91: Using AI in Sales to Automate Go-to-Market Execution with Jason Eubanks

Humans don't need to be in the business of copy and paste anymore. How are you helping them understand the urgency and the importance of it and how to do it right? I think the importance of it is directly tied to the reason for the urgency and I think you could boil the importance down to a few simple statements. You can unlock at least a 2x productivity gain with this capability, with AI, native intelligent automation, powering true execution, true automation, not just serving up insights. Sales can get pretty churny. Our customers on the average are cutting their onboarding time by 50%. Wow. That's internal onboarding or that's onboarding clients. That's their internal onboarding to productivity for their market teams. Has compared to what industry standard a couple of weeks maybe? Yeah, but it's about three to four weeks. Dude, this is just, it's not fair. Jason UBANKS is the CEO and co-founder of Oresel, an AI native go-to-market platform. He pushes leaders to stop adding chat wrappers to old stacks and instead use intelligent automation that can double sales productivity, eliminate CRM busy work and help teams move faster than competitors. Welcome to using AI at work. I'm your host, Chris Day. Each week we'll be learning how today's business owners, entrepreneurs, and ambitious professionals are getting more done with smart use of tomorrow's tech. Let's get started. Right now every business leader is asking the same question, what are we going to do about AI? If this is you, chiefaiofficeer.com has the answer. We'll give you a simple path forward where we provide executive and team training so your people know exactly how to safely use generative AI in their day to day. We also manage the deployment and implementation to make sure tools actually get adopted and deliver results. And we'll also got company-wide transformation, so AI becomes part of your operating system, not just another shiny object. The companies that act now will increase productivity, cut costs, and grow faster than their competitors. Those that wait will get left behind. So if you want to make AI work in your business, visit chiefaiofficeer.com and see how we're helping companies of all sizes finally get results from AI. Hi everybody. Welcome to another episode of using AI at work. This is Chris Daygel. And I'm actually super hyped up today to talk to our guest, Jason Ubank's founder of RSL. About we just kind of had a pre-conversation. We've had a couple conversations before this. And what he's doing is very cool and very interesting to me personally for where our business is. And it's addressing an area of every business where they'd love to get AI involved. And that's in the sales environment. So Jason, before we start, what is the takeaway that you want the listeners to have at the end of this episode today? I think there's if I could expand it to three takeaways. You know, one is just generally speaking. I try to encourage everyone who I have a conversation with to really challenge themselves to think beyond an incremental approach, beyond a wrapper interface when they consider how to use AI at work. And RSL, of course, is an AI native platform. We'll talk about that later. And I don't mean this in a self-serving way. I truly mean it in a way that most of the people that I speak to in business are still thinking about the application of AI through the lens of a chat. Ask it a question, get an answer. And that's fine because that was the first application in Interface of ForWitch AI generally was exposed to us as a public. As a platform shift, the power of AI is so dramatically impactful beyond question and answer. And I would challenge everybody as they turn internal to their organizations and think about how to unlock productivity, how to outcompete their market, how to better serve their customers. Just take, throw away that scared incremental approach of putting chat wrappers on this and that and connecting it to Slack and homegrown systems and wiring it up and get past that. Like it's cool that you could take a little bit more data and replicate a consumer experience in chat. We really were past that. Products were past that. Technology is ready. I would challenge everybody to jump in with both feet and pivot to an AI native approach everywhere you can. Love it. So that's number one. Okay. It's number one. And then hopefully somewhere in this conversation, I'll have a chance to talk a little bit more self-serving about ourselves for two things that I'm excited about that we are announcing tomorrow. And so a little preview here and you know what it's time to get out of probably will come out. But you know fresh off the presses and we have taken our AI native platform originally built for CRM plus about 15 other products on top of it. All in a single platform. And we're now offering. We're taking the power of that AI native platform, decoupling it from the dependency of a CRM. And making it available to sit right on top of legacy architectures like Salesforce and HubSpot. So large enterprises have a path to harness the power of AI native intelligent automation for all of the go-to-market through Oorsel GTM operating system. And they can sit it right on top of their existing CRM. That's number one. And number two, we're also shipping an agent, a custom agent builder inside of Oorsel that will unlock the power of AI native agent work flows for all go-to-market and ops teams out there. They with with just simple natural language prompt, they can you know execute agent work flows and build their own agents. So really with very