Revenue Tech 
Vision & Stack Design

Julia Nimchinski [ 00:00:06 ] Welcome back to the AI Summit Forecast 25, Day 2. Our first topic today is revenue, tech vision, and stack design, led by one and only Udi Ledergård, Chief Evangelist at Gong. Udi, welcome. Our community is super excited; got a ton of messages. So yeah, how are you doing? I’m doing great. Thanks for having me, Julia. I’m so excited to dig into the brilliant minds that we have assembled here today. So whenever you’re ready, we can get started. Awesome. Let’s do a quick round of introductions, everyone. Amanda, let’s start with you. Sure thing. Hi, I’m Amanda Calo. I am the CEO and founder of OneMind. I was also formerly the founder and former CEO of a company called Sixth Sense, which Kerry knows a little bit about. So excited to be here today.

Julia Nimchinski [ 00:00:58 ] Welcome. Who’s going to be next, Kerry? I’ll go since I’ve been called out already. My old friend, Amanda. And so I, Kerry Cunningham, I work at Sixth Sense now, and I head up a research and thought leadership discipline, which is really cool. And I’m a former analyst. And so I worked with Sears Decisions and Forrester for about eight years and covering predictive analytics at the time, which is the AI space now. So happy to be here. Elizabeth. Hi there, everyone. My name is Elizabeth McCauley, founder and CEO of StartStack. We’re an agency go-to-market services organization. I have a long background in enterprise software and services, and I live at the center of business strategy, product, and go-to-market. Matt. Hey, guys. Matt Darrow, CEO, co-founder of Vivint here.

Matthew Darrow [ 00:01:53 ] We raised $130 million to build tools for technical sales teams. So we’re really excited to be here today, including the industry’s first AI sales engineer. So we work with enterprises you guys know, like ADP, Dayforce, and Snowflake, and really excited to be here today. Last but not least, Glenn. Hey, everyone. My name is Glenn. I’m a co-founder and CPO at Expandi, and background in multiple tech startups. But Expandi is the first one released five years ago, and we’re doing a lot better now. Uri, back to you. Awesome. Well, I’m excited. I’m excited to be here. My name is Uri Ledergore. I’m the chief evangelist and former chief marketing officer at Gong, the leading revenue intelligence platform. Not that you need an introduction, but let’s kick it off. All right.

Udi Ledergor [ 00:02:43 ] Thank you, Julie. Thank you so much. All right, folks. So many questions. I hope we can squeeze most of them into the one hour that we have. So we’ve all seen the tech stack change over the course of the last two years. Part of it was part of the economy. Part of it was part of the launch of generative AI and many other changes in the marketplace. Why don’t we start with you, Amanda? You were the co-founder and CEO of Sixth Sense. You’re now at OneMind. How have you seen the tech stack change in these last two years? And what does it look like today compared to what you saw at Sixth Sense a couple of years ago? Yeah.

Amanda Kahlow [ 00:03:18 ] Yeah, I think we would all say that it’s hard to say that we can put our finger on where the future is going and where we are today. There are so many amazing opportunities. Coming into the future with this new wave of generative AI. I think, you know, when I think about the tech stack and the dynamic shift, we were previously building technology, you know, especially in marketing and sales for people, for humans, right? Whereas now we’re building technology for technology, for our agents, for what we call superhumans that can participate in conversations. And, you know, it was all about a single source of truth and a record of truth, and then actioning off that record of truth, where right now, I think the shift in dynamic between buyers and sellers has happened, where we can put control back in the seller’s hands.

Amanda Kahlow [ 00:04:04 ] * And I think technology; I don’t think we’ve even, like, I think we’re going to see in a very short amount of time where AI buyers and AI sellers are talking to each other. I know that’s really hard for us to imagine that you have an AI that’s going to talk to an AI to get the job done. But I think we are there in a very short order of time. And I think some of the incumbents are going to have, you know, a lot of time to talk to each other. And I think some of the incumbents are going to have some challenges kind of moving forward as every good time and transition in our society happens. Some of the bigger guys will have a hard time shifting and turning the ship.

Kerry Cunningham [ 00:04:38 ] Okay, I have a feeling Carrie has something, some thoughts on that. Carrie, what do you say? Well, first of all, I would say I think Amanda was on to something about 10 years ago, and she was right then. So if this is what she’s saying now, she’d probably pay attention to that. The second thing I think I would say, though, about all of this is that I think it’s really important if you’re a practitioner in marketing or in sales, that you keep your eyes on the prize. What is it that you’re actually trying to accomplish and needs to happen over the next few years? And then how can new tools help you do that and not work the other way around?

Kerry Cunningham [ 00:05:16 ] * And I think over the years, and Amanda, I think you might agree with this, we’ve seen it work the other way around a lot, where a lot of people will see the shiny new tool and say, ‘You know, what can it do for me?’ Well, that’s an interesting question. But if you haven’t already considered really deeply, what do you need done first, then I think you end up going down a lot of paths that are not very productive. That’s a really interesting point, Carrie. I think we’re going to have a little discussion about that later, because there are different points of view on balancing between the problem you need to solve and what the technology allows you to solve. Yeah.

Udi Ledergor [ 00:05:53 ] * To quote the tired out adage of Henry Ford, if you ask the people what they want, they’d ask for faster horses. But the new technology allowed us to do things that were unimaginable before that. So I think there’s more than one interesting point of view on that. But thanks for putting a pin in that, Carrie. Matt, I love your take on what leaders are getting wrong about AI and its impact on their go-to-market teams. You’re kind of the spearhead of everything going on there right now. Yeah, I think my one word is speed. And some of the panelists mentioned this already. It’s moving faster than I think a lot of go-to-market leaders are even anticipating. And an example of that is like when we were doing our roadshow last month, we were showing things that people thought might be possible five years from now.

Matthew Darrow [ 00:06:38 ] * You can actually do them with technology yesterday. And honestly, it freaked a lot of people out and it made a lot of people mad because they culturally need to catch up to how this work dynamic is changing. And that’s the number one thing for me, which is embrace the change. The change is happening quickly and start to prepare for it because our teams will never look the same again. Nearly every piece of the go-to-market function is going to have an AI doppelganger that’s going to help out and do the actual work. That’s the core difference. Matt, can you spell out for those of us who are not in the weeds as much as you are, what are some of those early appearances of technology?

Matthew Darrow [ 00:07:15 ] * Where are companies already getting results with some of this stuff that maybe some of us still think is futuristic, but it’s actually already working? Yeah, that’s a great question for me, even in terms of tools that not only we’re building, but we’re adopting. And this isn’t 12 months from now. We have more tools that we’re using unlike ever before. And it’s also because a lot of these are AI-native tools where pricing makes it easy to go and experiment because there’s not these big upfront commitments. So one big bucket, I think, is virtual workers. I’m not going to make this a Vivint plug around an AISE, but an AISDR, right? These are all over the place as well. So we intend to hire multiple clients in the next 12 months.

