GTM 2026 — Trends and Predictions Shaping the Next Era of Growth

Julia Nimchinski:
We are transitioning to our next funnel, GTM 2026. Welcome to the show, Doug Lendis, CRO and co-founder of StoryPath.
Doug Landis:
What’s up, Julia? How are ya? It’s good to be back.
Julia Nimchinski:
Very, very excited for this one. What’s the latest and greatest? What’s your top AI GTM prediction for 2026?
Doug Landis:
There’s gonna be a lot of consolidation. I think people are actually gonna start getting real value out of AI in 2026 versus a lot of the hype. That’s just my take. There’s been a lot, a lot, a lot of noise in the space, and it’s made things really confusing. I think we’re gonna get a lot more clarity, and people are gonna have real, real strategic kind of initiatives, that they can really execute on in 2026. It’s gonna drive real meaningful value. So, should be fun.
Julia Nimchinski:
Should we? Well, the stage is yours.
Doug Landis:
Brad, awesome. Well, I have such a great panel. In the interest of time, because we have a lot of discussions here. why don’t we just quickly go around the room, and y’all say who you are, and what organization, or what your role is, and what your organization is, and then we’ll just… we’re gonna jump right in. I’ve already given my hot take about what I think 2026 is gonna look like in the world of, you know, kind of AI go-to-market, but, we’ve got so much more to dig into beyond my… my… Measly little thoughts. Lisa, let’s start with you.
Lisa Sharapata:
Alright! Hey, I’m Lisa Sharapata, I’m the VP of AI and Go-to-Market Strategy at Metadata.io.
Doug Landis:
That’s rad. Look at that, VP of AI Strategy. When did that role start? Was that, like, a year.
Lisa Sharapata:
Yeah, I kind of made it up. So, I’ve been the CMO at the last couple organizations, and you know, it was just a completely, for me, like, I need to shift gears, and so let’s just change all of it.
Doug Landis:
Rad.
Lisa Sharapata:
Rad. I think we’re gonna see a lot more new titles.
Doug Landis:
Coming in, coming in the next year. Lee Margaret, Hi.
Leigh-Margaret Stull:
Great to see everyone. I’m Lee Margaret Stoll, and the CEO of Mural Software, which also includes Luma. It’s a services group that we’re also very excited about.
Doug Landis:
Nice. Nice. Hi, Claire.
Claire Maynard (Common Room):
Hey, nice to meet you all! How’s it going?
Doug Landis:
Great.
Claire Maynard (Common Room):
Claire, I lead the marketing team here at Common Room, and Common Room really helps go-to-market teams generate pipeline by understanding who to target, when to engage, and how to convert. So we sort of unify a lot of scattered buyer signals across the buyer journey into one unified person. Nice to meet you all.
Doug Landis:
A lot of people have been talking about Common Room lately, so congrats. Good to hear. You’re doing a good job. I was just talking about you this morning, in fact. Hey, Jay!
Jay Hallberg:
Hello there! Hello, everyone. Jay Hallberg, co-founder and CEO of Velocity Engine. We’ve been around for 2 years, helping teams go to market in minutes, not months, is our mission, so… Third time around the startup run, so…
Doug Landis:
That’s so fun. I love that. Minutes, not months. Sweet. You could take that in so many different directions, by the way. Hey, Mitch. Welcome, welcome to the call. Or the conversation.
Mitch Speers:
Wonderful. Hey, I’m Mitch Spears. I am CRO and co-founder at Buyer Foresight and a new venture called OMSI. We do event-driven demand gen for B2B companies worldwide, and I am really pumped to be here today.