few limitations. I mean, this is one of those moments where it's like your imagination is your limitation. Yeah. And exciting time. Awesome. Well, you know what? I think that's going to give me a lot to chew on here. I want to start with your number one. I'm with you. Like I'm drinking the cool late. I know what's possible now. And I don't quite understand why. I mean, I get there's risk concerns. We don't understand that they're risk associated with it or does the budget make sense. I get all that stuff. But you're that's a balsy comment and just say guys jump in. There's how are you helping executives that you're talking to prospects peers that aren't all in like you and I? How are you helping them understand like the urgency and the importance of it and like how to do it right? What are you telling them? I think the importance of it is directly tied to the reason for the urgency. And I think you could boil the importance down to a very simple, a few simple statements. You can unlock at least a 2x productivity game with this capability with AI, native intelligent automation, powering true execution, true automation, not just serving up insights. And those who unlock that opportunity for a 2 to 3x game and productivity first, we'll have a tremendous advantage. And as the gains continue to be exponential in the technology platforms that underpin B to B use of AI, they will by default be the first movers. For those other, the other cohort of people that are thinking about this incrementally and trying to stitch together, you know, you take a fragmented tool stack and you try to stitch together, you know, chat, chat bot like communication across 15 to 20 different vendors. And every time there's a increment, there's a, every time there's a step function gain and underpinning AI capabilities, it's just like anything else in infrastructure, you're going to be stuck trying to manage all of those versions, all of those interconnections, all of the different flavors of a, you know, niche agents and your homegrown bots that you've tried to build. And it's just like the spaghetti infrastructure of the past. Yeah. You know, when you went from, you know, scripts to full automation or on-premise to the cloud, I mean, it's just another version of that evolution. And everyone was scared of those technology shifts in the beginning too. Yeah. And I guess maybe it's because I've been around for 25 years doing this stuff that, you know, I can remember all those conversations when people went from building servers by hand to automating workloads that built data centers to not needing data centers. And to me, there's a lot of similarities here in the sense that the people that jump in and adopt the full power of AI native capabilities first will continue to stay out in front of those that take an incremental approach to get stuck in the tangled web of, you know, complexity. And I just think it's a hard thing to outrun. And now's the moment that you have to create that step function shift in your business along with that disruptive platform shift that's already occurred. Now, I've been a urgency. I think the importance really just comes down to, you truly can transform the productivity model of your business when we talk about go to market. The traditional B2B sales teams are still in a place that's upside down. I mean, just last year, for us, our all kinds of reports out there, you can see this is easy to find the data, but still, still 80% of the revenues come in from the top 25% of sellers. That means that your, you know, organizations are spending 75% of their go-to-market expense envelope to get 20% of the business. And that's just an unsustainable productivity model. When everyone's doing that, you have small levers for gains. When some portion of the competitive landscape starts to to garner a 2x productivity gain and through excellence and execution at scale with consistency provided through automation, you take those bottom performers and you move them up to look more like the elite performers of your org. Those competitors, those companies that do that first will simply just outpace the ones that are still here are spending 75% of their expense envelope on, you know, 20% of productivity and a market that is unrelenting around what we've seen recently in value slides. And there's going to be pressure anytime you have a market shift like that. There's going to be natural pressure that flows through on efficiency. And so, whether you think about it through the lens of gaining a productive edge or gaining efficiency edge either way, whether you want to drive more top line and you want to do it in more productive way, I just think the opportunity is there. And those winners will be the ones that jump in right now. The other side of this is, you know, I was talking, by the way, just to share a customer story and I keep the, keep the names out of it. But I was talking to one of the, the world's largest, you know, hardware and technology services companies yesterday. And they've been around for decades and decades and decades. And this is not a company that if I, if I said the brand name to you, you would think, absolutely, they're going to be on the top of the adoption curve of AI. But they are, they are challenging themselves. They're carving off a portion of their business, you know, 150 users out of 2000 sellers and saying, Hey, we're going to take this pod and we're going all, and we're throwing out all the 20 year legacy rules. And we're going to pretend that this is, we're going all in right now. How would we build this go-to-market motion today for this division of the company if they were a