Matthew Darrow [ 00:07:58 ] The second thing is content creation. We’ve been having a ton of fun there. A little bit of the spicy take is we know that long form content and people reading a lot of assets isn’t a thing anymore. And there are so many tools that can help us with video creation, blog creation, testimonial creation, podcast content. There’s never been a better way to get your message out using a lot of different experimentation. And then the last thing I’ll say is custom builds. You can use tools like Langchain built on top of LLMs. And actually build your own custom agents that do amazing things like write LinkedIn posts and social selling for you. And these are three different areas that we definitely experiment and we expect this to keep going too. Interesting.

Udi Ledergor [ 00:08:39 ] Anyone else on the panel is already experimenting and getting early promising results with AI, that you’d like to share? Yeah, I’ll go ahead and volunteer something. We use AI in all the work we do for operational marketing, content marketing, product marketing, business strategy. And the early results we’re seeing for clients we’re working with is so stunning. Some of the data we don’t know, we even want to publish because it’s really just, we’re proving that you can cut all the fat off of marketing. Marketing tends to be incredibly wasteful. One of the top ways that early companies burn money. And we’re getting ahead of that in pioneering some new capabilities to be able to do that in a much smarter way. What are those capabilities replacing in what you call wasteful marketing?

Elizabeth McCalley [ 00:09:33 ] * A lot of the specificity in how companies go to market. I think people are very overwhelmed by all the AI content, all the LinkedIn messages that are flooding people’s inboxes that are not valuable. And so a lot of the AI-driven research and the research that informs the messaging, that informs the strategy, that informs the product marketing. That’s really how companies can get back to enterprise value and try to stay away from the sameness that I think is very obvious when you read AI content. Interesting. Kerry, it looks like you have a take on this. I just, you know, we use a generative AI a lot when we’re writing lots of papers. I’ve got two people and we’ve written 10 research reports in the last three months.

Kerry Cunningham [ 00:10:26 ] * And you know, so we use generative AI a lot. We never stare at a blank page anymore. Just there’s no reason to do that. But for the most part, what I find when you’re doing things like ideation, what’s a new way to tell the story? If you ask ChatGPT or another tool for some ideas, you’ll get a long list of ideas that everybody else would already have had. And you can cross those off immediately. And it does lead you to some place where now, OK, you know, here’s a spark of an idea. If they didn’t, if I didn’t think of it, then maybe it’s good, right? Or maybe it’s interesting. And to go down that path. That’s the second time I’ve heard that idea, Kerry. And I love that.

Udi Ledergor [ 00:11:05 ] * I just want to highlight that in case folks missed it. One counterintuitive way of using ChatGPT is to actually eliminate the most obvious ideas, because that’s what ChatGPT is really good at doing. It’s giving you the obvious ideas that everyone has already regurgitated. So if you bring ChatGPT into a brainstorming meeting, say, what are the top 10 ideas for this topic? Those are the first 10 you can probably cross off your list because they’ve been done and then overdone it. So I love that idea. Matt, you have a take on this. Well, I wanted to chime in because I couldn’t agree more with Kerry and Elizabeth. I think why there’s so much challenge, why AI-generated content is a little bit of a malaise for folks, is that you’re just getting the middle of the bell curve of 10,000 people that already tried to write the same content.

Matthew Darrow [ 00:11:50 ] * And that’s just because of the co-occurrence and how these systems work. So then when we’re trying to figure out, well, how do we actually get content out? How do we make it lift and use these applications to do custom things, content creation? It’s got to go far beyond the LLM, and I think that’s the most important thing for GTM leaders to look at, too. If the LLM is the brain of the system, you’re not going to get the output that you want. That’s exactly right. I have a little – oh, sorry, go ahead. I was just going to throw in there, I agree with Matt. People do work. AI is part of our process. Whenever I hear humans in the loop, I just – I sort of cringe because that’s implying that humans are bystanders.

Elizabeth McCalley [ 00:12:25 ] * So, yeah. I think salespeople, go-to-market executives, whatever role people happen to be doing in their domain expertise, when those people become expert AI practitioners, that’s really where the magic happens. I have a spicier-I have a little bit of a spicy take on this. So I was trying to mix it up a little. I truly believe in some ways we’re all getting AI wrong across how we use it for go-to-market. We’re going back and we’re using it – everybody’s looking at this for efficiency gains, for making writing better content, for expediting a process. Even Benioff in his keynote at Dreamforce talks about task-based, simple tasks and efficiencies that we can use this for. I think we can use it for something much bigger. Jaco from Winning by Design talks about if you want to grow linearly, hire more people.

Amanda Kahlow [ 00:13:19 ] If you want exponential growth, then you need to think about AI. So how can we use AI? And I am leaning into the concept that we are truly – this is a new evolution of humanity. We are replacing humans. And AI can do it in a way that humans can’t. So humans have capacity limitations. We hire a human as an SDR. We hire it as an inbound. We hire somebody as an AE and then a sales engineer. And then we have our customer success person. The reason we have different roles in these functions is because we have time capacity and content capacity limitations. What if we could start thinking about AI in a way that really can’t just augment, but truly lean in and replace some of those functions where there’s so much waste and so much spend, 50% to 80% of our budgets are being spent on people across go-to-market.

Amanda Kahlow [ 00:14:03 ] And can do it in a way that at the end of the day, and I think Carrie would agree with me here, is that we need to put control in the hands of the buyers, not in our sellers’ pockets. And so if we allow buyers to get at information in an efficient way, the way they want it, meet them where they are, on the website, in the Zoom. Hey, let me spin up a Zoom. And let me talk to you about your technical requirements. And I’ll just end on one quick story. So, I didn’t share what we’re doing, but we are building, for those who don’t know, One Mind is building super humans. It’s a face, voice, brain. She can meet you on the website.

Amanda Kahlow [ 00:14:33 ] She can qualify you, give the pitch, give a demo, join a Zoom, answer the hard technical questions, pass it along and respond to your RFP. And then, oh, by the way, onboard you as well. So we’re basically building these digital workers, if you will, with a face and voice that can do what a human can do. And I’m in a deep sales cycle with a CRM company right now. I had somebody who was very much against what we were doing. Who basically said, no, I’m not having this. And she went and talked to our AI on the website. And then she basically got on the call two hours later and said to me, hey, you know, I was like, what did you think, Pamela? And she’s like, I was a no.

