Video: Embracing AI for Sales Success with Revshoppe

The AI revolution isn’t imminent, it’s already here. These industry veterans (and old friends) team up to dissect the intersection of technology and human touch, and how to realistically implement it in your own organization.

Join Manny Medina of Outreach and Jason Vargas of Revshoppe for an in-depth conversation on the changing role of AI in sales, reflecting on the lessons learned from early sales tools and the present-day push for AI-driven strategies.

They explore the delicate balance between leveraging technology for efficiency and keeping authentic, human connections at the heart of the sales process. From the risks of misusing AI to the game-changing benefits of adopting it thoughtfully, this conversation covers it all.

If you're curious about boosting engagement rates, overcoming your fear of AI, or finding ways to seamlessly integrate AI into your sales strategy – you won’t want to miss this conversation.

Good to see you man. Good to see you too. You're aging nicely. Thank you, so are you.

It's just the pepper, salt and pepper happening in the video, that's good, that's good. It's getting more white. It's getting more white, but it's knowledge. Thanks.

Introduction to AI Challenges

The oldest knowledge is accumulated right here. So what's going on with AI? How are we gonna solve that problem? Let's talk about it.

Let's talk about it. I don't know if you remember that. So when we came to market, the main tool was, Yesware and Tout. And their trick was to bump an email.

You send an email, didn't get a reply, comes to the top of the inbox, follow up with this person. And that was magical, incredible. And then we came to the market, and we were like, this is part of a workflow. If somebody doesn't reply, you wanted to send the next email, or create an action, create a call, or say, stop, this is not working.

Diverse Approaches to Customer Engagement

And when we launched the workflows, there were two vectors, people who were very thoughtful about it, that you were, I'm going to use this to engage customers and get them to know me better. And there was others who were going to, like, I'm going to engage a million people right now. It is going to be awesome, and then burn their inbox, and then blame me for their domain reputation. So those are the two outcomes that we had.

And I remember distinctly that – because we only had 10 customers, and you were one of them. So I'm looking at people's results. And the way we used to work is, Kinser and I, we wake up in the morning and put all the customers on a spreadsheet and look at their performance from the night before, because we see the client performance, we call them to figure out what's going on. And you were rocking it.

You had reply rates of 50%. Nobody has reply rates of 50%. And then when we look into it, you had all these different steps of, go check out their LinkedIn, and then drop a note on LinkedIn, and then go back to email and tell them that you did that on LinkedIn. You had these nested activities.

And that's when I called you. I'm like, what are you doing? That makes you so successful. And that's when you told me what you told me.

The Importance of Authentic Connection

Yeah. I think at the end of the day, for me, I was really focused, hyper-focused, on how do I actually connect with a person, with a human? Even though Outreach was new back then, I didn't want them to think it was just like this some automated kind of thing. We were still accustomed to email marketing back then.

My obsession was, how do I connect with this person in a way that felt real and authentic? Because I knew if I could do that, and if I had the right message for them that would resonate, I'd probably get a response. That's what we actually started seeing. Because I think we A-B tested.

We found something that the market, or at least the audience we were trying to reach out to, we found something that was really, really important to them. And something that was like, yes, we want to talk. And so after a while, we actually – even at the first or second touch, they would respond with a book of meeting. But because it was, for me, it was the obsession first. How do I connect the person? Outreach just made it real simple for me.

I didn't have to stitch all these different tools and systems together. You guys made it a way where we can have more of a streamlined process to actually accomplish that. But I always think it started first with understanding what is it that this human being, and then the end of the day, actually wants, and can we fulfill it for them? And can my message resonate?

Understanding Personal vs. Corporate Sales Problems

And it's so interesting, because if you think about sales, you're actually solving – you think that you're solving a corporate problem, but you're solving a personal problem first. Because that person has to endorse you to become your champion and your helper before they introduce you to the corporate problem. And getting to know the person well allows you to have insight into what the personal problem could be so that you can go and solve the bigger problem. And it leads to a more strategic sale.

You were a data nice, and you were selling data. You can sell data very quickly. But you can also sell a very big package, because you had all these different silos of data that you can sell, and you're able to sell the entire thing as opposed to just one thing at a time, which is what most transactional sellers do. I think as the space has begun to mature, the sales engagement space has matured.