new company? And they are, we're going on that journey with them. And they are benchmarking all of the metrics and all the productivity gains. Yeah. All of the expense, all the, all the additional insights and automation and intelligence. They are benchmarking it. And they're just going to put it to the test. And that's the kind of thing that I would encourage people to do when you see companies that are 100 years old doing this. Yeah. How could you be a younger company and not? Yeah. So a couple of things, I like this because I was actually trying to explain this to someone this morning. This idea that you had about the exponential gains that are going to occur from the individuals who adopt now, like they're going to pull away from the pack and it will, you will not be able to catch up with them. If you are, if you delay three months, six months and these people are in stealth mode unintentionally, but they're going AI native. So those who wait will not be able to catch up, which is a, like that's a paradigm that doesn't happen that often in business where somebody's like, oh, we just work twice as hard, we'll catch up. No, like the distance of time, performance, capability, resource requirement, minimization, like all of that will be, anyway, you, you, you verbalize what I was thinking this morning. And that's an unusual place. And I can see how that ties to the importance and the urgency there. Like you said at the very beginning, they're very much tied together. And then I like this idea a lot about an incumbent saying, hey, let's peel off a little bit of the business and let's go AI native. Let's go off the reservation, go all AI, how would we do it? They're going to learn some stuff that will be translated to the rest of the 2000 sellers and it will be lights out. That's amazing. That's a fantastic approach. We'd love to hear more about that data when you can, if you can ever share that. Okay. And then now the second thing was you were talking about the, this kind of overlay that you guys, I mean, when you and I first spoke about being on the podcast, it was probably, you know, before the holidays. And just in that short period of time, it sounds like there's been some developments, lessons learned and enhancements that have like, or a cell's a different product than it was 90 days ago. So tell me more about that, that overlay, it's basically natural language, search, and retrieval from all of my legacy systems. Okay. So you're referring to our, you second point. Yeah. Okay. So not something that we've said on camera yet. So let's bring the audience up to speed. So you're referring to our custom agent. No, that was the third thing that you mentioned just now. It sounded like you were indicating that this, this environment of having this cluster of systems that people used to need is going away. And that, yeah. Let's dig in on that a little bit. Okay. Sure. Sorry. So I guess let's, let's bring the audience on the journey. So we started or a cell in summer of 2024. Out of a place of frustration and technical opportunity. You know, I was, I've been an operator for over 20 years, building sales, marketing, and CS teams for multiple startups. My co-founder and CTO ran was SVP of engineering with me at harness for five years. We were last worked together. Prior to that, built big products like the cloud, cloud offering and Nutanik and Nutanix had built a lot of product for VMware, pre and post IPO. So worked together five years. We were talking a lot about the opportunity with with AI being a platform shift and settled in on, just a shared concern that we both have, which is the customer journey and how fragmented the existing go-to-market tooling landscape is and how go-to-market teams really have like three CRMs and tool stacks inside of go-to-market. You have your your your, your martex tool, tool stack, anchored by, you know, a, a, a, a, a, market or a HubSpot marketing or whatever kind of as the CRM of marketing of Salesforce HubSpot, etc. for, you know, this, the sales CRM, and you have, you know, plan, plan handgain site, etc. as kind of these CSM products. I would call that like the quote, unquote CRM of of CS and sure, yeah. For, from a customer's perspective, someone who's buying a solution off somebody, you know, that's just a single customer journey. You go going through different phases of that customer journey. Why should you be why should that intelligence about that customer journey be spread across three different systems? Why should there be fragmentation that that in the technology landscape that requires 15 to 20 products? When I was in harness, our go-to-market tooling stack was 22 products. Yeah. Yeah. Sitting on top of Salesforce. And, you know, I had a team of 11 ops people stitching that stuff together manually. You know, we had three products. We had custom built to fill the gaps on top of it. We had, I had engineers, I had data engineers, building data pipelines for analytics and top of all this mess. And it's like a Changastack, you know, it's like it's just leaned over and you have problems all the time and integrations break and you don't have a single lens for analytics. Metadata is trapped in 22 different databases. And, and when you think about applying that legacy architecture and the, to, to the go-to-market workflows in the era of AI, it just doesn't make sense. In the era of AI, you know, what we've built is an AI native CRM platform. That was the original product that we built at ORACEL. AI native CRM platform. It included the CRM, built on an AI native architecture with a unified data model supporting structured, typical CRM data, structured