Amanda Kahlow [ 00:15:07 ] * We’re not doing this. We’re not bringing this into our company. But I spoke to the AI and I had my 15 technical questions answered. I don’t have any questions for you and now I’m your biggest champion. Right? So it can give buyers control, gave her that control in my sales cycle. So I think we’re getting it. I think this piece is obvious. Sorry, I’ll stop. Go for it. I’m smiling because just this morning, Jason Lemkin posted something that made me laugh on LinkedIn. He said that Mark Benioff just announced that he’s hiring a thousand salespeople to sell their new AI agents, which are supposed to help their customers have fewer salespeople. So which one is it? But jokes aside, I love that take.

Matthew Darrow [ 00:15:44 ] Matt, did you have another quick plug before we move on or just lift a hand up from before? I do want to comment on a matter. Amanda’s piece, and I’m glad you went with the spicy take because similar to what I mentioned about the roadshow, that’s kind of what frustrated people or riled them up was when you take them all the way there, like that is the logical conclusion, what you just described. Like, there’s this productivity farce, which is, well, if I make everybody 10 times more productive, then it’s great for everybody. But what happens is they’re just not that much more throughput in the marketplace that your business can drive. So ultimately what’s going to happen is that roles will change hands, responsibilities will change.

Matthew Darrow [ 00:16:20 ] * And I don’t know if you want to answer it here. Like I was a believer that what’s going to happen is like you’re going to get the steel pillars of the organization will remain, say, sales rep carrying quota, product person building product. And a lot of the other ancillary functions that were born out of specialization because of time, capacity, mental throughput, that is a kill zone for what agents can do and change that whole dynamic with you. I think it would be really interesting to see how roles and responsibilities are kind of ebbing and flowing in the next few years, and it’ll definitely take some time and the more traditional industries will take longer as they always do. But it’s definitely going to be really interesting.

Udi Ledergor [ 00:16:59 ] * And we’re already seeing very tight, small organizations that are hitting milestones that typically you have to be 10x larger in order to hit. So thank you all for taking on that. I can comment on this for a second because we’re reinventing our product management process. We can write PRDs. We can do this in like a week with all the product requirements and starting from ideation through conversation. So I think to the point of Amanda’s, the bow tie, I think there’s an opportunity. That’s kind of the revenue side of things, but also in how AI is supporting back office, product development. AI-native companies are going to have fundamentally different unit economics than other companies. Thank you, Elizabeth. Glenn, last one to take on this question, which I’m glad opened up this discussion.

Udi Ledergor [ 00:17:58 ] * Yeah, we are already doing this from our support. So basically gathering like the biggest pain points, the biggest complication we have in our app. And basically it will help us to brainstorm quicker, to go through ideation quicker. So right now it’s already there. It’s already like way more efficient for us. So it’s like, I think, 40% time saver already. So, Glenn, while I’ve got you, why don’t you kick us off with the next question? Looking at your own tech stack right now, do you expect to be using more or fewer tools in 12 months from now and why? I think, to be honest, way more because every quarter we do a review of everything that we use. But yeah, with Lyft, with AI. I think in the last week.

Glenn Miseroy [ 00:18:44 ] We already started using 10 different tools. So month over month, that rapidly increases. But we’ll keep doing that. So basically implementing it in smaller teams will work better because if we do it company-wide, it’s very tricky, right? So testing it, get quick results and then rolling it out company-wide is something we do on a weekly base. Interesting. Kerry, you speak to a lot of companies in your role as head of research and thought leadership. What are the trends that you’re seeing? Are companies expanding? Are they expecting to use more tools? Are they expecting to use fewer tools? And I asked this on the kind of backdrop that in the last 18 months, every single CFO and RevOps person I spoke to said that the mandate now is to chop off anything from 10% to 20% of your tech budget.

Udi Ledergor [ 00:19:29 ] And that led to some inevitable consolidation. Is the market bouncing back? What are you seeing? Yeah, so I see the same thing. And we did a tech consolidation landscape thing about this time last year. And I think a lot of things. Companies did. Certainly, Sixth Sense has been moving to allow customers to consolidate on platform instead of a bunch of smaller tools. So I think everybody’s saying that. But I think in practice, what’s actually happening is every time you make a change, it’s like a fractal geometry, right? So you look at it from this angle and it’s got these characteristics. You pull in a little closer and, oh, even at a smaller dimension, it’s that way too and that way too. Every time. You make a change. You add.

Kerry Cunningham [ 00:20:16 ] * You consolidate a little bit or you add another piece of technology. You open up two gaps on either side of it, and those gaps on either side of it get filled with something else and two more gaps and two more gaps. So even when you consolidate, you’re sort of, you know, you’re the old Irish fable of Cahulan fighting with the sea. You know, you’re just in the ocean trying to bat the waves back. So I think we’re thinking consolidation in order to keep something maybe the same size. Or not exponentially growing. But I don’t think. Your bottom line is it will definitely grow. The tech stack is constantly growing. While we’re talking. The beast cannot be stopped. Yeah. I don’t think it can shrink at this time.

Amanda Kahlow [ 00:20:57 ] * Like, I think there are some, maybe some big, for the bigger, like, more incumbent players, some of the core functionality, it can shrink across those players. But there’s so much happening right now. And there’s, and people are really starting to catch on that they have to do things in a different way. Like, we came up with the idea of AI LG, like AI-led growth. And if you’re going to do that, that’s going to change the dynamic of everything that you need. If you’re not serving humans anymore across your sales cycle, you’re serving agents that are doing these digital working functions and talking to your buyers. What do we need from a tech perspective? So things are going to shift. And I don’t think we know what that looks like yet.

Udi Ledergor [ 00:21:35 ] * Matt, your quick take on the number of tools growing or shrinking. Yeah. I mean, from personal experience. At Vivint, we did SaaS consolidation. And, you know, Gong, I think, is a relevant example here because we were using Gong for CI. And Gong has a great product with, you know, the competition for outreach. And then we just sort of moved to Gong. And I see that happening across, like, SaaS. That consolidation makes a lot of sense. But I’m with Amanda that, like, all of our experimentation, all of our new tools are in all of the AI-native workflows. Again, whether or not it’s digital workers, new workflows. New processes. New data. And that’s where I see the proliferation expanding, where I love to consolidate the SaaS stack.

Matthew Darrow [ 00:22:19 ] And then a lot of these native AI apps, I welcome them in because, again, the way that they monetize, the way that they price, it makes it easy for you to do that experimentation with the right problem in mind. So if I try to summarize and weave together the different answers that I heard here, here’s what I’m hearing. I’m hearing is where there’s a category or a workflow. A workflow that is a little bit more mature makes a lot of sense to consolidate. And Matt started the Gong example, so I’ll finish it. You know, Gong started out eight or nine years ago with conversation intelligence, which then evolved into revenue intelligence. And then two years ago, based on a lot of market pull, we added Gong Forecast, which replaces legacy forecasting tools.

