that's my fear. And I'm [00:54:00] very much in the camp of, you know, I'm, I'm, uh, [00:54:03] How to Use AI for Writing Without Losing Your Original Voice --- [00:54:03] Darrell: I'm a big fan of Ryan holiday. [00:54:04] I don't know if, if, if, if, if you, you both know him, he's an author and he said that, you know, the, the, the hard thing isn't writing. The hard thing is having something to say. And I've always thought that that was, that was very true. And I think that the danger for marketers out there. Is, is thinking that AI is just going to do everything for them and just put out a lot of stuff where in reality, what they really should be using AI for is, is to improve their strategy and to learn about their customers more and to, to, you know, surface details that we just takes us too long to try to understand, um, is kind of my hot take on there. [00:54:46] Austin: Oh, I mean, I agree. Like, um, in the example I provided before, you know, what role is the AI agent serving? It's serving in the synthesis and manual work of taking a bunch of bullet points in [00:55:00] conversation and structuring that in a way that makes sense. Now, if you're silly, you just go and publish without reading it. [00:55:06] In reality, again, it's, it's not good enough to really pass the, the sniff test without a human, um, editorial review. But, I would argue, the hard part is not, Um, uh, is not the editing. The hard part is getting things down to a state where you can edit it. When I think about my own writing, because I was, you know, I was writing manually without LLMs for a long time, I would sit there and stare at the page and think about what I want to say. [00:55:30] Now I feel a lot more confident as a writer, because I can spew everything that comes to mind, and then reread it and structure it into groups, and I don't have to think about As much a wreck. Like, what is the exact sentence and verbiage that I need? I just need to get the main points out. To your point, Daryl, it's like, that's where the creativity, what you have to say, becomes so much more meaningful. [00:55:50] Because if you give an LLM garbage, it's going to give you garbage out. But if you give the LLM actually real, meaningful points that are tactical with a lot of context, it's going to [00:56:00] produce something pretty good. Um, and I mean, we could also talk about scaled SEO at some point. Like, I think that's also like a completely different topic because. [00:56:08] You know, I would argue that like, the reason why websites are producing a lot of bad content, um, is not necessarily to create readability, it's to get eyeballs and like, That's going to be a big problem for Google. Um, and everybody's doing it. So, you know what, do you take the moral high ground and say, I'm not going to do it because everybody else doing it? [00:56:26] No. Well, [00:56:27] Phil: no, it's such a great point. I love the case study example there, the customer story, taking the transcript, putting into something that's a bit more polished to exactly what we do with our transcripts from, from the podcast episodes. Uh, I have like a year plus of like the, the prompt that I use in GPT to tweak that, throw it in mid journey to have like nice header images for each of the questions in the sections. [00:56:49] So a lot better still than just being like. Here's this problem that we solve for this customer. Write me a case study about it. Like that's going to be total garbage compared to here's a [00:57:00] transcript of the questions that I asked. And I go like question by answer question by answer. And so the output still requires some editing. [00:57:07] It's still filled with unlock and em dashes everywhere, but it's still better. For sure. Um, We're getting close on time, Austin, really appreciate, uh, your time. I feel like there's a bunch of tangents we could go down to. [00:57:19] Reimagining CRM Through Modern Automation --- [00:57:19] Phil: Um, I did want to ask you and give you a chance to, to, to plug clarify a little bit here. [00:57:24] Um, I spent a few years at close. io, a bootstrap fully remote team building as CRM for SMB, uh, sales teams. And during my time there, I was exposed to a sea of CRM tools, uh, lots of verticals, uh, for CRM, like. CRM for real estate, CRM for agencies out of all the freaking categories you could have picked in martech. [00:57:45] Why a CRM Austin? [00:57:50] Austin: is one of the largest categories of SaaS software on the planet. Um, so, uh, there's a lot of big numbers at play, which is like, you want to build in a big space because there's a lot more [00:58:00] opportunity to have a big win. Um, so that's just like the, uh, the financial operator in me. Um, but, but really the reason is, is like. [00:58:08] So my co founder and I, Patrick, we, we both spent a lot of time in the CDP space and we spent a lot of time in the serum space and it felt like there were these competing forces for the same tool. I think the, you know, what happened with CDP space is interesting. It's like segment rose to fame as probably the best CDP. It got sold. Quality went down and particle really took off. Other competitors came in. Uh, then the, uh, the capabilities that we talked about before kind of became, uh, I'm commoditized across the industry. So like what it meant to be a CDP collapsed at the same time that no real winner emerged. And so I think like now the CDP space is kind of not dead, but it's it's dormant. [00:58:52] It's like it's it's a collection of of of capabilities, but those have not really moved anywhere to like [00:59:00] they just kind of like kind of blown apart into random other tool categories. But we haven't seen a full fledged migration of what a CDP is to something bigger. And at the same