data, and unstructured data with a, with a data lake house. And having knowledge graphing and time series and all these, you know, rag models and all these AI native architectural components allowed us to build an agentic layer on top of it, you know, being backed up across five of the, the world's best known LLM models and drive the surfacing insights that were relevant to the different personas at the different phase of the, of the perspective buying journey from, you know, contact to contract and then driving intelligent automation through an agentic workflow model built within the platform. That's the first product we took to market and we have customers on today. What we're announcing now are two different products. One, we're taking that the power of that entire AI native platform and decoupling it from our CRM and allowing it to just plug and play right on top of Salesforce or HubSpot. Still getting rid of those 14 other products that you have to plug in on top of your legacy CRM to make them useful. You know, we still ship with 85 million accounts and 850 million contacts. Our platform forms still ships with the operating system still ships with 10,000 agents in the background that are doing deep research AI enrichment surfacing automated AI enrichment extending custom AI enrichment and then putting all that to work and automated agentic pipeline workflows personalized outreach at scale, you know, for AI forecasting, etc. So all these capabilities that sit across all the internal and external conversation signals that are being enriched to unlock intelligent actions. That capability is what we're shipping in our go-to-market operating system. But, but now large enterprises and customers that want to coexist with maybe other workflows that they've built into the RCRM system. That can coexist and it can either be a bridge for adoption from a legacy tool stack into an AI native platform as you kind of take a crawl walk, run approach or and or it can coexist forever. Now, what does this mean for the day-to-day work of your sellers or marketers or CS teams? It's simplified. It's automated. It's enriched. You take the the user and you put them in a RSL, allow them to have a single place for all of those signals driving contextual awareness across all the internal and external conversations and unlocking intelligent actions for them. Making them twice as productive, getting rid of 80% of their, you know, manual toil time, eliminating the need for another 14 products on top of your legacy CRM. That's what we're shipping in the go-to-market operating system. So, as a user, as a participant in those departments, I have one place that I go. I'm not getting a report here, extracting that data, uploading it here and playing that whole game. Right. That's an incredibly unproductive use of a human's capacity. Right. Our belief is that so what we do is we design all of our automation, all of our insights, all of our enrichment, all of our automation that sits on top of it with the notion of what would a human do. What are the next three actions that the human we're serving? The are so deserving in that moment. What would they do? And can we automate that intelligently for them to further free them up for conversations like this one? That's how you may operators superhuman operators and hours to free them up to do what they do best. And I would imagine that in the sales environment, there's churn as in any department, but sales can get pretty churny. That means probably onboarding for new reps is pretty quick because there's one tool that they're dealing with primarily. So they're not having to go and figure out all the proprietary stack that was built. Interesting. Yeah. We're seeing on the enablement front or an onboarding front. You know, our customers on the average are cutting their onboarding time by 50%. Wow. That's their internal onboarding to productivity for their rather market teams. I mean, we of course use our own product. Our SDRs are booking meetings and productive on their third day. Yeah. That's compared to what industry standard, a couple of weeks maybe? Yeah. Yeah. And then and if you think about, you know, a 50% reduction to productivity time, when you're scaling on the back of a productivity model led by sales, one, it's costly, then you always have to over hire because you're chasing a six to nine month product, you know, ramp time. And so if you can save that by 50% and get to max productivity faster, while you're also increasing the the productivity average productivity of a seller, your word by 50, 50% to 100%. So somewhere between 50% to doubling your productivity for head and the average. When you get those two levers for productivity, yeah, you really are, you dramatically reduce the amount of hiring you have to expense you have to lay out to reach the same or better top line goals. And I would imagine that just you think about it, it just kind of makes sense. It's the, you know, all the intelligent automation is there to feed them signals so they spend time with the right prospects, you know, you dry dynamically driving ICP territories dynamically filling up those accounts with the right contacts automatically showing them the moment that they should contact that person. Yeah, because we see the external signals. And then really feeding them the personalized outreach and all the intelligence on the account, automating the enriching the value hypothesis and giving them a ready made pitch on what to do and what how to say it in that moment that they're supposed to reach out to them. You just remove a lot of the toil and you maximize a lot of conversion. I'm thinking