Doug Landis:
That’s awesome. Event-driven demand gen, it feels like that is, like, a pretty hot wave right now. I mean, it’s interesting, because, like, even if you just think about events just in general, I feel like more and more people are interested in events, in live events, if you will, because, like, so much of what we do is over, you know, kind of this medium. But let’s… but we can talk more about that, but I want to kind of jump into the first question, which I think is a great catalyst for this overall discussion, which is, if you think… if you kind of zoom out over the last 12 to 18 months, what has changed in the world of go-to-market? faster than you expected, and perhaps more stubbornly, what hasn’t changed? What didn’t change at all, just over the last, like, 12 to 18 months? And you can… we can anchor in, like, where we think AI’s impact was actually overestimated or even underestimated. But I’m just curious, like, what have you noticed that’s changed the most in the last 12 to 18 months from a go-to-market perspective, either faster or maybe not so much? Who wants to jump in?
Lisa Sharapata:
I’ll go first.
Doug Landis:
Yeah, I was gonna say, at least I feel like you have a pretty strong opinion about this.
Lisa Sharapata:
You think? Well, it may not be what you’re anticipating, but I was anticipating a lot of changes in the go-to-market strategy, but what I didn’t anticipate was how much it was going to change how buyers buy so quickly, and so… the adjustments… I think that need to be made. aren’t just in your agenda go-to-market approach, but even reimagining, you know, how you… how you go about it. So…
Doug Landis:
Hmm.
Leigh-Margaret Stull:
I’m gonna jump in and just piggyback off of Lisa’s comment. That also parallels to mine. I think that, there are two things that I saw that was just super accelerated speed, probably already headed in this direction. But the… the workflow aspect of go-to-market teams and how that needed to be reimagined, it was surprising to me. It’s like teams picked off little bitty components of the workflow that they understood and owned, but it wasn’t really centered around the human or the customer. And to Lisa’s point, the skill set, now that customers can find so much information on their own, the expectation Around their interaction of the sales rep and the human, completely different than it was A year ago, much more collaborative, much more strategic in what their expectations are around the human. And that shift was already on its way, but it just happened so quickly with the ability to get content on really any product the customer might be interested in.
Doug Landis:
Right? Right.
Lisa Sharapata:
So if I…
Doug Landis:
The explosion play, right?
Lisa Sharapata:
Yeah, go for it. Oh, sorry. To say, even to add to that, so think about now, like, we’ve talked about the switch of, like, SEO to AEO, but also think about, by the time someone comes to your website. they’re so much further down, so then you gotta think about, well, how am I retargeting, for example? And I think that it’s that next step that gets missed. the… the, okay, now, when they come, it’s later stage, I have to change my whole strategy for retargeting, for example, yeah.
Claire Maynard (Common Room):
Yeah. The old now what? I think, too, like, I think it just… because there’s been this explosion of AI and outbound and being able to scale these channels, people have become, you know, deaf to that, and really, like we were talking about events, leaning into these very human-centered type, of discovery or learning, like, community, peer groups, events, and I think from a marketer’s perspective, it’s like, wow, like, we really need to pay more attention to those types of channels, and go deeper there, I think just because people are reacting to this explosion. And I definitely didn’t anticipate it changing. The buyer behavior so quickly, and kind of giving buyers, you know, the lead on their… their go-to-market approach and how they’re going to discover new products.
Mitch Speers:
I think it’s also, really raising the bar for go-to-market teams, you know, good enough isn’t good enough anymore. Since AI can do so much of the, sort of, just regular generic stuff. When you’re, you know, at the tip of the spear, a salesperson or a marketer engaging with prospect accounts. There’s no room for half-assing it.
Doug Landis:
Hmm. Meanwhile, by the way, meanwhile, reps still half-ass it. What Gartner said, 82% of reps still show up, you know, for conversations with their buyers, totally unprepared. what the hell is that all about? Like, you know, I think what we basically… one of the things we’ve identified is from a buyer’s perspective, their expectations are now dramatically different, because they have access to so much more information, and so when you show up to talk to me as a buyer, I expect you to be way beyond prepared. You gotta speak my language, you gotta understand my world better than what you’ve ever done before, because things have shifted, because I have a totally different perspective about what it is that I’m really trying to solve for now, and how I can actually go tackle that. And there’s so many more options.