The Changing Landscape of Sales Technology

Even the category has changed names multiple times. I think what we've started to see is we have that whole people using technology to your earlier point. Just use it to burn the fields – or boil the ocean. And I think a lot of organizations, they look at technology –

I've said this to you before, but they look at technology as a means to the end or as the thing that's going to solve the problem. And so now, I think that even if you look at the market, the Martek landscape, just the sheer amount of tools in tech and software that has arisen within this space is staggering. People are always looking for that next thing of, what's going to solve my problem? What's going to solve my problem?

No one actually stops to try and understand, what are we actually trying to accomplish as a business? What do we actually want to do first and foremost? What is the problem we're solving? How are we going to do it for a human being?

The Need for a Clear AI Strategy

And then once they do that, then they can look at, OK, well, what technology can we actually use or leverage to help support this? I think partially it's because right now, I'm seeing a lot of pressure from boards and even other CEOs saying, we need an AI strategy for sales, or otherwise we're going to be behind. And so an AI strategy in absence of a goal is really incomplete. And it's going to end up in the wrong result.

And what ends up happening is that you rush out, you buy yet another thing. So now you have yet another tool that is going to be used or not. And if it doesn't get used or it's used poorly, then it's not going to produce results. And then you burn the one opportunity that you have to really empower your organization to drive with AI.

Misuse of Technology in Sales

And then you end up not solving the problem. On the other hand, it was really interesting. So when we launch Outreach, we have people like you who use it for a purpose. I want to engage better.

And then we have others who use it for another purpose, like, I want to prove product market fit. So I'm going to get a million leads. Put them in Outreach and see what happens. And then within a month, that domain reputation will be toast.

And yes, they will have a few customers coming in. But that was the wrong use of the application. And I'm seeing the same thing happening right now with the new wave. Well, it's the new wave of the clays and the 11Xs and whatever. You can use it for something really good. Or you can use it to just burn through a lot of things and just destroy your lead list.

Yeah. With the whole wave of AI happening, I think a lot of organizations want to adopt AI. Because there's a couple of things. There's that fear of missing out.

Right. But if you're also a organization that is not as mature as we can see in the tech B2B space, there's also a fear of being left out or missing out. And I think that's a huge fear. So I think that fear drives a lot of people's behaviors to want to just adopt it, even though they don't always fully understand how or where or why.

And I think that's why we saw this huge surge in AI that's now kind of retracting because they have it, but then what? You guys are experts in changing human behavior to adapt to new technologies that will give you to revenue efficiencies. What is your advice for a mid-sized organization or even a large organization to start embracing technology without burning the thing that is supposed to help you? Yeah, I think it goes back to my earlier point.

Identifying Core Business Issues

You have to understand, you have to take a step back and not think about the technology first. You've got to look at what is the actual issues that you have or what are the efficiency gains you're trying to achieve? What is it in your business that's not working or is broken that needs to be fixed? It's usually a human component.

And so the work that we do, a lot of it is around change management. How do you even think about a technology? Or if you have a problem, how do you actually solve the problem? And then how do you map that back into technology that's going to support what you're actually trying to achieve?

Organizations always miss that first layer. First layer is let's solve the actual – or let's address the actual issue that's happening within our business. Why we're not hitting another number, why customers are churning, whatever it might be. It's a huge human component. Then once you solve that, then the next layer is, OK, which technology can we actually bring in?

Or do we have today that we can utilize more efficiently to achieve the results? Then that last layer is to make sure it gets anchored within the business. So if you know what you're trying to solve, then you have to have a change management strategy or layer or process to be able to drive the change you're trying to achieve with that technology, which ultimately drives the change you're trying to have in your business. So what is the biggest pushback you get when you're doing this?

Overcoming Resistance to Change

This doesn't sound good in absence of trying to get this done in our organization. I think change is hard. And ultimately, as a human, human beings, are always resistant to change. And so I think you have to first achieve small wins first.

Once they see that and they can see something's possible, then it becomes much easier. The resistance becomes less. And so a lot of the success we're having with customers who are using Outreach, we first have to have that foundational layer. And we have to have a small win.

And once they see a small win, then just the change happens really, really fast. It's like this slow, slow, slow, slow, and all of a sudden, boom, this hockey stick effect. But yeah, change takes time. But I think organizations have to be patient.

Because if you have the patience and you do the foundational work and then layer the technology on top of it, it's game changer. The efficiency, the ROI, you'll get it. But you have to slow down a bit. One of the things that is also plays a big role in preventing adoption or success of technology.

