Ground Rules: Kat Garcia with Scott Hartley
Kat Garcia, co-founder and co-CEO of Ground chats with Scott Hartley, Managing Partner of Everywhere Ventures on episode 104: Ground Rules.
In episode 104 of Venture Everywhere, Scott Hartley, co-founder and managing partner at Everywhere Ventures, talks with Kat Garcia, co-founder and CEO of Ground, a startup building the AI revenue system for autonomous revenue generation and retention. Kat shares how she left BCG Digital Ventures to work for free with B2C companies, uncovering that operators didn’t need more productivity tools—they needed technology that could autonomously generate revenue on their behalf. She discusses how Ground’s opinionated AI ontology transforms static metrics into actions that drive up to 10% more top-line revenue, moving companies from dashboards to agentic commerce.
In this episode, you will hear:
Unlocking unrealized revenue potential in fragmented tech stacks.
Autonomous revenue generation beyond productivity tools.
Real-time commerce ontology that learns and acts.
Proving autonomous systems in high-churn e-commerce.
Democratizing enterprise capabilities for mid-size brands.
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00:00:04 VO: Everywhere Podcast Network.
00:00:14 Jenny Fielding: Hi, and welcome to the Everywhere podcast. We’re a global community of founders and operators who’ve come together to support the next generation of builders. So the premise of the podcast is just that, founders interviewing other founders about the trials and tribulations of building a company. Hope you enjoy the episode.
00:00:33 Scott: Hi everybody, I’m Scott Hartley, co-founder and managing partner of Everywhere Ventures. I’m super excited to have Kat Garcia on the podcast today with us. Kat is the co-founder and CEO of Ground, which is building out agentic AI revenue generation and retention.
00:00:49 Scott: Ground is now based between Silicon Valley and New York. Kat brings with her a number of cool experiences, having been at BCG Digital Ventures before where she served as the head of growth for multiple companies, helped take Amex’s first debit card to market, and also launched Spin by OXXO. OXXO is the Venmo of Latin America.
00:01:10 Scott: Fun fact, Kat has a background in entertainment, was a film actress, and a number of other fun things we can get into. Kat, welcome to the podcast.
00:01:17 Kat: Thank you so much for having me, Scott. I’m excited.
00:01:20 Scott: I want to take a step back. Go-to market is a broad-based term, but what we’re really talking about is the top of the funnel revenue generation and revenue retention for companies, and how this is moving to a more automated self-driving approach. Walk people through the high-level problem that Ground is solving.
00:01:40 Kat: When I think about Ground, we’re the leading AI revenue system. We generate, we manage, we compound growth. And a lot of that is incremental revenue. And we do that autonomously.
00:1:52 Kat: When we sat down and we were thinking about, okay, how do we help companies achieve their own potential? That’s really the mission. How do we elevate businesses and make sure that they’re reaching their potential, and in many ways, their growth potential with their offerings, with what they’re building?
00:02:11 Kat: A lot of the gap that we found was that there’s an unrealized potential that is hidden in a business because of the way that tools or even technologies have been created or designed.
00:02:26 Kat: A lot of these technologies, when we think about go-to market, when we think about growth, it’s been to support people and teams, to help them be more productive and be more efficient. But it hasn’t really solved for the problem of, oh, now I can actually grow my business and there is impact.
00:02:46 Kat: For the last 20 years, we’ve thought of software as this thing that it’s like, okay, software is saving the world. It’s going to help me achieve my goals and I’m going to, maybe, end the year at a certain point in revenue and it’s going to be helpful.
00:02:59 Kat: But when we were thinking about the problem and a lot of the fragmentation across the tech stack, we sat down and we started working for free. I was a head of growth. I left my job at BCG Digital Ventures and I started working for free as a head of growth for a lot of B2C companies, products primarily.
00:03:18 Kat: And the COOs, the CROs, the CEOs, even go-to-market teams specifically and operators were like, please do not build a productivity tool. I don’t need to be more productive. If AI is really here, we’re in the AI era and we’re in the agentic era, then you should be able to have a technology that can understand my business in real time and just communicate to itself and generate the revenue. Can you just generate revenue for me on my behalf?
00:03:48 Kat: At the time, we laughed. Because it was a joke. But that was an important need that we took seriously because we’re like, well, what if we were to do this? What if we could actually have a measurable impact where you don’t need to guess anymore and you can actually achieve the full potential of your business day-after-day, month-over-month, year-after-year autonomously?