Leigh-Margaret Stull:
Well, and I think that, you know, buyers are not buying products. They’re buying solution to problems, and sales reps that aren’t…
Doug Landis:
comes.
Leigh-Margaret Stull:
Yeah, they’re totally asking for speed to outcomes, and sales reps that are not going deep to understand their problems. The products are just an answer to a bigger pain, and I think the tolerance is low for pitching, demoing. They can do that on their own. They’re looking for humans that can actually deeply empathize and understand their pain points and their problems, and build a trusting relationship. So that they’re co-creating the solution along the way. They want to have a role in that, not be pitched.
Doug Landis:
Totally.
Jay Hallberg:
And I’d say from an internal perspective, so we worked with about 40 companies. A year ago, I think one of them had their own GPT or LLM. Now they all do. multiple ones, and so what, you know, hasn’t changed is still the humans need to approve, but we’re seeing a lot more of, how do we also coordinate those agents and ensure consistency? So that’s been a, you know. 20x, 20x run, and then I think, you know, probably overestimated where we’d be at from, like, an originality of writing.
Mitch Speers:
Hmm.
Jay Hallberg:
LLMs, and things are starting to sound and look the same, and probably also overestimated from where, kind of, image creation and content would be, but I think, when we fast forward and look at predictions a year from now, I think we’ll be stunned where all of that is.

Doug Landis:
Okay, so that takes me to my next question. So, basically, what we’re seeing is LLMs are moving, and AI technology is moving so fast, faster than most orgs can actually handle enablement. Mark was just talking about this in the last session, how, like, I think enablement becomes a huge unlock within an organization. So I’m curious, amongst your orgs, where are you actually seeing, like, AI move real… Revenue outcomes, how does enablement… how has enablement kind of played a role in that? And if you have any, like, real concrete examples, because it feels like reps just can’t keep up right now with the pace and the velocity of the tooling that people are actually either building or leveraging, and so it feels like enablement just becomes this big, big, unlock. if it’s handled properly. Curious if y’all have any examples of… of… of maybe how your… how enablement has actually really helped drive even more revenue in your organizations.
Leigh-Margaret Stull:
So within…
Claire Maynard (Common Room):
Go ahead, go ahead.
Leigh-Margaret Stull:
I was just gonna share, within… so, Mural is collaboration software, and our focus is really around alignment of teams. In a… in a way that’s visual, because visual is just… it’s just faster than text. And one of the things that we are seeing that enablement certainly supports, and what we’re doubling down, you know, from a focus standpoint for ourselves. is the motion around account planning. So, if we all agree that customers are expecting reps to show up and ask discovery questions and get to know them in a way that’s much more strategic. The step before that were teams internally, whether it’s the enablement, the SDRs, the AEs, in some cases CSMs. The alignment of those teams around the account plan and strategy, and what they need to focus on becomes more important, and that has been a very, very painful, and still is today, because every rep kind of does their own thing, or leaders do their own things. So that area in particular, being able to automate that through AI, is a huge unlock. Somewhere between 40% and 50% time savings is what we’re seeing, which obviously drives speed to revenue.
Mitch Speers:
Yeah, we’ve seen, you know, our approach to Agentic especially is… it’s very focused. It’s too easy to abdicate your job, basically, to the LLM, and… and that does not work, at least not yet. And so, we’re focused on… Giving our, especially our sales team. insights that are… that are real, right? Deeper research into the accounts, and… and what they’re struggling with, instead of just, kind of. vomiting their pitch at the next prospect the same way they did the last 10. We want them to go in there and impress the prospect with how much effort they’ve put into understanding them, as you said, speaking their language, understanding how their problem is different than, you know, 5 other companies that they directly compete with. And that’s where we’ve seen real value, and not only for us, but for our… when we’ve managed to drag our clients along that way. Conversion rates are noticeably improving as a result.