It's not only, there is the impetus and the desire like I'm fear of missing out, but then on the Ops side, people who are running the shit, they also have fear of screwing up. We call it FOFU or fear of fucking up. And that fear is real and it's real because if you introduce a change and the change breaks something that you intended to break, then you're at fault, right? So, people are trying to figure out how do I not become at fault.

So, for those who don't have the benefit of your involvement, what would you recommend for operations and enablement team to drive a change and overcome that fear of screwing up? Yeah, that's a really good question. So, anytime we engage with the organization, they want change across the whole organization or globally right away. It's just, that's not the right way to do it.

That's where you're gonna have a fear of screwing up because it's gonna be so big. So, we typically start with a pilot team. So, we would recommend starting with a small team to actually prove out what you're trying to prove out. To be able to show like, hey, this actually does work.

So, then you have that win that you can then evangelize or vocalize within the organization. And if you fail, the failure is small. And you can iterate and it's multi. And so, instead of thinking of change globally right away, what is that small win you can do that?

Yeah, if you'd like you'd point to fail, no problem. Iterate change until you find the success you're looking for. When you have that, the next goal is you wanna get buy-in at the executive level. You wanna show them like, this is what's possible.

Here's like a sample, here's a taste of what's possible. Because at the end of the day, you wanna have an organization, you wanna build a team within the business that's responsible for the success of change. Like a center of excellence. And when you have executive buy-in and they see like, holy, like if we don't do this across the organization, like we're gonna be left behind or we're gonna miss out.

Once you see it, you cannot unsee it, right? So, it becomes from an ROI argument to a cost of inaction argument. Because now you see that it works and you're actively saying not to do it. Yeah, so it's even harder to say no to that.

Building a Center of Excellence for Change Management

Exactly, and so when you have all those pieces and you have a center of excellence, that team can be responsible to make sure any initiatives or any new technology that an organization does wanna bring, you have a team that's responsible to making sure that actually gets deployed correctly. But they can then work with the rep. They begin to show them like, here's the click path of how to use, Outreach, here's the click path to success. Or here's how we're gonna leverage AI initially.

But I think without having that process, like starting with a pilot, getting executive buy-in, building a center of excellence, you're gonna have a really hard time with change. You're gonna have a really hard time with integrating technology into the business in a way that you're hoping. You'll see small incremental changes with the technology, but you're not gonna see the actual change that you're hoping for. So if you take that forward, so you drive the change from say, no using AI to using some amount of AI.

Navigating the Shift to AI in Sales

And now the talk of the town is, is a genetic AI. So how do you go from just using single point AI where you're solving a problem, like writing you an email, to including an agent that is going to qualify a lead, or is going to go find the right person to engage with an account, or even engage that person in the account and get you all the way to the meeting. That's even more disruptive, right? Because now you feel like that's my job, and the AI is taking that over.

So how do you drive the change that is so core to what sellers believe is their job? In regards to AI, specifically. So it goes back to first, take yourself out of the conversation of AI or the technology AI. I think fundamentally technology is technology, right?

And AI has this really big hype thing that people are really interested in. But you first have to take a step back and ask yourself like, where do you actually want AI to make an impact, right? And so what we typically do is we have like a matrix essentially that we'll build out. And we'll look across the whole funnel, top funnel, the bottom funnel.

And we begin to map out what is actually happening at each stage from top funnel to the SDR, BDR functions, AE functions, CSM functions. And we look to see, where do you want to get gains? Again, go where do you want ROI? And then you can ask yourself that question of like, what needs to change or where do you want to have change?

But when you begin to build out the matrix and map against the matrix of what technologies do you have today against the whole funnel, you can begin to see gaps, right? So if you're trying to achieve something with AI, but you literally have no technology there already, you don't want to go from zero technology to all of a sudden AI. I think it's like, you're trying to crawl, you first need to crawl, but you're trying to like launch yourself to the moon. It's not realistic.

Assessing Readiness for AI Adoption

Right, right, right. And it also depends on the maturity of the business. Maybe they're not ready for AI, right? If there's no technology, then it's application selection, and then maybe consider automating, and then maybe consider AI after that.

But you have to think of it in a very systematic way. So building this matrix is gonna give you a point of view or lens to realize like what you actually have today and what you don't have. And what's realistic, what's not realistic. One of the things that I struggle is the fact that there is some problems that AI is almost the only solution.