time this is happening, I would argue that even though there's great companies like closed and copper and pipe drive and there's audio and folk, there's lots of good CRM companies. [00:59:19] Um, and I say that because like I'm a big believer in positivity in this space. And I think there's a lot of room for lots of winners. And I also just believe that you get out of the world of what you put in. And so I never want to, um, bad mouth, any, um, Any of the people who have built products besides ours, but there's there's a lot of space for innovation there. [00:59:36] I don't think any CRMs are really considering what it would look like to have an event stream layer embedded inside of a CRM. HubSpot might be the only one, but I think that was a happy coincidence, right? They built a marketing technology tool. Um, for emailing people which had to collect event data and then they built the CRM and they kind of put these things together over time. [00:59:56] It didn't really even come out with support for event data until about eight [01:00:00] months ago. Um, at Ramp we were trying to send segment data to HubSpot. You could send like the event name, but you couldn't send the event attribute. The payload would just be nothing. It would be like a nothing burger if you did that. [01:00:11] And, and so that's really what, uh, Inspired me was to think, like, what if you could combine multiple spaces into one single product that served marketing and sales teams and revenue teams and technology teams and maybe in the future success teams, and I think alongside, as we're building this, the dream for an all in one complete CRM CDP solution, we started to understand how I could help with automation. [01:00:36] And so, like, one of the, you know, one of our mantras is we're here to help our customers save time by removing. The manual work of data entry into these tools, and we're here to help them build better relationships. And those two things are related. If you're not spending all your time manually entering data inside your CRM, which is sellers and account executives and salespeople and rev ops people spend 90 percent of their time, rev percent of their time entering [01:01:00] data. [01:01:00] But salespeople spend 30 percent of their week, 40 percent of their week, according to Salesforce, entering data inside of their CRM. So if you can take away all that time, automate their lives by being smart, ingesting data from their calendar and their email, updating fields for them, giving them summaries, providing them notice notices of when they need to follow up with people, you automate all that away and you give them back time to then do the fun part of the job, which is having conversations with people. [01:01:26] learning, helping people, supporting them on their journey. Many of the things that I like love as a founder, I feel like a lot of sales people naturally gravitate towards. Um, I mean, actually some of the best sellers I know act like mini founders. They treat their customers almost as if they're like their, their best friends. [01:01:42] They text them, they're on WhatsApp. They know their, their problems. They know the revenue of the company. They're at dinners together. And I think that's what good sellers want to be spending all their time doing. But we have these machines that are making us spend all this time with data entry. So I think, I think that like that [01:02:00] really was the inspiration or the dream for Clarify is to build a system that really functions in the background. [01:02:05] It's an automation of your own brain. It has the context about your calls and your emails. It makes it really easy for you to follow up with people and to do the next step. And it removes all that manual data entry. And I think that's like, probably what's unique about the space and, and drove me to it is, is like, That opportunity in general. [01:02:22] Um, and then, of course, the long term vision of building an all in one solution that combined some of my experience and love of CDP into a CRM is, um, it's certainly like an interesting part of it. [01:02:35] Phil: cool. Awesome. I appreciate you sharing that. We'll definitely link out to the site. Um, if folks want to check it out, uh, I have it on my list to check it. I don't have a CRM yet for, for the podcast. I'm wearing a bit of a sales rep hat these days, uh, myself. So look into a level up for that. From, uh, the Trello CRM board that I have right now. [01:02:54] So I'll give it a spin. Austin, uh, we've got one last question for you. You're a founder, obviously a [01:03:00] teacher, a martech practitioner. You're also a husband, a dog, dad, a student getting another degree. Uh, you're also a water skiing fanatic and avid runner, a notary, an ordained minister, a certified financial planner, and a drone fanatic, honestly, I don't think we've ever interviewed someone with water skiing. [01:03:16] More hobbies than you. You also trained for nine months recently, uh, to do an Ironman and marathon, uh, while going to school and running a new company like this must have come with a ton of sacrifices. Obviously. Uh, one question we ask everyone on the show is how do you remain happy and successful in your career? [01:03:33] And how do you find that balance between all the shit you're working on while staying happy? [01:03:40] Austin: Well, first of all, I'll caveat anybody listening that, uh, I did a lot of those things in COVID and COVID was wild time. So if you survived COVID with any semblance of your sanity, you know that. Maybe picking up too many hobbies was the norm like mine just wasn't bread baking which I feel like half of our generation did So, um, yeah, I [01:04:00] mean like the first thing is I I am very intellectually