Doug Landis:
Yeah, go for it.
Lisa Sharapata:
At Metadata, we’re a digital advertising platform, and so we’re marketing to marketers, and the first step was everything internal. We all need to be drinking our own champagne, using that, and our sales reps need to understand it very deeply. of what is built into the platform, and how to talk to a marketer in a way that is gonna resonate, and I think more than like, more than most, I would say, marketers are some of the most skeptical B2B marketers, you know, because we know all the tricks, we know all the ways to twist something to make it sound good, and so there’s a lot of having to show it, and show results, and the sales team meeting to see it, so… we’re all in it all the time. The show and tell, it’s like…
Doug Landis:
show, don’t tell. It’s like, let’s actually pull this up, use it together.
Lisa Sharapata:
talk through scenarios and use cases, and just find that there’s… there’s a new Challenger Sale book out, can’t remember what it’s called right now, but it’s all about confidence, and I feel like that’s what the market’s really needing, and so do your reps. And so, the more you can build that confidence. through, like, real enablement scenarios and situations, I think the better.
Jay Hallberg:
Where we’ve seen it, I like to say, you know, sometimes in my experience in B2B and tech marketing is. Product marketing is one of the most important roles relative to enablement. an outcome, and it’s kind of been a forgotten one relative to AI and automation. So that’s something we’ve seen, is companies kind of increasing the velocity at which they’re planning campaigns, and if you can scale what product marketing can do in conjunction with enablement. hey, we’ve got an idea for something, let’s whip up good enough persona briefs, or can’t, you know, get this information in front of sales, because that… I think all of us who’ve done that role before, you can spend 3 weeks making those slides, so certainly seeing an impact there of giving product marketing more horsepower and a bigger seat at the table.
Doug Landis:
So interesting. Lisa, one of the things you were just saying is that, like, we live in a show-don’t-tell world right now. And I think one of the challenges from an enablement perspective is actually getting people comfortable with showing. Showing from a perspective of what your buyers are really trying to accomplish, showing from a… see, the last 15 years, when things were really frothy, people would just show product and be like, let me just show you what we do, and you’re gonna buy it, right? And now it’s actually, no, no, no, let me show this so that you understand how it actually fits in your workflow and changes the Experiences you can have with your customers. They get so much more wildly customer-centric. And I think that’s a shift that I don’t know if enough companies have actually done from an enablement perspective. I think from an enablement perspective, we’re still taking the old-school approach of, like, oh, let me just… enable you, train you on how to use the products, give you the pitch, give you the personas, do all the old school stuff, and we’re not actually being more advanced in terms of putting ourselves in the customer’s shoes and trying to identify what they’re trying to accomplish and how we can help. And oh, by the way, what other options they might actually have As well, we can’t forget about that.
Leigh-Margaret Stull:
Yeah, just to double-click on that, what customers are expecting along the lines of the empathy of their pain is that you understand and acknowledge it, and one of the things that I found most interesting in the last year, stepping into this role, were the use cases around some of our accounts. how they were using, that visual show-don’t-tell motion all the way up front, and just even documenting workflows for their accounts. And so that’s something that actually has inspired us, but very, very top Fortune 500 companies. And their motion is rapidly being evolved to really focus on the documentation of those pain points, because through that journey and process, as you’re co-creating with the customer, you’re building trust. And customers then trust whatever comes out. As potential solutions, because you’ve stopped to really unlock and allow the customer a space to think through all of that on their own. So, it’s definitely taking more of a consultative sales approach, which, again, was already in motion, but it is just rapidly accelerated and elevated the skills required For any sales rep in any team, whether, you know, that was… used to be sort of a concrete thing, and now it’s an expectation of anybody that’s calling on accounts.