So for instance, I was talking to another CRO about this particular thing. So this company has a product that they sell to a persona in 20 countries in two segments. And they have that, you know, that train works, it runs, they know how to sell it, they have the pricing and packaging, everything is dialed. They decide to launch two new products that are adjacent to the core product, but it doesn't sell to the same persona.

One, it's upselling to finance, the other one is upselling to HR, which they don't know nothing about. So now they have a new persona, a new buyer, and they have the same buyer in 20 countries which creates more complexity. And then the value proposition, the pitch, is still not quite dialed yet. Like they know what works, but it doesn't resonate the same thing for every single one of those, in every single persona for every single country.

So now you have, you know, two new personas, you have two new products, each of them with two new personas, each of them in 20 countries, and each of them needs to experiment. The combination of types of messages that you're gonna be generating gets up to the hundreds. You know, now you have 200 potential combinations of messages that you should be using, and no sales rep is gonna remember all that. You see what I mean?

You're gonna get into a conversation, and the person is gonna ask you a question, and you're gonna give it the one thing that you remember, not the 400 that you're supposed to remember, right? So AI is excellent at this, right? Like they can take all these potential combinations and then just create variety of messages, and then just give it to the person and figure out what works, and do the A-B testing. So not using it is almost criminal.

You know what I mean? Like not using AI in this situation, like it actually prevents you from solving the problem, right? So it's really hard to go from like not using AI to like using the full power going through the middle, because in the middle it's just a ton of work. You see what I mean?

So like you're literally losing all the benefit of AI by not using it. So how do you get somebody to see that light? The fact that by not using it, you're losing all these opportunities to land more deals. I mean, it's a big jump, so it's really--

It's a massive jump. And so it goes back to the fear of F and up, right? So I think most people don't want to take that leap because it's too big of a leap, the gap's too big. But then the alternative is even worse, right?

Like for instance, the alternative is what happens is that everybody develops messaging from the US and then you take that stuff to Europe and it doesn't work. And then your European team is all upset because you brought in your American flavor that doesn't really work. And then you take it to Asia, we're like, this even works even less. You see what I mean?

How do you bring it up? Yeah, I mean, and this is where people start using technology in not the best ways, because they're trying to just get things out, right? And so when we started looking at what was happening with the AI technology and people putting out all these new products and the want from the market to use these tools, but not sure how to use them, how to even think about them. So that's what we created the AI for quadrants, right?

Understanding the AI Quadrants

It was a way, it's a way for people to think about AI and how to ingrate into your business. So in this particular case that you're talking about, you're going from an organization that's probably, and if we look at the four quadrants, we have human. Why don't you describe the four quadrants for the audience here? So we have human-led and human-assist.

These are things that have always been done and still are done by human. Doesn't mean that it should continue to be done just solely by a human. The next quadrant is the human-led AI assist. So AI is assisting the human for its efforts to make it more efficient, maybe drive more insight to things.

The next quadrant, then you get more advanced. Like composing an email, right? Like you want to prompt the AI, you compose an email, the AI assists you. So the AI assists you with the email, but the human has to look and review it to make sure.

And then you have the human, assume the AI-led human assist. So AI is doing all the work. And the AI is, the human's reviewing the work of the AI. And then the final one is AI-led AI assist.

So this is AI doing everything. Doesn't need any intervention from the human. Humans trust it, it's good. So when we're going back to what you're saying about you have all these new products that are launches and there's so many, hundreds of variations of emails.

The messaging is. The messaging can be written. You have to understand where you are in the matrix the AI matrix in quadrant. Because if you don't and then you just jump, then you might make bigger errors.

And so I think that are just the, they don't know how to like activate it. Cause like using something like Outreach in general, like it's a great tool, but if you don't set up properly or align it to what you're trying to accomplish, it can become more disruptive at times. And so I think with AI, it's the same thing. So you got to understand where are you today, where are the gaps within your own capabilities as a business from a process standpoint, from a technology standpoint.

Mapping the Funnel for AI Integration

If I were starting from zero, going into 2025, this is what I would do. I would look at my whole funnel, right, and I would begin to map our quadrant against the funnel from human-led, human-assist, to AI-led, AI-assist, and begin to look at where are the gaps within my funnel that I want to actually bring efficiency to. And typically it's going to land on one of the four things, right? It's across technology, across content, across people, and then across data.

Right. So to map all that within the quadrant and then begin to stack rank, what's actually important to me from what I'm trying to accomplish as a business, as an initiative? Right, so you can figure out which one, you have the smallest gap with the biggest impact and prioritize that, because that's what's gonna be a quick win. Right.