Udi Ledergor [ 00:23:03 ] And then based on even more market pull, especially with the economy that we have, last year we succumbed to the pressure. And we released the sales engagement product, which replaces those 10-year-old legacy sales engagement products with an AI-native product that was built for 2024 and beyond. And so we’ve seen Gong Engage and Gong Forecast grow much, much faster than our conversation intelligence product just because, A, we have the install base, and, B, the market was ripe for that sort of consolidation. And at the same time, what all of you are saying one way or another is that this is the best time to be experimenting with these next age points. I think the way we think about it, and I think that’s a great question.

Udi Ledergor [ 00:23:39 ] * The way we think about it is that there are some really interesting point solutions that have not yet evolved into a platform because they’re so young and they started with a little wedge. But you’d be foolish not to experiment with these things and see where they could add either fewer jobs needed to do the job or more productivity on jobs that we’re keeping. Did I get that more or less right? Yeah. And I would add to that. So, the way we think about it, probably similar to Matt, is I don’t know if Matt you’re thinking about it this way. But I’m not going, I’m not selling against like a Gong or a Sixth Sense. Right? This is a software play. I’m actually selling humans. So, you’re going to pay for this like a human.

Amanda Kahlow [ 00:24:14 ] You’re going to give me upside like a human when a human performs. And if my human performs better, let me have a piece of that pie and I’ll give you a smaller base. And then you’re going to charge based on the time that she is in the conversation, the usage component. So we’re basically looking at this as you’re buying capacity to have conversations and talk to your buyers in a way that relates to them in the most empathetic, real-time, wherever they are across any channel, way. So I’m really trying to stay away from this: ‘you’re buying software’, right? I don’t want to, you know, these license fees anymore. We’re really starting to relook at this. We do have a base license fee right now, but yesterday we spent three hours talking, maybe we’re going to shift this, right?

Udi Ledergor [ 00:24:57 ] There was more of just a, you’re buying humans, you’re buying capacity. I think you bring up a really important topic that we probably won’t have time to dive in today, but that is the emergency. We’ve seen the emergence of new pricing models where for 25 years, we’ve all been selling software by licenses in the last, let’s call it five to seven years. We’ve seen the emergence of usage-based pricing on things like cloud consumption and that sort of thing. And now we’re seeing this quick rise of the third one that many companies are already experimenting with, which is around, I’m replacing your humans. So I want to price it that way, but let’s not dive into that right now. I do want to take a detour into an audience question that just came up, which is this.

Udi Ledergor [ 00:25:35 ] I’m interested to hear more about whether or not the panel sees how they’re using GenAI today as a competitive differentiator, or is it just their starting point to get people adopting and comfortable on it? Who wants to take a first stab at that? Go ahead, Matt. So both, and God, I hate when people say both, but let me go in both routes. I think the first is like earlier this year at Vivint, we, we bought a license to ChatGPT for every single employee. And, and the whole reason we did that was it’s almost like a, an ice bath that you give the organization from a culture standpoint, because the point was, it’s like, Hey, look, this is, this is like using the internet.

Matthew Darrow [ 00:26:20 ] And if you, if you don’t know how to use these tools moving forward, like culturally, you’re just not going to be in a place to not only be at Vivint, but be at any organization under the sun. And that was important to do culturally to set the tone and the signal, but then also the use cases are really odd. With Gen AI, it’s not like a SaaS app that has 10 declarative things that it does. Like, you need sort of, sort of crowdsource creativity to get people comfortable. So, I think that’s the ‘yes’ culture internally, but then on the competitive differentiation side, not just us, but that’s why our customers want to use these tools because at 1,000% is a competitive differentiation.

Matthew Darrow [ 00:26:53 ] And I would imagine, Amanda, I’ve not super familiar with your guys’ service yet, but totally excited about where you guys are going. But if you’re doing things like your buyers are engaging directly with AI, I mean, that has a huge impact to how your company is perceived in the marketplace too. You’re just perceived as an innovator, a company that others want to be like to do business with. And I think that there’s, it’s much more than just, wow, are you offloading the work, but it’s how you show up in the world. And those companies that are using AI to show up in the world differently are going to differentiate. Yeah. And on that, I think it’s a question. A lot of people ask me, well, will buyers want to talk to the superhuman or talk to the AI?

Amanda Kahlow [ 00:27:27 ] And my response back is we’re not, we’re not forcing anyone. We’re giving them an option. Think of what we do to people who go to your website. Like they go to your website, they go to Gong, they have a need. They want to think about like their call reportings and their forecasting. And then they research and look around. They have two options. They can talk to this lurking chat bot in the bottom, right? That like 2% people do. And it just like, it doesn’t work, right? Like maybe it has a small conversion rate and sure generative can make it more conversational, but it’s not really empathetic. It’s not understanding. It’s not giving me the pitch. It’s not giving me the demo, or you can fill out a form and wait a week for somebody to call you back.

Amanda Kahlow [ 00:28:01 ] And Oh, by the way, if you’re an SMB or don’t match my ICP, we’re not calling you, right? So the other option, you’ll get a call within hours. I will try. I will go on. But, but even, but even then, wouldn’t you rather as the owner of your business and your PNL, not put a human that’s going to cost $89 an hour. If you actually look at their fully loaded costs for a hundred thousand dollar BDR, but put an AI that costs a few dollars an hour that can have a much deeper conversation and right there in the spot, right, right there in the moment when somebody has a need, answer their questions. And go as deep as they want to go, not just high level.

Amanda Kahlow [ 00:28:37 ] Let me qualify you and do my job, allowing the buyer to ask the questions and take control back in that first touch, right? So that is the beauty of AI. It allows us to do things that we never could do before. We couldn’t even dream of it. I mean, we can’t even; I’ll give one more point on a call. A seller cannot bring up a slide in real time. When asked a question, if somebody asks me, ‘What’s your technical overview?’ I have it. I’m like, ‘Oh, shoot, it’s over here.’ Let me go grab it from the other side. I’m like, this deck that we look; we can’t, we don’t have that kind of recall, but the AI can.

Amanda Kahlow [ 00:29:09 ] * So we can actually meet buyers and do some really basic things that transform the buying and selling experience and really shorten that sales cycle, which we’re all looking to do. Thank you, Amanda. Elizabeth, your quick take on that. Internal work, definitely a extreme competitive advantage. And it is the work that we do through and through. I would say that I like, I like the whole analogy of the ice bath. But I find that people who are incredibly process-oriented, people who love to learn, people who are curious, people that want to figure things out, tend to be the most successful in figuring out how to invent new ways of doing things. Because I think we’ve all made the point on this call, the way that things have been done may not be how things will be in the future.