00:04:13 Kat: That’s essentially what we set out to build. That’s why we’re here.
00:04:17 Scott: It’s funny when you say that because it’s such a direct action, but effectively when you have companies myopically building for one problem or another, they get lost in the weeds sometimes.
00:04:30 Scott: The ultimate goal of a company is to solve customer pain points and sell more of whatever they’re selling. To your point, the number of tools and systems that have been built don’t necessarily have a direct impact on that bottom line and that end objective.
00:04:47 Scott: If you think about the inputs, you’ve got humans, you’ve got technology. And the ultimate goal is to generate more bottom line for the business, which then enables the business to reinvest in product and reinvest in tools and become more productive and compound over time.
00:05:02 Scott: What you guys are doing is really trying to streamline that in some ways, bringing the agentic AI era in a more direct way to just generate bottom line for the businesses. Is that correct?
00:05:14 Kat: That’s exactly it. It’s been amazing to be building in the space where it’s instant product market fit because the demand is always going to be there. It’s an evergreen problem, but it’s more so… well, does the product work? Do you actually have AI models that are able to guarantee revenue?
00:05:34 Kat: It’s been great to see that on average, across all of our companies and clients, we’re able to add up to 10% more top line revenue to the business after not much work. It doesn’t really matter the size of the company, whether you’re making 5 million a year in GMV or if you’re doing a billion in sales online, we’re able to install Ground in 15 minutes.
00:06:00 Kat: The onboarding is very simple for businesses. And the ontology or that opinionated AI model or revenue system across your business continuously gets built and it’s able to drive that incrementality.
00:06:15 Kat: I also think about why did we decide to go the route of B2C. This is great for enterprise. But when I look back at the behaviors and the needs, it’s reminiscent of Uber, Airbnb, DoorDash, Waymo, where what a lot of companies in this AI era have been getting wrong is, is to think about AI as for go-to-market, as software, as a service again, with the idea that it’s all about workflows and productivity rather than having a direct impact on a business.
00:06:51 Kat: Because a lot of AI companies are approaching building as, oh, I’m going to build a faster car and better features, faster features. But at Ground, we’ve always approached it as we want to build Waymo. We want to build a car that drives itself and that helps you get to your end destination.
00:07:08 Kat: When we think about why that’s a huge impact on the entire market for B2C companies, it’s that Uber, Airbnb, DoorDash, Waymo, they were building, and in many ways, democratizing their solutions for the middle class. They gave the middle class what the elite had.
00:07:29 Kat: Uber, the elite, they have private drivers. Airbnb, they have access to villas around the world. DoorDash, they have private chefs. Waymo, same thing as Uber.
00:07:41 Kat: But when we think about it and compare that to our industry, enterprises also have access. They don’t need autonomous revenue, but there’s a new class of companies that is emerging that need this. And they want their companies to be self-driving. While many AI companies are approaching the landscape from productivity and better workflows, I want to help midsize brands have outsized outcomes.
00:08:08 Scott: It’s a great metaphor to think about this idea of autonomous vehicles, autonomous revenue, agentic revenue. When you get down to the brass tacks of how that operates, is the problem that people have top of funnel and scraping new leads? Is it management of data that exists in these silos like Salesforce or Databricks or Snowflake?
00:08:29 Scott: Because ultimately you’re trying to meet the customer where the customer is and speak to them in the most authentic way.
00:08:36 Kat: For us, our wedge or sandbox in many ways has been e-commerce so B2C. The reason for that is because the funnel is very similar to B2C across experiences and services, for example, travel or hotels like hospitality, healthcare, entertainment, as well as B2B.
00:09:02 Kat: However, e-commerce is something where if you can build and if it works for e-commerce, it works anywhere. It has the highest churn. It’s the most competitive go-to-market environment because of how fragmented the stack is, how competitive it is.
00:09:21 Kat: Also teams are not digitally native. They’re operator-led. They’re not engineering-led. You need to do a lot of convincing. So your technology needs to have measurable ROI to say my technology or my AI agents drove that incremental revenue that otherwise you wouldn’t have been able to see.
00:09:40 Kat: From day zero, we built Ground to be full funnel. We’re able to be a part of anything before transactions all the way to actually helping you get those transactions through.