And then you can wrap that into a pilot and boom, get it going, and then move into the next one. Yeah, so maybe it's something like, you know what, forecasting is probably the biggest thing for us. Right. So, okay, maybe that's where we wanna put our time.

Because look, the reality is, if you map your whole funnel against the four quadrants, there's gonna be a lot of work to do. Like a ton of work, there's gonna be tons of gaps. Right, right, right. Right?

So, you wanna identify, hey, well, what tools do I have today that can actually give me some efficiency that I'm not using today? Right. Versus, where do I wanna apply AI? Right, and so there's gonna be a lot of work to do, so you wanna stick with something.

So, if it's say, like, forecasting is a good example. Where are we today? Reality is, most organizations are still living in spreadsheets. Right.

Right, and so, living in spreadsheet, that's very human-led. Right, it's actually worth. Most organizations are asking the reps to give them a forecast without any backing, any substantiation, no evidence that the forecast is gonna end up one way or the other. Which is wild, that's crazy.

Which is wild, it's like, we're like, cars almost drive themselves, and the reps still have like, this is my forecast. (laughing) What world do we live in now? Exactly, and so that might be the place you wanna bring some efficiency and get those gains there. Right.

Leveraging AI for Effective Forecasting

In my opinion, if you were to think about your strategy for 2025, you start from zero, and you want to adopt AI in a major way that gives you the most amount of bang for the least amount of disruption, I think you start with forecasting. With a forecasting platform that gives you visibility into the deal, per se, because then you can see the visibility into meetings, deals, and accounts in a way that the AI is doing all the heavy lifting of telling managers or even reps where things are at so that you don't actually have to forecast, because a forecast happens by itself, right? The forecast, the deal and the conversations will tell you the probability of closing, and will tell you where you are in your Medpicc or in your Spinnen or whatever roadmap you are, and that is the easiest lift.

Get with a forecasting platform that is well-unified across prospecting, deal management, and forecasting so that you don't have to second-guess. I think that that will be the easiest lift. The hardest lift is having replaced what humans actually enjoy doing or think that they're good at. Remember when we were starting Outreach, people will do A-B tests of messaging, and they will pick their favorite message, and they will pick a B-test message that whatever marketing given, and sometimes a B-test message will win, and they will still use the A message because they like it or whatever.

They have some attachment to it or because they came up with it, and a couple people told them they love it, and that is completely statistically irrelevant, but they will still do this human behavior. So there is some human behavior sometimes that is counterproductive, where AI does not attach into anything, it doesn't have a family to feed, it doesn't have a job to lose, that doesn't really care. It's only optimized for the one thing that they're optimized for. So I think that that is the hardest thing in change management and transformation is to detach people from what they do and make them all just care about the outcome, as opposed to care about the values in the middle.

So I think the great thing about AI is that it doesn't care if it calls a rep out, it doesn't care about the emotional aspect, it's just showing you this is what's so, according to what we know, what data points we have. You've said that this deal's gonna close, but there's no history of the conversations in the last month. There's no activity aligning or pointing to the point that hey, this deal's gonna close. And so it's actually worse, it's like, you say this is gonna close because I was VOC, and then they went dark with you.

So the deal's not closing, and the VOC means nothing. And AI will say that, but in your heart, it was like, oh my God, I got the VOC, and now I've rendered a choice, and now we're gonna win. And they went cold on me, and I don't know what to do now. Like that deal's not happening.

Yeah, I think for certain things, taking out the human component, I think it is a benefit. I think when our ego's getting away, we wanna look good, we wanna perform well, but it can oftentimes hinder us. So I think that that is a powerful thing of AI, is that there's certain things that if we can take the human emotion out of it and actually show you what's so, in a way, it's actually bringing a lot of integrity into the business or into the performance as a rep. Actually, you can't hide behind anything anymore, so the integrity forces people to be more truthful or more honest, and so I think there's a lot of incredible applications of AI that people probably don't even consider.

The Role of Storytelling in Sales and AI

Yeah, you know what's really interesting, as you were saying, that I was thinking of the fact that, the way we sell is by telling stories. We tell a good story and people get become attached to the story, but that's also the way we fool ourselves, is by telling ourselves stories, right? And the stories is also our downfall. The fact that we can tell ourselves a story that, of course they're gonna sign, because they told me they're gonna sign, or the cause they're gonna sign because they have this pain.