Elizabeth McCalley [ 00:30:00 ] I’ve pushed back a little bit that, and this is my personal preference. I have experienced a sales cycle with an AI native company, and all the AI is in the back, so the people and real human interaction can be in the front. And that’s how they’ve changed, you know, their unit economics of the company. And I think there’s still real value from people that are part of a process. So I have a, I see, kind of where you’re going with this, Amanda, I don’t disagree, there’s huge opportunity. But I’m going to double down that people like people, people like relationships, people like and buy from people they trust and respect. And it also kind of depends on what kind of business you’re in. If you’re in a software-based five-volume widget kind of business, maybe that’s okay.

Elizabeth McCalley [ 00:30:49 ] * But I think that businesses are incredibly complicated, and people need to make sure that they’re doing the right things. You know, I mean, all of us here in technology sales, you know, the technical teams, you know, are always for the win. And, you know, I’ve met my share of architects in my life, and they are very hard to replicate an enterprise architect or people like that with some very, very deep skills with AI. I haven’t seen it yet. I’m not going to say it’s impossible. But, but, you know, I take that as a challenge. I would love to put your people against a superhuman to do the same job. And I bet Matt would do the same. Yeah, we have our topic for the next webinar, Amanda, I-we do need to move on.

Udi Ledergor [ 00:31:33 ] * Carrie, one more take on that. And then I’ve got another spicy one. I thought the next one is going to be spicy. But you’re finding spice in the most innocuous question, which I love. So thank you, everyone for the great discussion, Carrie, your last take on this one. Yeah, this would be a little spicy, too, I think. And I’m going to jump a little bit on Amanda’s bandwagon. So one, buyers: 80% of buyers do not want to talk to a seller while they’re deciding what they want. And they won’t, they can’t change it. You can email and call them, and they’re not going to engage with you. The primary reason for that, I believe, is because they don’t want to be pitched. We can say that people like to talk to other people.

Kerry Cunningham [ 00:32:10 ] * But no, they don’t. Because we know what’s going to happen if we do, right? We’re going to get pitched; they’re going to try to get us to do something that we don’t want to do. I am much more comfortable telling a bot to buzz off – I don’t want it – than I am another person. So if I have the opportunity to interact and ask questions of a bot, and I don’t have to hurt somebody else’s feelings or be mean to them, or whatever, it’s going to happen at the end, when they try to pitch me, I’m going to do it. And I’m not alone. The data set. You’re a much kinder man than I am, Carrie. You should have heard me with some service providers yesterday over the phone.

Amanda Kahlow [ 00:32:43 ] * But thank you for that. People like to buy, not to be sold to. People want to buy; they don’t want to be sold to. And so, that’s just allowing people to come in and build a relationship. And there are pieces of it. But to get information, there’s a much better way, let my kids jump on my lap and let me learn about Gong, right? I don’t have to worry about the-I think Amanda touched on an important thing, which is what stage of the buying process I am, because you’re both right. Carrie is right to say that in the early stages, if I’m just trying to get information from four different vendors to help me make a decision on how to narrow them down or which one I’m going to work with, I don’t want four people having my phone number and calling me and pitching me until the cows come home.

Udi Ledergor [ 00:33:20 ] * But at the end of the day, I think Elizabeth is right as well, because once I have chosen my vendor, especially if it’s a six or seven figure deal, I absolutely want to talk to human beings. I want them to confirm that they understand my unique security and IT challenges and how they’re going to solve it for me. Glenn, bring us home on this one. A lot is about the intent, right? So if they give certain triggers, like intent triggers, I think you can fight the right moment. And by using that, I think the chance of success is 10 times higher. If you combine it with a soft approach, I think instead of like a hardcore lead, what you said, if you have like four agents directly on top of you, not the right moment, it won’t be successful.

Elizabeth McCalley [ 00:33:58 ] * Right. And what we’re going to talk about here is the organizational intelligence of the sales cycle. And that, you know, we’re all making the point here that there’s a role for AI at some point in the process. There may be a role for people in the process, but are organizations really intelligent enough to know exactly where that buyer is on their journey and which tools and capabilities to serve up to keep that journey moving along? And, you know, that is, I think, probably the grand challenge is, how do you build organizations that are, have this organizational and system intelligence that also includes people? And I think that’s probably pretty hard with what we’re talking about here. Okay.

Udi Ledergor [ 00:34:42 ] I’m going to move on to the next one, which is, let’s try and do this in a little bit of a different way so we can actually get through some of the questions. Let’s try and do a rapid fire round here where you each limit yourself to like 30 seconds. And I’m going to take a take. I can’t do that. I know. I know, Amanda. I’m going to find this one challenging. Let’s try this. I’ll start with you, Amanda. What is one tool or business area that is absolutely ripe for AI disruption right now? But 30 seconds or less. I will cut you off. Humans. Inbound humans and inbound sales engineers. They’re ripe for disruption right now. Inbound humans, inbound sales engineers. Thank you. Not inbound sales engineers and inbound BDRs.

Udi Ledergor [ 00:35:25 ] * Yeah. There you go. That was short. Matt. Same. It’s any role, it’s a hybrid. That has knowledge. Any knowledge worker? Is that what you’re saying? Knowledge worker. That’s a specialty worker. Hey, good take. Glenn, what about you? Support. Support. That is a big one. We’re seeing a lot of companies trying to automate that now. Elizabeth, how about you? All aspects of the business. All aspects of the business. Interesting. And you, Kerry? I’ll say. I’ll say. I’ll say. And I think, you know, enabling buyers to buy without being sold, I think, is a thing that absolutely the first ones to do it well are going to win. So let’s stay with you for a minute, Kerry.

Udi Ledergor [ 00:36:14 ] * And go back a little bit to the number of tools, but do a little bit of a deep dive on the consolidation. So as you mentioned yourself, we’ve heard a lot about this and you pointed out some of the problems with the gaps that are left around consolidation. Where do you see this? Is this trending and is 2025 going to be another pivotal year in how companies think about consolidation versus just dispersing everything they need into dozens or hundreds of little tools? I can share that at Gong a couple of years ago, we did an audit. I’m sure we do this more often. But the last one I saw was a couple of years ago. And at a company, we’re probably a small enterprise with about 1,300 to 1,500 employees.

Udi Ledergor [ 00:36:54 ] * We have well over 1,200 different software tools as the company. Yeah. And my marketing team alone, which is one of the smallest teams in the company, there were at least 59 tools in a very old count that we counted. So where are we going with that, Kerry? And how is AI going to change that? Well, I would say, first of all, AI could make that not matter. So, one thing AI could do is say, ‘All right, you’ve got 100 tools, AI, go make them all work nicely together. And I don’t want to think about it again. So that, right? Or we could just take all, I think, you know, Matt said it well earlier, you can take the things that are kind of standard practice things today, consolidate them all down, and then you’re continually bringing in new experiments and things that you’re going to do.