about all these things that are unlocked at every interaction one of the sales say. I'm thinking about all these sales books that, you know, all these salespeople have read out their career that give them systems on follow up and, you know, all that like out the window, the whole different paradigm. That's all automated, right? It's all automated. And by the way, it's not, those things are still great. I mean, the, we have built, we have built the sales frameworks into the system. And so as our customers set up or a cell and choose the frameworks that matter for their organization. And by the way, you can choose different frameworks and different sales processes for different motions. So PLG motion can be different from a high velocity sales like commercial motion, different from a large enterprise, very complex motion. All those things can coexist and dynamically apply automated at the right moment. And then it's coaching like the value-based selling frameworks. The coaching is derived from the best practices of those sales frameworks that our customers are choosing. So it's like having your best trained sales leader on the shoulder every sales rep. This is incredible. So one of the stats that always struck me, I'm not from a sales background, but it was how little amount of time of a salesperson spent on the phone. And it was surprisingly low. You think, okay, it's a salesperson. They're on the phone a lot. No, they're updating the CRM, they're sending the email and preparing the proposal or whatever. This is that that increased productivity you're talking about is because the salesperson isn't doing the things that usually were the parts of the job they didn't like, but that the sales manager was always like, dude, you got to get the stun update the CRM, put your notes in the, yeah. And now this is all being handled automatically. So the industry stat, by the way, what you're talking about is in 20 is 24 to 30%. So an average B2B seller will be in a productive selling activity talking to a prospect, either in a meeting, on a call, whatever, 24 to 30% of their life. That means you're paying them. Yeah. So whatever you're expending per head on your sales team, you're wasting 70% of it with regard to productivity models. And just going back to that stat you shared earlier. Yeah. Yeah. So the objective is to free them up to do what they do best as close to 100% of the time as you can. And you really touch on another another aspect of this, which is the emotional unlock those that toil that manual toil that manual activity. Those are the parts of the job that every seller hates the most. Every marketer hates the most. Every SER hates the most. Every CSM hates the most. You know, who hates it just as much as they do. The manager's rapper chased them to do it. And you waste in the cycles those managers too. Yeah. And the exacts above them who have to chase the managers to get it done. The ripple effect of toil on productivity and emotional drag just goes through the organization like a title wave. Interesting. The whole paradigm of the sales environment is going to change. You're going to need fewer people. They're going to be better supported at higher momentum, higher speed. Incredible. Now, let's move on to the third thing that you talked about, which was this kind of breakthrough that you guys are having with the agentic things. I don't know if you can share the example you were telling me earlier, but like it's kind of mind blowing as a listener, as you guys pay attention to these about to say, like I want you to think about how many people would have been involved and how much time would have been necessary to execute something that's now natural language initiated. Go grab a cup of coffee. Yeah, sure. So I'll give a couple examples of what Chris, what you're referring to is our conversation ahead of this meeting, which, so, or so we are about to ship our agent builder. To put that in the context, what does it mean? Well, because we're an AI native platform, and the architecture already has embedded within our platform services, an agentic workflow engine, you already can go into the orcil platform and build workflows that have agentic properties. And that is powerful. You know, it's very powerful. You can deep web research, married together with AI logic research and actions that are templated. And it's great. What we're shipping now is different though. What we're shipping now is the ability, I'll give you a couple examples so it's a concrete for your listeners. One example, which I just walked into a room at eight o'clock last night here in the office and a couple engineers and my co-founder and CTO were asking what they're working on and they demoed it to me. And it was fantastic. And with two lines of just natural language prompts, meaning, hey, the actual prompt, hey, or so, tell me which of my users, which users are the top three users of my product, how they use the product and recommend to them something that they might get more additional value out of in the platform. And then build an automated sequence to share that information with them, expose and expose knowledge videos to teach them how to use it. So, you know, a couple sentences, natural language like you might ask me to go do something. From there, Oursel's agent builder pulled in post-hog feeds, evaluated all the users usage, ranked it by power users against features, derived the logic and reasoning to understand what value would be unlocked in context of that, that users business of our platform with those features created a message around that and outreach message around a message that was a sequence that