Or my buyer told me that he's just going on vacation, coming back next week and we're gonna move forward, and then the person never gets back to you. So AI doesn't believe in stories. AI just looks at patterns and then tells you what the pattern indicates. So when somebody, if the yield velocity slows, we got communication slow, your deal is at risk, because historically that has happened.

So unless you know something that AI doesn't, that deal is at risk. And it's a much richer conversation, but it's a difficult conversation as a human being. Because going from one story to a story that is not the story that you had before, it's hard. Yeah.

I think that's where the growth happens. In organizations, going back to change management, it's the difficult conversations or the things you have to admit that you don't wanna admit. That's when change actually happens. And so I think with AI, it helps to bring the change organizations looking for, if they allow themselves or they allow it to do that.

And so with organizations who are wanting to integrate AI into the business, they at first have to actually be truthful, like where they are today. Right. And what they hope to accomplish that they're not accomplishing today, I think, but they have to admit that to themselves. Right.

So it's interesting because you almost have to replace the story of, I'm a rep, I understand my business, I know how this works. To another story, we say, I am great at talking to my customers, but the AI is better than me at understanding my business. Because AI can see all the different, all these other parameters I cannot see. I can see all the history of transactions for the life of the company and tell me where I trend compared to other things.

So we need to re-storyify ourselves. We need to recreate the story that we tell ourselves in the organization to say AI is here to stay and it's good for you. Yeah, and also embrace it. I think if organizations can use AI with AI-led and human assist or more human-led AI assist, it's like you get a superpower, right?

You have something that can actually support you. It's not gonna replace you. I think we're very far from that. Going back to the human aspect, the end of the day, humans are always gonna be able to connect better together versus AI.

And so if you can leverage AI to support you in being able to connect with that human, it's a very powerful tool. And so the whole fear of AI replacing, I think that's unrealistic at this point. So it's really interesting. So that guy that wrote that book, Gita Malik, that wrote that book, so he has his post.

So the latest post was on the strawberry release from OpenAI, so he tested it. And what it does is that OpenAI got a lot better at reasoning and then laying out the reasoning. So instead of just giving you an answer to the question, it will lay out what was he thinking about as a way to get to the question. So for instance, Ethan gave it a crossword puzzle and it asked him to go fill it out.

And then for each of the prompts, for each of the, there's a four-letter word that answers this question, blah, blah, blah, AI will do the reasoning in print. So it will print out how am I thinking about things to get to the answer and then what am I thinking about the next thing to go to the answer. So as the AI gets better at explaining themselves, the amount of trust that we have with humans will go up, because it's like a little assistant that is truly telling you what's going on. And the human trust will elevate and then you have an opportunity to tell a different story and get people to adopt it more.

Building Trust in AI Solutions

I think at the end of the day, trust is always a foundation in business or in sales. If a person doesn't trust you, they're not gonna buy it from you. And I think right now, we're kind of in the same phase with AI where there has to be trust with the AI, the human has to trust AI. Right.

Right, so it's like we're in a sales cycle and we're the AI seller and I was like, "Hey, trust me." And so that takes time. So we can't expect AI just to automatically, people are gonna adopt it for everything, or trust it enough to be able to give it more ability to help and support their own process. Right, right, right.

It's interesting because if you look at the way that Steve and Kobe defines trust, one of the components is that you say what you do, you do what you say you're gonna do and then you do it repeatedly. And as you continue to deliver on that promise, trust builds up. And it brings it back to the fact that the problems that we're solving with AI are not new problems. AI is new ways to solving the same problem in significant better ways.

Humanity as a Barrier to Adoption

But the rate limiter of our adoption is our own humanity. You see what I mean? It's like our ability to adopt change, our ability to tell ourselves new stories, ability to tell our buyers new stories, to their ability to trust. If that trust is not there and it's not explicit, adoption is gonna be hard across the board.

Yeah, it's so weird to do this over. Last time we did this was. It's 10 years ago. Next year house, 10 years ago, and they got better with more wine.

Yeah, three bottles of wine. Three bottles, and it was supposed to be a series, and I think we did one. We did one. That hit them right there.

10 years later, we found out. 10 years later, we finally did. It was good to see you, man. But it was good to see you, it was good to see you.

Staying Engaged in Sales

I love how you're staying engaged in the market, and it's funny that your brain doesn't shut off about this stuff. I think by now you've moved on into other things, but now you're still thinking about sales all the time. So are you. That's right.

All right, good to see you around.