Kerry Cunningham [ 00:37:39 ] * And you’re continually realizing new gaps in what you want to be able to do. Your organization is thinking of new ways to add value and all of that and finding new ways to do it. So I think those two things are both possible, plus probably lots of other stuff I can’t think of. I love what you said about asking AI to fix those problems. You know, Tomas Tungu is from BreadPoint Ventures. He wrote a really interesting piece a few days ago where he was describing some of his own AI workflows, and he’s always kind of trying the cutting-edge things. And one thing he realizes is that now that he can take a photo of either a piece of code or another resource and show that to a piece of AI, and an AI just reads it and then does whatever he wants with it.

Udi Ledergor [ 00:38:18 ] He said, like, are we at the end of the need for software integration? Because AI can now see. I don’t have to build these complex APIs and integrations. I can see what I wanted to see and what I wanted to do with that information. So maybe we’re heading to a future where AEs don’t need to input information to the CRM, nor do any other system that we’re integrating in there. What a wild thought. If you think about any biological system, they’re immensely more complicated than any technical system that we have today. And yet they work fine and we don’t think about them and work in ways that are completely flawless. So why wouldn’t the technological environment come to mirror the biological one?

Udi Ledergor [ 00:38:59 ] I mean, everything, every cell in your body is dramatically more complex than anything that you know of, right? And it just goes on and on. Yeah, I would agree with what we’re talking about here, Carrie’s comment, because the context of this conversation is tools, right? And all of the technical debt where the tools are required to fill in what isn’t possible or hasn’t been built before. And companies that are born AI native will not have these technical debt problems because AI is an architecture. It’s you could put all the complexity under the waterline and it just works. And that’s what will be very hard for mature old companies that have Franken-clouds. That’ll be really, really hard for them to make that transition to the AI-native world.

Matthew Darrow [ 00:39:52 ] Similarly, how on-premise SaaS companies had a really hard time with the technology. So I think that’s a really, really hard time making the transition to cloud. The difference is times is going much faster. And it’s pretty stunning. What’s possible. Frank and Cloud is a good one, Matt, and then Amanda. Yeah, I wanted to touch on this number of applications and sort of, you know, revisit the this point, the point I made earlier, too, which is, I’m definitely not a suggested proponent for GTM leaders to say, go consolidate SaaS, and then go get like 100 different AI point solutions out there. The reason why that there’s going to be more tools, though, and you look at like, well, why is AI just so disruptive? We’re not changing form factor.

Matthew Darrow [ 00:40:32 ] It’s not like desktop to mobile, we’re not changing infra like on prem to cloud. The disruptive moment is it’s a labor disruption. And this is going back to why Amanda keeps talking about the human side and the workforce side, like that, that is what it is at its core. And I think the farce or the the angle to go down that you don’t want to do is be a GTM leader that’s just buying a bunch of like, point use cases from AI. What you need to do is, you need to go buy, ‘what does the human do,’ and go get that. And then, that’s, that’s how you’re not going to end up with this amalgamation of crap that, like, you go here for research here for information over here for another thing.

Matthew Darrow [ 00:41:09 ] And then all of a sudden, I’m using six AI tools that are sort of loosely strung together. Because if labor is the core of the disruption, you need to go find what the human does and go get that, and then use it to change your workflow. Thank you, Matt, Amanda, and then Glenn will close us out on this question. Okay, so you brought up something earlier, where you said, we’re going to update, we could update the Salesforce records, I think this is one of the places like where we’re getting it wrong, is that we’re thinking about how we can do what we do today better. Those are incremental point solutions, making what we’re doing today with the processes and the limitations of humans better.

Amanda Kahlow [ 00:41:41 ] *But instead of how can we update Salesforce instantly and have the right summarization, etc. How can we use the conversational data in the next conversation, so that I can bring that recall in real time into the conversation to move the deal forward and close business. So the goal is not to make efficiency across what you’re already doing, really, it’s to think about to the future, that our goal is to grow. Yeah, it’s not growth at any cost anymore, right? We can’t just throw money at the problem. So we need to do efficient growth. And it’s not about making what we do today, slightly better. And I think that’s a place that people are sometimes getting this wrong. Totally agree. Glenn, final words on that.

Glenn Miseroy [ 00:42:22 ] * So as a SaaS, we are aiming to be more connectable for AI, right? So that people can build LLMs around our SaaS. So I do think that opens a lot of those human-sized paths that people want to do. So I do think if every SaaS would do that, it would be way more easier for people to connect to multiple apps in a very short amount of time. So if the SaaS staff is actually doing that on their own, I think it’s going to be very good for people to be able to build that on. It will be a lot faster because, um, basically if people need to really do that on their own I don’t think it will happen very short. Glenn, let me stay with you for a minute, um, and shift gears a little bit.

Udi Ledergor [ 00:43:05 ] * The bar for developing new software with all the Gen AI tools is now lower than ever. How do you think that’s changing organizations’ decisions? How’s it changing your decisions on the build versus buy question for your tech stack? You have a specific need; are you going to consider building it now because it’s so easy to build or at least get started with building? Are you still going to go out there and look for someone who’s been cracking this problem for a couple of years and probably has something that’s good enough for you to use? Yeah, so in the past I think, let’s say from two years ago we would always decide to build depending on our company core values um and core value proposition but I do think in the last months we definitely decided to integrate or to buy.

Glenn Miseroy [ 00:43:54 ] Yeah, interesting. Saying that despite the lower bar for building today, you’re actually looking externally first now, yeah I mean you can get competitive advantage very quickly if you adopt other tools or let’s say if we adopt, yeah AI built by others. Um, building it yourself is but I think only for operational purposes. Um, to give an example, basically what I explained with the support issues, the things that we get like feedback, we gather negative pain points, all those things-if we want there are no models right now, yeah maybe uh um on the created one, but there are no models right now that would actually combine that for instance with financial with our financial data right so we use a different financial platform than our support platform but if you can connect it to we could do things based on aspects like Gud is helping us build the system關 12 .

Glenn Miseroy [ 00:44:47 ] * 22, on the financial impact instead of only using it for ideation for product instance, I’d love to get Elizabeth’s take and then Matt, yeah, I think as yeah, so, build by partner, it’s a really important decision and it really depends on what the purpose is of the of what you’re evaluating right. If it’s part of your intellectual property and competitive advantages, it’s probably um, you know, core to own all your technology, but if it’s really just part of an operational process and things that you can switch in and out or even experiment um, and some of the things Matt’s talking about um makes sense to leave room to be able to do that. So, a lot of companies that are we’re engaged with that’s really the first step is how do you rapidly figure out what that market opportunity is and what you should, you know, build and and what may already exist that fits nicely into your stack.