curious. [01:04:04] I Like I feel like I always like to learn things and try new things and pick up skills And so a lot of the pursuit here has been Um, just for who I am. You know, I just like to learn things and I think it's fun. Um, and, um, as it relates to staying happy, uh, you know, I'm just such a big believer that all things come back to your, your mental health and your physical health. [01:04:32] Um, so, you know, getting enough sleep, having relationships outside of work, not taking yourself too seriously, having time to reflect, um, working out regularly. Uh, having a life outside of work, having games you play, and friends you have, and hobbies, like, in my mind, those are the things that are the foundations of a happy life, and I do feel like in my 20s, I spent a lot of time in [01:05:00] pursuit of other things, and I always told myself I would get to them, and, That's true. [01:05:06] I'm starting to get to them, but it did come at a cost. I mean, there were a lot of days in my 20s where I, you know, kind of look at myself in the mirror and not be happy with the life I was creating because I was so singularly fixated on my job and my career. And, you know, the work I was doing for clients and money and all these things and kind of get in the way of what's obvious and in front of you. [01:05:29] And so my advice to people is, is actually pretty simple. It's, it's just what I said. It's like, take care of the basics and the rest will take care of itself. Um, and, uh, and yeah, um, as it relates to sacrifices, cause you did mention that, like that is a key part of it too. Um, I've learned a really good lesson from my co founder Patrick, which is to like view a lot of decisions and outcomes in life just as trade offs, um, because at the end of the day, that's what a lot of stuff boils down to. [01:05:59] [01:06:00] Whether you do an experiment or not, whether you build something or buy, whether you, um, hire a new team member or not, whether you're able to achieve a goal for the year, everything comes back to kind of a mental calculation or sometimes a mathematical calculation of what are you trying to achieve and how much time do you have and how do you make that equation balance. [01:06:16] And I think a lot of people are just unwilling to confront it. They're unwilling to balance the ledger. They're unwilling to say like, Oh, I can't do these things. And so increasingly I've just, I've kind of accepted that in order to pursue the things that I care about, it's going to come with trade offs. [01:06:32] Um, and a really great example of a trade off that I make all the time is like, I have a non negotiable of trying to go to bed at 9, 9. 30 every, every night because I have to wake up at 6 to be able to clear my inbox, to be able to go to the gym, or do the run, and it, it seems so obvious, and I'm not like touting that as some, um, you know, impressive thing, it's just like, It's a math equation. [01:06:55] You know, I can't sleep less than seven and a half hours and be a functioning [01:07:00] human. So if I want to achieve my goal, if I want to be able to run a marathon one day and I have to run six miles tomorrow, I'm not gonna be able to do that without sleep. And I think just a lot of people are like unwilling to confront those tradeoffs, tradeoffs like that. [01:07:12] Um, and I think that somehow they can magically create a world where they can have everything they want without making the tradeoffs. And so, you know, work backwards from your goals, make the decisions you need. To get there and, um, and be willing to set some non negotiables. [01:07:26] Phil: Such a great answer. I saw Daryl, uh, shed a couple tears there, uh, for the, the, the sleep points there. Daryl is [01:07:33] Darrell: Dude, yeah, [01:07:34] Phil: month old right now. Uh, what, how many, how much [01:07:36] sleep [01:07:37] Darrell: well, I'm [01:07:38] Phil: now, Daryl? [01:07:39] Darrell: Oh man, it's, it's like getting worse. But I, but I agree with Austin. Sleep is a superpower that people don't, for some reason they just don't get it. And that's why I'm, I'm hurting so much because I have a, I have a 10 week old. Um, but I, I, I know we're over time, but I will say too, like, uh, Austin inspired me to, to, to share this. [01:07:59] I was [01:08:00] just reflecting on this. And, um, one thing I think about happiness is like, if you is doing this mental exercise of, if you imagine, You get all the things that you want. You sell your company, you retire, you know, you, you build a great business or whatever you, you achieve the marathon, let's say you get all that. [01:08:22] What do you do tomorrow? Like, what do you do the next day? And I think that that's such a fascinating question. When I started to think about that and I was like, Holy crap, like I would probably go play golf with my family and spend time with my wife and my son and, and like play some games or something, and those are things you can do right now, and, and I, I, I, well, when I, when I started to think, reflect on that question, I, I found it very peaceful, you become very peaceful when you think, when you think that way, because the things that you, you want, even the things that you're chasing, even if you get them, It probably won't change who you are, you know? [01:08:57] So, so anyway, just wanted to share that cause [01:09:00] Austin had a very inspiring answer for his happiness question. So. [01:09:04] Phil: Yeah. Awesome. Thank you so much for your time today, man. This is super fun. Uh, uh, you know, we'll share links to everything that's, uh, that's going on for you, uh, right now, but yeah. Thanks again for your time. Super, super fun. [01:09:15] Austin: This is a great combo. I appreciate it guys. Thanks for having me on.