Oursel executed to send that user message. And then looked at what they're not using. Again, married it against the value hypothesis of that our customers core business and then derived the reasoning for how they might benefit from understanding another capability in the platform, explained it to them and then from there, grabbed a knowledge-based video and embedded it. Now, the other thing that happened here was and we watched their run on the screen in Oursel in the editor mode, is in the middle of all that that our Oursel agent builder started writing code to go out and discover other fragmented data sources that were relevant to answering the question. So, think about the fact that we pulled in post-hog data, we have value hypothesis information and other structured data in our CRM, of course, so it's using structured data from two different sources and then, based on that user, it went out and looked at persona and then it went out and used our agents to go gather information about external signals that would further inform it on what that person might find valuable and then it wrote a connector into a data warehouse that separate from our unstructured lake house where additional data was stored and it wrote that connector on the fly, gathered the user information, prompted where it didn't have it, established the connection, pulled in other unstructured data as part of its research and reasoning and then came to a conclusion executed in eight steps sequence and with zero user interaction. While that's happening, the competition is saying, hey guys, on Tuesday, we need to do a meeting, okay, we need to plan this thing out, make sure the devs are going to be there because we're going to have some stuff for them, Q and it, like, you're talking about whatever just happened while you guys sat at that conference table, the competition is taking a few weeks just to get off, like, get started. Incredible. Yeah, I mean, think about the old way of doing that, you would go on a journey, probably we're a data engineer to ask them to pull together three different data, three or four different data sources. They got you, they can't stop and do, like, I'll get to it later kind of thing, yeah. And then you, you know, that would be served up to an exec somewhere, some list would get handed to a CS team and a sales team. They would then write outreach based on that, maybe they put it in a sequencer, maybe they wouldn't, probably half of the org would actually execute the request. Yeah. And then they'd get busy with context switching on something else and, you know, go do something else. And by the way, the, the, when that, when that message goes out, it's not just about the outreach of the message, the interaction continues. So when that, that message is responded to our agent continues the dialogue for as long as and tell you until it derives and action that it has to involve a human, all of that hits, notifies the human attached to the account, all of that hits a timeline in the account. So anybody involved in the team can see it. And at any point, a human can step in and take over. But if the human doesn't, it's going to continue to work and engage. In this way, it kind of goes to that like context switching drop balls, lack of fall kind of. Yeah. Yeah. Now, like, human has the power to supersede at any point in time. But if you want to let it continue to go, it will. Like, you know, and like go like another example of extending that that workflow out is scheduling. It's simply, like, you know, can we, would you like to have a meeting with one of our field deployed, four deployed engineers to learn more about it in real time? Beyond this video. And if they say, they come back and they say, sure, I'd love to, that great. And it takes over the calendaring action, interaction. Again, personalized, it's going to feel like human interaction to the end user on the other side. And then it'll go tap the right resource and organization with that meeting happens and needs a human. And off we go. And so that was one example. Another example, which is pretty cool, which I like was was really interesting was as a, as a revops example. And in this case, we told the agent because because or cell knows about the profile of the customers in our platform, we know we've sucked in, you know, the case studies, we know what they sell, what problems they solve, who they sell to, the buyer personas are, ICP competitors, etc. Because we know all this information already, you know, now in or a cell, and if you were setting it up for the first time, like if a revops person wanted to establish a cell's process, or a cell has an opinion on what cell's process best practices would look like based on your company. And now instead of thinking about going through this long design process and setting everything up in your system, a revops person, we do this, do this demo last week, a revops person simply goes into or cell and says, design design a cell stage process and recommend cell frameworks that would best optimize outcomes for my company. That's it. You give that prompt. We run the research logic and and show you a visual of the cell stages and the cell's frameworks and it might be one, it might be three, depends on your business that co-exist. And then if you say great go or a cell goes to work building it and configuring it in the platform for you, that's it. It's it's really that this is what I mean by unleashing the power of the hand you have platform. The productivity just just wipples throughout. So for the listeners, I mean, obviously this type of you know, experience is occurring across other departments, but