Claire Maynard (Common Room):
Yeah. One thing we built for our go-to-market team is this internal kind of Slack bot, and so any rep can go in and say, hey, I have an upcoming meeting with a RevOps persona, they’re a PLG motion, you know, here’s what I know about them, here are the notes from my discovery call. And it’ll actually query and look at all of our Slack conversations, all of our Gong conversations. It’ll reference all of the product marketing materials that have been built, and be able to come out and give you this really customized, personalized way to demo, or pitch, or ask more discovery questions for that particular persona. And AI is just so powerful in the sense that it can synthesize all that information and find it immediately, so that’s one way that we’ve Being able to just use AI to really, sort of, it’s, like, in the background type of indirect, sort of. helpful sort of information for our reps that they can just get at the, you know, very, very, very quickly, so…
Doug Landis:
What’s interesting about that, though, is what a lot of people don’t realize is that’s actually still a pretty lagging indicator data. So it’s one thing to, like, it’s super helpful, because, like, you know, because so much… so much of the challenge our reps face is just context switching, right? It’s time management, and it’s context switching. It’s like, oh my gosh, I gotta jump on another call in 15 minutes. I need to get booted up on what’s happened in this account, or with these conversations, you know, over the last, you know, 2 weeks, three weeks, months, whatever it may be, right? It’s such… so helpful to give them, like, the context going into the conversation. It is also a lot of lagging data, though, because it’s like, oh, this is all the stuff that’s already happened, or this is the stuff that we already kind of know internally. within the organization, so it’s something for everyone to keep mindful, to be mindful of. One of the things I want to talk about is, like, the speed of adoption of technology. I mean, all of you in your roles, one of the things that we have to do as leaders is be really mindful about what I would call, like, whiplash, technology whiplash. I mean, there’s so many new tools out there that make so many promises. And, you know, it’s like, by the time you adopt something… I mean, adoption is one of the biggest challenges for all of our technology, right, that we all sell. It’s like, how do we drive adoption in an organization? How have you designed your go-to-market organization so that reps don’t actually feel the whiplash of constant new tooling and new technology, whether that happens on a monthly or quarterly or even maybe just an annual basis? What’s been your plan or strategy?
Leigh-Margaret Stull:
I’ll jump in. So, for us, we… we definitely, focused on… and it comes back to the… to the conversation we opened with. The whiplash for us was… was coming from… there was a period, and I think we were all in on this, where it was, like, just… rapid experimentation, everybody bring your AI tool to the party. And it allowed, you know, it allowed.
Doug Landis:
It became a hot mess.
Leigh-Margaret Stull:
Right, it became, like, a hot mess, and then…
Doug Landis:
You know, pretty quickly, the brakes started to get pumped a little.
Leigh-Margaret Stull:
But it comes back to. anybody that is allowed, like, completely, complete freedom to do that, and we’re not thinking through that entire workflow, it creates a cluster. So it’s ironic, because all of these promises of save time, or improved outcomes, etc. actually, you know, it’s actually a ginormous fail in that regard, and the recent MIT study sort of proved this out. Around 95% of AI projects are failing, and what was more interesting to me about that study wasn’t the 95% failing. That wasn’t super probably surprising for those of us out in the middle of it. But the 5% that were succeeding, it all came back to the humans that were inside that organization and how they were aligned across entire workflows to install AI and really reimagine what those workflows, entirely. should be. And so, I think there’s a lot of learning there for all of us around the 5%. And how we shift from just everybody bring their own rapid experimentation to how do we experiment as an overall org to get to a better customer experience overall.
Doug Landis:
Yeah. But it’s all… I mean, it’s so common, but it’s, like, the outside-in perspective. It’s like, what are we trying to accomplish? What’s the best way to do that? How do we not create the most noise or, like, whiplash or hangover for our teams, because we’re constantly making changes? Yeah.
Mitch Speers:
We’ve largely avoided that whiplash by simply not putting those tools in our sales team’s hands, right? We’re taking a conservative approach because we know that the tendency, the natural tendency, is gonna just, like, okay, just write my sequence. And tell me.
Doug Landis:
Oh, right.