Matthew Darrow [ 00:45:41 ] * Thank you, and so Elizabeth, Matt, I i was going to add on the build front, I think it’s a little bit of a false positive that it’s so easy to build because like go get an LLM go get LangChain. go sling some python and you’re going to make something that you just scared yourself about and that’s good but but if you’re going to do the work a human does it won’t cut it and i think why the builds are so hard and amanda if you’re in the same track that i am too you know this like knowledge management recall memory and and and and and and and and and and and and and and and and and and

Matthew Darrow [ 00:46:11 ] * learning like the llm does not do any of that and unless you have hyper specialization in ontology building design memory learning recall understanding that’s those are the things that there’s it teams don’t know how to do that and i think that’s Why building versus buying is a little bit of a farce, like if you want to do an LLM wrapper, cool, go do it, but that’s not going to live up to the promise and the premise of Gen AI which is labor disruption. Yeah, I just know you have a take on this. Well, obviously I’m going to say I’m going to say bye on especially what we’re doing um and it’s like what Matt said it’s the final mile right?

Amanda Kahlow [ 00:46:47 ] * You could, you can go by get by an LLM you can put a face on it you can put a voice on it but is she going to know when to speak in conversation does she have active memory, she a passive memory, she able to pull up the right slide and you know as we all know like the it’s that final bit like the anytime we make one small change everything can be out of whack again right so it is it’s an art changing a table in microsoft word right try it is really difficult right like there is that fine balance and then there are tricks that you learn along the way and then you know knowing who she’s speaking to and pulling all the information in and then sending it to the next place like the downstream systems that she’s going to go

Amanda Kahlow [ 00:47:25 ] yes some of the core can be done but like there are so many micro and i we call them like the agi challenges like we’re trying to get as close to like the human experience as we can to Recognize emotion, be able to read emotion, play that back, know when they say no, they actually meant yes or vice versa, etc those things are difficult problems and like they’re the small problems that add up to a solution that will really work in terms of replacing humans um yes can we all do a you know create our own chat bot yes but is it going to be good enough to put in front of your customers probably not thanks for that take Amanda Carrie coming back to you and to the discussion that we pinned earlier today how much of your tech stack decisions are based on a problem you need solved versus wanting to explore the potential.

Udi Ledergor [ 00:48:11 ] Of new technology like Gen AI, so I’d love to hear your perspective and what you’re seeing out there with companies that you’re speaking with, yeah. So I think you you can think about it top-down or bottom-up, uh, bottom-up being there’s stuff that we can do, so which of this stuff should we do, uh, top-down being what are the things that we really should be doing and I think to everybody’s point, especially Amanda, you know there’s a lot of things that we’re doing in B2B and go-to-market that we shouldn’t be doing, uh, that we’re doing because it’s the legacy of how we’re doing it and what was built and all of that um but there are lots of things That we could or should be doing that we’re not doing, and I think the way to understand that is to understand your buyers and what your buyers’ needs are-their information needs, what they’re trying to accomplish, what’s the difficulty in doing it.

Kerry Cunningham [ 00:48:59 ] It takes a buying group of 11 people, about 900 interactions just with vendors including content interactions, to make a purchase today, and 11 months so that sucks! Why does that have to happen? Um, maybe it doesn’t. And then when you think about what they’re doing today-so buyers are going out and they’re doing information searches all over the place and Googling; they’re not going to be doing that anymore even next year so what is your website going to do for them so I think companies need to be thinking about that what is what is it that we actually should be doing to make the experience of buying us and to make our brand preferred what can we be doing and should we be doing and how can AI help

Kerry Cunningham [ 00:49:41 ] instead of well here’s a bunch of tools and they can do this do we need that okay you know it’s it’s interesting but that’s going to lead you to a lot of things that are going to waste your time or maybe set you up to do stuff that you don’t need to be done that shouldn’t be done and I’m seeing a lot of that so I’d like to see the Top, you’re strongly entrenched in the start with the problem camp if I get your drift, yeah, and I’m sure there’s some other some other maybe more nuanced approaches to it if you want to give it a step, yeah. I I definitely think the user

Elizabeth McCalley [ 00:50:16 ] experience the buyer Journey all those interactions when AI should be interacting with buyers versus when things are kind of behind the scenes so I I always index on user experience and the buyer Journey so I think everything starts with process many companies don’t know what their processes are which makes it really hard to figure out how does it apply and it’s kind of like you know it’s it’s It’s kind of like, what’s old is new again. Start with the process and figure out how to design from there. Interesting, uh, Matt would love your take on, uh, start with the problem or is sometimes starting with the technology a good starting point. I’ll, I’ll, uh, double back and double down on one of my prior answers which was, uh, uh, which was definitely the problem because there’s got to be a problem or else you’re just sort of wasting everybody’s time involved, but the one exception, uh, was what I discussed was on the culture side.

Matthew Darrow [ 00:51:11 ] I thought that was really important was just to send the send the signal to the organization. That this is not a trend, it’s not a fad, it’s not asking people to go and put all your ‘and’ I’m not going to pay you through blockchain like this is like a real thing that’s going on and uh and so forth like you got to learn it and that’s a cultural change even though there was no problem and what happens like fun things come out of that because then when you give people that freedom, and then you crowdsource these different use cases, you’ll get like finance teams doing modeling without you get like CSM teams like interpreting usage data for them, you know on their own or you’ll even do like if you guys if you haven’t done this, sorry.

Matthew Darrow [ 00:51:49 ] Shameless plug for something kind of fun, which was, if you ask AI to go roast your LinkedIn photo, you’ll get a really funny response. Like, there are these cultural things that bring people together and start conversations too. But, but I think that’s just like, you want to send the signal that’s where the world is going. But, if you’re going to make a businessman in a purchase, it’s got to be around a problem. And the problem always nets down to the core of it-it’s a disruption of knowledge work. Find the knowledge work you want to disrupt and go solve it! Alright, Glenn, any, take on problem versus technology where do we start? Um, yeah. Usually, problem-first, right? Um, but technology can also help to to explore new things, so it’s definitely not only the the pain points you’re trying to solve.

Glenn Miseroy [ 00:52:34 ] We also test sometimes with AI some new things and we see that it’s pretty successful. Thank you, Glenn Amanda, last one to round us out on this one. I mean, I always say start with the problem right? So, that’s always the place place to go. Um, and then technology. But I think we need to not start with problems that we’re looking at today where we think we have issues, but look to the bigger picture like first team principles right? So, what are we really all trying to achieve? We’re All trying to achieve growth, um, and cut costs right at the same time, and how do we do that? Thank you for staying with me; let’s do this. Last question, that I’ll, uh, get everyone’s take on, and we’ll we’ll probably end with that.