00:09:54 Kat: We’re able to generate new leads. If I were to compare B2B to B2C, it’s like if someone is coming from different sources, from different channels, for example, paid ads, UGC, that’s typically the main ways that you’re able to generate top of funnel for B2C.
00:10:11 Kat: A lot of these channels do not communicate to each other and go-to-market teams have a lot of work to do in terms of understanding the source, the creatives. How do I get a new visitor to give me their information? And then how do I get them to make a first purchase? We have Greet AI as one of our AI agents that does that.
00:10:32 Kat: We also are able to support the middle of the funnel. 70% of revenue decisions, they lie in abandonment. So understanding customer intent and fragmentation, where you have a layer that is able to identify these people in a way where it’s privacy first, you need to have a technology that stitches everything together. That’s ReCartify for us.
00:10:56 Kat: Finally, retention is really important because you may have a lot of customers that you’re trying to understand and use regression models or past data to be like, when is this person going to come back? When are they going to buy again? What do they need? How do I drive more LTV without affecting my CAC? And that’s really our ReBeat AI model that is able to drive usually three to seven times more repeat purchase revenue.
00:11:23 Scott: It’s amazing. Basically it’s a set of agents optimized for a few different tasks within that funnel. So one might be attribution back to the initial inroad for that particular client. As you mentioned in B2C and e-commerce, typically that’s attribution to a specific creative or a user generated content or ad profile.
00:11:46 Scott: And then there’s a middle zone, which is helping activate and figure out what the specific hangups or reasons for people not making a purchase. The third bucket is looking at past data and signals to figure out what the leading indicators might be for somebody repurchasing or coming back. That’s on the retention part of the funnel.
00:12:09 Kat: Exactly. More importantly, it’s the ability to take all those insights, predictive patterns, outcomes, and also your existing first party data, and then making sure that we’re generating the revenue so that way you’re not left with a bunch of data or dashboards or tools. It’s doing it for you.
00:12:33 Kat: It knows at different points in time, in real-time across all of your channels, all of your tech stack, executing the right actions in order for you to actually get those dollars in your business. That’s why we’re able to say on average, 10% more top line revenue is because of Ground.
00:12:53 Scott: It’s a great point because I think that’s the move to agentic versus dashboards and data that existed five years ago, is that delineation between not just knowing. But being able to know and acts and have an agent that performs an action or an intervention on behalf of the company to nudge that user in one way or another, which generates bottom line revenue for the business.
00:13:19 Kat: Exactly. That is what is so exciting about all of this because it’s for the first time that this is possible. More importantly, it’s not just the technology, it’s the behaviors. That’s why I go back to, for example, enterprises, maybe the behavior isn’t there yet, but for future enterprises. That’s really where the mid-size market is. They want this.
00:13:47 Kat: Agentic first companies, they’re the ones that are generating dozens or a couple hundreds of millions of dollars a year. And they’re like, we want to be able to manage these different agents, as well as having a system that does it for us. So that way we’re not guessing, and we’re not out here at the end of the year being like, did we hit our goals? Did we actually do everything that we needed to do in order to drive revenue?
00:14:15 Scott: One thing that we’ve noticed at Everywhere the last three or four years, initially there was pushback to AI companies or wrappers that were using off-the-shelf larger language models or LLMs to then integrate into a really specific workflow, like what Ground does, specifically around go-to-market.
00:14:34 Scott: Do you now see that the moats that you’ve been able to create with Ground and the stickiness of the product have to do more with integration into workflow tools for these companies?
00:14:43 Scott: Or is it also that you’re starting to collect and build your own models based on the data signals that you’re seeing for these specific agentic actions, where you’re now backward integrating into having datasets and your own models that maybe were bootstrapped using LLMs, but are now bespoke to just Ground.
00:15:05 Scott: I would imagine you’re starting to see more stickiness and more moat as you guys have been in this market now for a number of years and generated a lot of data and bespoke understanding that you have around these really specific actions and pain points. Do you think that’s a fair characterization of the market over the last few years?
00:15:26 Kat: I would say so. We took the ladder approach, where from the very beginning we built our own models. But over time, they’ve definitely gotten a lot better. Even with our own clients, we have different revenue agents across different parts of the funnel that I had just shared.