Mitch Speers:
Right? And so instead, we’re… we made a conscious effort to control what we can control in terms of surfacing useful insights that they can use to then mold their pitch. In an effective way, but not try to make them build those prompts themselves. And the real struggle That we see is not so much that they’re… the whiplash about the technology, it’s the whiplash of the expectation that we now… the growing expectation of Can they start to think a different way? Can they start getting into a habit of connecting insights with suggestions about how we could engage with a client? And if they can’t do that, then that’s a real problem. That’s a bigger challenge for us than You know, the technology evolving as fast as it is.
Doug Landis:
I also feel like, and Lisa, I’m gonna look at you here for a second, I also feel like, and we also got a question from the audience, but there is this element of, like, you also, you need some… what’s the… What’s a way to… you need some government. In your organization, thank you. That’s the word I was looking for. I think every organization right now needs some level of governance. They’re like, we… here’s our AI strategy, here’s how we are planning to leverage AI within our organization so that we don’t get overwhelmed or inundated with, kind of, everyone bringing their favorite tool. I think You know, it was mentioned earlier that, like. that’s what we used… that’s what we did in the very beginning. I was like, let’s just kind of have some fun with this. It’s like, you know, the white elephant party, if you will. But now it’s like we need some more guardrails around what we’re looking at, how we’re looking at it, what problem we’re really trying to solve. So, Lisa, I’m curious, in your role, is this kind of the… is this a bit of the role that you get to play within your organization, is you get to be, like, the cops, if you will, the sheriff?
Lisa Sharapata:
Yeah, I mean, I think there’s both sides of it, so…
Leigh-Margaret Stull:
Lee and Margaret talked a little bit about that internal piece and the orchestration and rolling things out internally.
Lisa Sharapata:
And then, I think partially because we are a marketing technology and a marketing company. on the other side of it, I’m looking at even how our product is being rolled out, and how we’re doing things, which I’m trying to find more of. So the… you asked about, like, whiplash. I think the first thing is moving away from massive, like, quarterly product rollouts, and really having these more iterative, continuous. updates and tweaks, and especially since things are changing so quickly with AI and what you can do with it, it’s like, what’s the problem to be solved? And let’s reverse engineer that piece, and… solve for that. And then, if I’m going to be really specific with things, like with metadata, for example. we… they started building, the engineering team started building all these agents. We now have 71 agents. And it’s like, what is it solving for? What is it… But now they’re built into an MCP server connector, and we’ve sat through and gone through scenarios and use cases and documented What kinds of problems it’s gonna solve for, and kind of put them into playbooks, and prompts. and we’re packaging those and helping people to see how to use it, and it’s internal, too, because we’re using our own stuff, and I think that that’s… This proliferation of, like, all these… agents and things that you could do, and I’m seeing this in lots of organizations, an agent for this and an agent for that, but is this one talking to this and orchestrating this thing to create this desired outcome? And I’m seeing more people starting to think holistically, now that they’re understanding the art of the possible. And so I think, kind of going into next year, we’re going to see more and more of that.
Doug Landis:
Do you allow, and this is actually to everybody, but do y’all allow people to bring, kind of, new tooling suggestions to your organization? Do you have, like, a moment in time, just like on a quarterly basis, like, hey, let’s just show off the new thing that we just… that we just learned about? I can tell you, and just… just internally. anytime… that used to happen to me all the time, everywhere I’d go, and I’m like, you know what? I tell you what, I am gonna be… you’re like, show me, cool, we can have a conversation about it, but we’re not gonna share this broadly with everybody, because I… we need to keep people focused. We need to keep people focused on the job at hand, which is like, alright, how are we building pipeline? How are we getting our customers engaged? How are we moving our deals forward? How are we getting these deals closed? So I’m just curious if y’all are, like, still allowing the, kind of, the proliferation of conversations around new tooling, develop in your orgs.