Udi Ledergor [ 00:53:17 ] * Most of you here are from smaller startups, I think, um, I think Carrie and I are the only exceptions of like later-stage companies right now, and I’m sure many of our audience members are currently either building their startups or working for startups. Amanda, you’re closing some big logos in tech, and you’re a smaller startup at one mind; how are you getting in the door, and why are these prospects thinking about bringing in a small player like you versus going to one of the incumbents in the space for their AI needs and and try to phrase this and and this goes for everyone as a lesson that our audience can take with them today how how can I as a small native AI startup make it big out there with large enterprises when there’s all these big incumbents around me that I maybe don’t think I can compete with yeah well I have an unfair advantage um so you know Carrie I I I I’m

Amanda Kahlow [ 00:54:11 ] I go back to it’s easy when I say I was the founder and former CEO of six cents it opens doors like that is just the just a simple fact for me um and I’m proud of everything That Six cents has done especially since I’ve left, they’ve done incredible things and it’s an incredible product, so I don’t think that’s going to help people out there, but I would. I go back to like my early days of Six cents and how we got that off the ground early. For me, it was always about building the relationship, so this is where the human aspect matters right? So in the early days, I would never I would host events, you know?

Amanda Kahlow [ 00:54:43 ] I started the Empowered Event at Six cents and it was never about selling Six cents; it was always about bringing together, creating community, and providing a space for people to collaborate in. a world that in an under they weren’t served in their needs they didn’t have that community and that connection so you know I’m always looking for opportunities to connect with people and have a human aspect and then that gets me in and I can have the conversation and say oh and by the way two weeks later can I can you connect me the right people on your team I can share what we’re up to right so it’s never the hard sell and it’s always really going back to listening to what their pains are right so instead of trying to like Hawk your solution every time it’s just listening listening listening listening that’s going to get you In the door here, take away right there, um, Gary, I think you started, oh, I’m just agreeing, yeah, I think that’s great.

Udi Ledergor [ 00:55:31 ] * Make it about the relationship first and pitch later. Matt, your take, um, I, I also agreed there, I, I think you need to be part of a discussion about something much broader than your startup too. So prior to founding Vivin, I was over at Zora, at the subscription billing company, um, I was there from nothing through IPO. I ran the global SE team and I tell that story because like when when the company started, we were billing and man, God, that’s boring, right? I was just kicking out invoices, but what they didn’t know so masterfully and He worked for Mark Benioff way back in the day too at Salesforce, and they’re just master marketers. And like that’s why people wanted to talk to Zoraa at an early stage was that we were the first ones out there helping you figure out what is ARR, what is LTV, like nobody defined these metrics.

Matthew Darrow [ 00:56:23 ] And even though it was a small startup, we were driving such thought leadership. It didn’t matter that we were small; I think that’s the same route that we’ve found ourselves in at Vivin. Is that like the world is clearly going a very, very different place, and it doesn’t matter how big or small you are if you have technology that Solves a problem, and you’re part of I would say a really important um like thought leadership wave uh that’s what’s going to help you not only build the right community around you but that’s what’s going to help you get in the door with very very large organizations because it’s not just hey you have a problem here’s my product, it’s like no, the world is changing, let’s talk about that.

Matthew Darrow [ 00:56:56 ] A huge plus one on that Matt. Before I move on to you Elizabeth, just to give the Gong angle on this which is very similar to what Zora did with the subscription economy, Gong did this with making decisions based on actual data from customers. Conversations so, when uh I started at Gong and needed to start creating thought leadership, we created the Gong Labs content series which taught the world that there’s all this data locked up in your customer conversations, and the data now shows us with the right AI analysis, before AI was cool, what’s actually working and not working. And that really created this groundswell of hundreds of thousands of sales professionals and sales leaders that wanted to know what’s working and not working on their teams, and didn’t want to use uh gut feelings and guesses to figure that out anymore.

Udi Ledergor [ 00:57:44 ] And that’s really what helped. US propel brand awareness for Gong and revenue intelligence as a category, that there is a better way than making these uh medieval style decisions of well this is how we’ve always sold so this must be working. Thank you, Matt Elizabeth, and then Glenn and Carrie will close us out. Yeah, I think we’re touching on uh something, and that’s really about how do you take emerging technology and create a new business model, a new way of doing things, and invent something entirely new. And that’s what we’re doing um with entrepreneurship at Start Stack is enabling founders who need to hire 30 people they can’t afford and We’re putting all that knowledge in a box so we can help people form their ideas, help them with their business plans or strategy their go-to-market, go much further faster while protecting their equity and capital along the way.

Udi Ledergor [ 00:58:33 ] And we want to bring new companies to market that are more investible and companies that are successful. So I think there’s a whole world of opportunity. I think I would completely agree with Matt that when you have a point of view, Amanda has a point of view. I love it, um, and and people will come along; they will go uncomfortably into the future with you, that’s the way to be strong. Point of view from Elizabeth, you heard it here Glenn, what’s your 30-second take? Yeah, well, basically I actually would like to ask Amanda a question because building relationships, I’m a strong believer in that; that’s also something we try to do. But how would you be able to do that with an AI agent? Ah, great question!

Amanda Kahlow [ 00:59:13 ] I actually think you can have a connection with an AI, which is why we move from Avatars to photo-real faces that and having more emotion and tone in the conversation with the AI. I’m not trying to fool anyone; our goal is never to clone and our goal is never to trick anyone-you always know you’re talking to an AI, but you kind Of let your guard down, and you start having that natural conversation. Um, and then it’s the point where we also have the ability to say, ‘Hey, now I want to talk to a person and she could spin up a Zoom and grab someone right and get on and be there, and then pass off on the Zoom like we just had this conversation.

Amanda Kahlow [ 00:59:45 ] So I think you still can build a relationship with an AI and have a connection, but you’re not going to go by the Bordeaux or take them to dinner, of course. Um, thank you, thank you Amanda; we are all done here. Carrie, sorry we didn’t get to your take on this last question. I want to thank my panelists here, Amanda, the CEO and founder of One Mind Math, CEO. And co-founder of Vivint, Elizabeth, the CEO and founder of Star Strike, Glenn, the founder and chief product officer of Expandy, and Carrie, who leads research and thought leadership at Sixth Sense. Thank you so much to our audience members and for the wonderful takes here, uh, I know we’re all happy to connect with you on LinkedIn, so happy to continue the conversation there, wishing everyone a great next session, thanks folks, thank you, they appreciate it. Welcome Caitlin,