00:15:43 Kat: When I think about, for example, the incrementality and the lift that we’re able to provide… like Greet AI, if you want to get more first-time customers in the door and first-time customer revenue, it used to be that the average was Ground can add maybe 20% more. And 20% was like, whoa. You’re adding 20% more first-time customers to the business. Amazing.
00:16:06 Kat: But now we’re seeing where it could be as high as 80%. That’s because when we think about the models that we have, one thing is that they’re able to learn over time because of all the customer data. We’re able to have a surface level that is connected to all of your channels.
00:16:26 Kat: So if you’re using Meta, it’s learning on your Meta. If you have TikTok, it’s learning on TikTok. It’s learning on Shopify or your homegrown site, Klaviyo, all of your different systems. But when you look under the hood, what we’re building is an ontology and it’s an opinion of commerce. It’s an opinion of your business.
00:16:48 Kat: So instead of it just being random clicks or metrics or hovers and actions or ads, all of those things, back in the day, it was just metrics. But being able now to have micro mini LLMs or different agents that operate in different ways, you now have an opinion that has been built just for you that is training over time to take those actions. It’s able to take those actions and learn in real time, which is the magic.
00:17:19 Scott: That’s a really important distinction in the evolution of agentic commerce and in where AI is going is taking static metrics that you used to have in a dashboard and, as you said with Ground, being able to generate an ontology, which is just a mapping of those different signals with an output, with an opinion about what the action should be given those inputs.
00:17:44 Scott: And so it’s really more about this opinionated mapping of KPIs and turning that into actual actions. Now being multi-years into the journey as an AI founder, your background, you didn’t come from a world of AI. None of us did more than a few years ago.
00:18:01 Scott: Walk us through some of those experiences that you had in the past or what was it that you learned at BCG Digital Ventures or in your experience with OXXO in LATAM that really gave you the experience or the confidence to dive headfirst into this market?
00:18:16 Scott: Because now as one of the category leaders, it’s pretty incredible to see the ways in which you’ve reinvented yourself and the ways in which you’ve really generated pole position in a market that’s very fast moving.
00:18:28 Kat: A lot of it has been my subject matter expertise in growing companies. I understand B2B funnels really well, but I also understand B2C, like how do you grow a consumer-facing business, whether that is product company like a Sephora beauty company, or if it’s Equinox, Four Seasons, NFL+ streaming service.
00:18:52 Kat: There’s so many different types of businesses and having had the opportunity at BCG Digital Ventures to incubate companies and be the interim head of growth and launch all of these companies and understanding at different phases how do you do 0 to 10 million ARR in 12 months?
00:19:10 Kat: And then how do you do that and scale it from 10 to a hundred? How do you work with Fortune 500 companies? And all of those growth questions are very different across all those stages of growth, the types of companies as well as their customer base.
00:19:29 Kat: I never really approached it from technology or the solution. It was like, wait a second, I know that the growth playbook is dead. There’s so many technological shifts that are happening where the next Glossier is not going to be built in the same way that Glossier was built in 2010 or Casper, Warby Parker.
00:19:50 Kat: I always approached it from a curiosity lens. And then being able to sit down with CEOs and their teams and work for free and essentially tell them, give me all of your problems and them giving us their data and being like, yeah, this is everything. Here’s my QuickBooks. Here’s my retention problems. I don’t know how to get first time customers in the door. This is how much I’m spending here.
00:20:15 Kat: Being able to have access to that and really just think about it from a first principles thinking and say, okay, this is how we would solve for it manually. And then I’m very thankful for my co-founders, my CTO and co-founder Antonio. He was doing his PhD in AI and machine learning a long, long time ago and dropped out to build within AI and machine learning startups.
00:20:37 Kat: I would always explain to him, this is how I think about this problem manually from a growth marketing standpoint. Now, how would you think about it from an AI machine learning standpoint? Can we automate this? You tell me.
00:20:51 Kat: It was a collective effort by mixing subject matter expertise and then saying, how can we use technology to make this better and drive this outcome? But a lot of it beyond that is education.
00:21:06 Kat: The reason for why we are the leading AI revenue system and why this market, we’ve been working with all these incredible nine-figure businesses so quickly is because we have spent the time to educate people on the importance of AI and demystify how scary it can be.
00:21:28 Scott: One of the things that we used to say at Google and I think is an industry standard at this point was eating your own dog food. As a company that’s leading the charge in AI-driven go-to-market, how do you take a step back and reflect on the lessons that you’re pitching to clients in how you grow Ground itself?