you know, the easiest place to get big buy in is show me the numbers, right? Like is it impacting the revenue? And this is obviously mechanisms that will certainly do that. So for the people who are listening because our audience is all strata, obviously, but we do have a lot of lower middle market executives that listen to this. Who probably hear this and this sounds like magic to them. How do they get a peek behind the curtain and see some of that magic with Oral? Yeah, I mean, it can feel like magic sometimes. So we, you know, just reach out and we're happy to give you a demo. We do have, you know, there's a there's a short explainer demo that's on the new website coming up. We'll have that in the show notes. Okay. Yeah, if you want to check that out, you can hit the homepage and click on it and you can schedule a meeting with any of our or sell team right there. Well, we still send human star meetings. We do use we do use our another agent. We're about to ship soon in March is our autonomous SDR agent. So we're using that internally and our SDRs are just 100% on the phone now through our voice style. Wow. We removed all the other work from them. Yeah. I'm interested in that for our endeavors as well. So you book a demo, a human show by promise. Yeah. So we'll have links to that certainly in the show notes, but as far as like you sharing perspectives, do you like do you have time to even post on any of the social platforms or blog or anything for the company? I can be better at this. Yeah. I dry. But so yes, I'll make a commitment to be better at it. What's best in cloud? Okay. Where could people pay attention to it? Because we know what's happening in the marketplace here at chief AI officer. And what you guys are doing is advanced, but still accessible to companies that aren't all in on AI. The way that you've explained things, I get it. I could not even know how all this stuff is working as a business owner yet still have access to what I would consider cutting edge, capabilities of generative AI for my sales environment. So like as a as a listener who may not be as deep into it as you were, I, I think that if they were to get more of your perspective, it would be easier for them to translate that to the rest of the team and say, guys, we got to do this, right? So where do they pay attention to kind of how you're looking at this and how you're explaining it and the experiences that you're having talking to other businesses about it? Great question. I am most active on LinkedIn. That would be the short answer. We'll put that. We'll put your LinkedIn handle in the show notes as well. Jason, this is, this is awesome. I'm kind of like the kid in at Christmas kind of vibe because every time I talk to somebody who's doing something cool on the podcast, I'm like, oh, I want to do that too. I mean, not, not build the product, but use the product, right? So I'm actually going to have our head of enterprise sales reach out and just go through the process as a customer and that would be great. Yeah, what you're doing is pretty cool stuff. So I think for taking the time out, I know that with as much travel as you're doing with both of us having startups that are starting to take off, it's tough to get people on on for an hour on a podcast, but I appreciate you sharing this with the community and any closing remarks or anything that you think we need to wrap this up with. I think that I'm just underscored again. If you're not, if you're not doing this in a big way, assume that everybody's playing with AI at some point. Yes. You go to you go to dinner party and everybody wants to tell you that they find out that you're in the industry and they want to tell you about how they use chat GPT. You know, so everybody's playing with AI. So of course, you have to assume that your competitors are. And again, I would just understand where that now is the opportunity, now is the opportunistic time to really jump in and consider AI native approaches across the business and all of your workloads and workflows. Because I do believe it's the is the moment to create a gap. It's a really unfair gap in whatever it is that you do with your business. And you're right. The our technology and the way that we've built it is meant to deliver kind of this magical moment for all of the personas that we serve and their respect and workflows. And it's intended to be automated in a way that it doesn't require you to think about the infrastructure behind it. And that makes it accessible to everyone. So that is part of our design practice. It's part of the way we built the platform. So I'm glad to hear you say that. Yeah. I hope that part of this conversation makes it a little less intimidating for those listeners who are considering doing more but nervous about jumping in or you know, taking in incremental approach to get started and challenge themselves. Like that company, that big company that I talked about before is challenging themselves. You know, you can do that at any stage whether you're a small, medium or large business, young or old. And other than that, I just say thank you Chris. Thank you for having me on. It's always a pleasure to have a conversation with you. I think we could just kick around all of these stories and ideas for hours. And so this is a, you know, I very much enjoy joining you. Awesome. Well, thank you again, Jason. And safe travels. I know you've got a bunch of business travel coming up. And for all of our listeners, my advice as always, go use A.V. Thanks everybody. We'll see you on the next one. Thanks for tuning into using AI at work. 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