00:21:49 Scott: What are the learnings or what are the ways in which you’re able to grow your own business based on the problem that you’re solving for your clients? Have you adopted internally at Ground that’s been a learning of something that you were providing to a client?
00:22:04 Kat: It’s baked in inside of our DNA and how we’ve been able to grow because our business model is outcome-based. Our business model is one where we have a platform fee, but we also do revenue share.
00:22:18 Kat: The more revenue that Ground generates, the better for the client and the business, but also the better for us. We’re incentivized to have the models work as best as possible to generate as much revenue and growth for all of our clients.
00:22:34 Kat: That has pushed us to innovate and think about, okay, well, if Greet AI is working really well, how do we expand that agent? It’s not about, oh, now we’re going to build new things and we’re going to hope that it has an impact or people want to buy it.
00:22:51 Kat: It’s more like, well, wait a second, we can make this AI agent a lot more powerful if we were to expose it to other channels. If it’s working with Meta, now let’s work with Google ads. Let’s work with TikTok.
00:23:05 Kat: Oh, great. We’re touching online commerce, but then how are we helping our brands make as much revenue as possible on LLMs now with ChatGPT and Shopify? How are they showing up in Perplexity and how can we help them generate more revenue there? The marketing is expanding rapidly and that has pushed us to innovate and think outside the box every day.
00:23:30 Scott: When you think about the future of Ground and the future of the business, looking forward to 2030, what do you see as the undercurrents? Or what do you see taking the business in developing more of these hyper-specific agentic problem solvers for different injection points in the journey?
00:23:49 Scott: Do you see it as going deeper with the ones that you have or building more agents? Where do you see the opportunities in the future of the business and what you could see ultimately as a really successful platform for Ground?
00:24:00 Kat: I love this question. The way that I view it is we have been really focused on our AI agents since inception and making them work better in order to drive as much revenue. But in many ways, the AI revenue system that we’ve built is a control plane.
00:24:18 Kat: While today we’re focused on how revenue should be generated, we also want to think more so around management. How are those transactions being managed across both online or the internet and then now LLMs? And then how are we able to reinvest those dollars into your business in a way that makes sense?
00:24:41 Kat: Because we now have the ontology in which the agents are able to drive revenue and they know how to do that as best as possible given your channels and your tech stack. But over time, you need to also understand autonomously how to reinvest all those profits so that they’re not just going back to the same channels, hoping that you’re doing your best across channel mix.
00:25:07 Kat: We should also have the ability to better manage your business’s financial health. That’s really where we want to go and where we’re thinking.
00:25:16 Scott: It’s almost like another metaphor you often talk about is quant trading. Thinking about the last 20 years as a number of different siloed systems and tools to optimize people and dashboards and KPIs moving from that static siloed system to a more integrated AI driven opinionated ontology of the inputs that your business is generating, whether it’s from ad attributions or customer signals, moving that into this quant trading metaphor.
00:25:48 Scott: Giving people the ability to not set it and forget it, but really set it and have it perform more automated actions than have happened in the past. Is that accurate?
00:25:57 Kat: That’s exactly it. Quantum trading is a perfect analogy. I think that for AI, it’s that a new category should exist and it should emerge. Having an AI revenue system reminds me of Stripe, Klaviyo, Gong, and Shopify.
00:26:14 Kat: Stripe showed that transactions can be managed, but it doesn’t create the demand. Klaviyo showed that customer data, first party data can drive outcomes, but it still relies on manual analysis and past analysis as well.
00:26:30 Kat: Gong showed that AI can create those patterns. It can understand, predict outcomes, but it doesn’t take those actions. And then Shopify showed that if you own the point of purchase, that creates massive leverage, but it’s still very verticalized.
00:26:46 Kat: What’s missing is that control plane that is able to generate all those outcomes based off of those patterns that it understands, and then actually manage those transactions and put it back into the company.
00:27:00 Scott: It’s really a system of dials. And you can develop with Ground this control plane where you can even dial up some of those outcomes by 5% or 10% across the stack. That really compounds into an advantage of acquisition, retention, expansion, modernization. It’s really a holistic AI native operating system.
00:27:23 Kat: Yes, exactly. I love that. It’s funny because even when we were doing our 2026 planning with our CTO and my co-CEO, Antonio and Shahriar, we visualized almost these dials.
00:27:36 Kat: Maybe our dashboard can look more like dials where larger companies, enterprises, the ones of today, they want to have more control. So go-to-market teams, they want to have dials to play around with stuff. And so how do you build for a world that is autonomous, but also you do need specific guardrails? So that’s a really nice visual.
00:27:59 Scott: One thing that Jenny and I talk about a lot with one of our venture partners, Anna Barber, is it’s not necessarily about being contrarian, but it is about predicting consensus and figuring out where the market is going and leading into future consensus in some ways.
00:28:15 Scott: So part of that is having a worldview and an opinion about where you think the world’s going. What is one idea within the sector that experts or putative experts say or often state and believe that you disagree with?
00:28:30 Scott: Where do you think the world is moving if you’re going to predict this consensus? It may be contrarian in the moment, but it’s really about being at the consensus where the market is going ahead of everyone else. What’s one viewpoint that you disagree with where you put your stake in the ground?
00:28:47 Kat: I spent a lot of time in San Francisco, and last year I kept hearing this, which is that foundational models like OpenAI are going to win all of agentic commerce, and that websites are going to go away. Forget the internet. Who cares about B2C funnels, especially top of the funnel?
00:29:09 Kat: I think that is incredibly flawed, especially because we kept saying the same things 20 years ago. It’s like, oh, e-commerce is going to take over. Websites are here. No one is going to shop in real life. That’s going to go away.
00:29:25 Kat: But 10 to 20 years later, retails… it accounts for 84%, whereas e-comm is only 16%. So offline is still four times bigger than online commerce. It’s really a missed opportunity if you’re thinking that now you have to put all of your eggs in one basket. You need to understand where the expansion is, but you need to build for both, and you need to be hybrid.
00:29:50 Kat: Foundational models, they cannot do everything. Google didn’t win everything. Then we wouldn’t really have venture as a whole industry, nor would we have startups and different technologies that have emerged and have IPO’d. So I think foundational models are important for the infrastructure, but we have a very long way to go.
00:30:10 Scott: It’s funny. Thinking back to 2011, my old venture fund, we had a whole future of retail thesis when the world was all moving online and everybody said, e-commerce is the future. Retail is dead. We took a contrarian approach and invested in a lot of optimization for brick and mortar. 15 years on, as you said, 84% of commerce happens offline. So it is a good lesson to remember that you have to build for a hybrid environment.
00:30:37 Scott: And so just when the world is running after LLMs, and obviously you guys are leaning heavily into agentic commerce, there is still this need to optimize across all these different inputs and tool stacks. I think you’re doing a great job of that. I totally agree with that viewpoint. Sometimes you got to push back on the San Francisco consensus a little bit.
00:30:56 Kat: Definitely. As builders, you understand where the behaviors are and where they’re going to be and where they’re not. It’s really important to be able to build for today and tomorrow and not get so stuck on how exciting the technology is.
00:31:12 Kat: That’s been the beauty of building for B2C. When you’re in B2B and you’re stuck on those funnels, the way that you grow a B2B company typically is more engineering led. So you’re going to be faced with ICPs that are incredibly digitally native and they just want to test.
00:31:29 Kat: They just want all of that fun stuff, even though it provides no value. So it’s been really helpful to have to prove value from day one and to scale with folks that are naturally skeptic.
00:31:43 Scott: I have about a hundred more questions I want to ask you, but in the interest of time, we’re running short here. I wanted to laser in on one part of your background, which is just so unique and fun to ask questions about, which is your background in entertainment.
00:31:55 Scott: The lead off story of a book that I wrote in 2017 was about a theater arts major who became a YC founder and built a healthcare company and really attributed her ability to hire and sell based on her experience as an actress.
00:32:11 Scott: She was talking about how when you go to audition on Broadway, 50 people show up in the room, 50 people get the exact same words on the script, one person gets the part. And the one person who gets the part is the one who can imbue the story with the most authenticity, the most meaning, fit the role the best.
00:32:30 Scott: What is one thing that you learned in that prior life experience in entertainment that you’ve taken on as a CEO that has helped you build to where you are today?
00:32:41 Kat: It’s funny because when I was doing founder led sales, it really reminded me of my acting days because for 99 or a hundred auditions, I got one part and it’s not like it was easy either.
00:32:57 Kat: I controlled the outcomes. I never took no for an answer, even though I wasn’t allowed to. I had an agent. There’s casting directors. It’s a very hierarchical industry. It’s incredibly difficult. I would say it’s harder than startups because in startups you can control a lot of those rooms.
00:33:16 Kat: When it came down to the audition process, I always did something that you weren’t supposed to do, which was I would find out the casting directors’ information. I would find out their DNS records of their website and who had created their websites.
00:33:33 Kat: Usually their phone numbers were listed there and I would call them and send them my cover letter of why I would be the best person for the job. I got every part because I did that.
00:33:47 Kat: I recall one of the films that I did, it was a short film that premiered at Cannes. I’ll never forget. I got a call from the casting director who said, hey, Kat. I’m calling you and you’re going to get the part of Molly.
00:34:02 Kat: And I just want to let you know that you were not the best. You were not the best actress, but I’m going to hire you anyway because you’re annoying and you kept calling our office. We got your CD with your demo. And look, you’re relentless and you’re going to work really hard. And that’s also something that the character would have done. So congratulations. That’s it. That’s just how sales is done.
00:34:26 Scott: That is so parallel to founder-led sales. That persistence, that grit, the perseverance, but also the orthogonal thinking, thinking what are the other ways in which I could gain an advantage.
00:34:39 Scott: I love that example of looking up the DNS records, finding the addresses and listings of phone numbers on public databases to back your way into roles. I think that’s so indicative of the grit and persistence that we’ve seen in you as a CEO in the portfolio over the last few years. Thanks for sharing that story. That’s awesome.
00:34:59 Kat: Thank you.
00:35:00 Scott: So really quickly and wrap up, we’re going to do our speed round. So I want to know, what’s a book or podcast that you’re currently enjoying?
00:35:08 Kat: 21 Days Countdown to Riches by Rhonda Byrne. She’s the author of The Secret or The Law of Attraction. This one is more about financial wealth.
00:35:19 Scott: Very cool. I’m going to add that to my Kindle list. If you could live anywhere in the world other than on an airplane between Los Angeles, San Francisco and New York, where would you pick?
00:35:29 Kat: I’ve been dreaming of a very specific home in Cartagena, Colombia. There’s these really gorgeous old colonial homes that have been redone with gorgeous pools. There’s this one villa that I would love to buy and have it be my home.
00:35:47 Scott: That sounds fantastic. I know exactly those old pools that you swim through, an arcade under an old wall with plant foliage and all that. I had a wonderful experience the one time that I was in Cartagena for a wedding. What’s your favorite productivity hack?
00:36:03 Kat: Ooh. Okay. My favorite productivity hack, and this is something that I did a couple years ago, is I really turned off a lot of social media, the noise. I created different profiles for myself on Instagram, Twitter, that have nothing to do with work, that just actually give me a lot of joy. Even Pinterest.
00:36:22 Kat: I have alternative accounts across all of my digital channels for social, and then even for ChatGPT, that are a lot more abundance-oriented that don’t really stress me out. Because it’s not like a bubble where I need to compete. I’m in my own zone. The algorithms have been trained to be with things that just give me peace.
00:36:45 Scott: That’s a great idea. Finally, I guess, across those platforms, where can listeners find you if they look for you online?
00:36:51 Kat: @katgarciaonline across anything. I’m most active on Instagram and LinkedIn. LinkedIn is really where I spend most of my days.
00:37:01 Kat: For Ground, we just redid our Instagram. You can find us there, @joinground. And then we also have a podcast with some of our clients and the ecosystem called Grounded Insights.
00:37:13 Scott: I love that. Well, Kat, thank you so much for being with us today. Congratulations on leading the charge at the forefront of the AI-driven commerce. Thank you for everything that you’ve been building with us.
00:37:25 Kat: Thank you. This was fun.
00:37:28 Scott: Super fun.
00:37:30 Scott Hartley: Thanks for joining us and hope you enjoyed today’s episode. For those of you listening, you might also be interested to learn more about Everywhere. We’re a first-check pre-seed fund that does exactly that, invests everywhere. We’re a community of 500 founders and operators, and we’ve invested in over 250 companies around the globe. Find us at our website, everywhere.vc, on LinkedIn, and through our regular founder spotlights on Substack. Be sure to subscribe, and we’ll catch you on the next episode.