Mitch Speers:
Yeah, absolutely. You know, the ideas come from all corners of the organization, and I think we’d be silly not to listen to it, but we also want to, you know, back to the idea of governance. There’s got to be rules in place to make sure people aren’t going cowboy off in all kinds of directions in ways that that affect, our business, or even worse, our clients negatively. So, controlled, but yes, we, you know, we wanna, we want to understand what’s the latest, greatest thing.
Doug Landis:
Right.
Claire Maynard (Common Room):
Yeah, absolutely. Like, we’re selling into go-to-market teams, so our own go-to-market team is the best dog food, you know, dog fooding experience of the product. So if they’re going and finding solutions outside of common room, right, we want to know what… what is that? Can we bring that back to our product team to understand what… what we… how we can improve that capability with our product? But, you know, we’re always trying to basically Dog food and ensure that our team is using our product, because it’s, like, the best insight we have into what’s working and what’s not.
Doug Landis:
I’m just…
Leigh-Margaret Stull:
piggyback off that with what Claire just mentioned, we’re in the same boat of, I call it drinking champagne. We like to drink our own champagne. But I think as you’re trying to build a culture of experimentation and curiosity, honestly, like, sales reps. And any, you know, successful leader in an organization, you want them to have that curiosity. You’ve got to be open. There’s a balance, to bringing new tools and suggestions. But we’ve gotten much more rigorous around starting with the problem statement first, and ensuring there’s alignment on the problem statement, and that the problem statement is a high enough priority to warrant solving for. on the list, so really, more consideration around, is there… is there overall alignment that that thing is really the most important thing that we focus on? Right. It’s always great to see, you know, new emerging technology and the way it’s being used, but that has helped us with With a more streamlined approach to what we invest in versus not.
Jay Hallberg:
And we do as… we do as well, and similar to Claire, you know, we sell to go-to-market teams. Just for context, I only have a couple people on the go-to-market team right now, so there’s less whiplash, and we’re in that, I think, enviable position that we can use caviar, dog food, our own software, and then look at… what are the, you know, what will it look like over the next 12 months? And so I think, you know, I’m also… very curious, you know, it’ll be interesting to see for companies like ours and others that are just building go-to-market now, how, you know, with a fresh stack, what does that look like? So it’s.
Doug Landis:
I’m doing it right now, and it’s brutal. Yeah. Because… because, by the way, there’s just so much… everybody says they do the same thing or something similar, and, The good news is I know I don’t need that much technology. That’s the great news. My cost for my go-to-market tech stack is very, very low. And it’s crazy how expensive everyone is charging for these products when I’m like, dude, I can build custom GPTs and my own agents and connect it to an MCP server and cost way less than what y’all are building out there. It’s kind of a little bit more fun. It’s hard, though. Not everybody can do that. Right. let’s… let’s actually… but one of the things that I’m really trying to solve for is workflow, right? So, in your point, in your case, Jay, you’re talking about how, like, we just don’t have a whole lot of people in the organization, so workflow really, really matters. Our friends over at RB2B, right? They’re like, well, if we can just… if we can accelerate workflow, we can actually build a really big company with very few people. What… and we just see right now, gigantic workflows are starting to really bend processes within organizations. and maybe ways in which we didn’t plan for. Maybe it’s because it’s accelerating the sharing of information from customer success back to product, back to marketing. What’s kind of an emergent behavior you’ve seen, either good or bad, by the way, from AI agents or automation inside your go-to-market motion that you… Been watching, or tracking.
Claire Maynard (Common Room):
I think maybe on a positive… positive one, it’s like, all this information right at a rep’s fingertips is making them more creative, right? Like, you’re not seeing the volume plays as much, because they’re able to access, you know, all this data about the person that they’re trying to reach. They can actually be way more creative, and maybe volume goes down, but that quality bar goes up, and we need to give them space to do that, because that’s the whole point, right? And so, when you can start to tap into all these insights and signals about your buyers, like, it only helps reps strengthen their strategic, you know, game, and we’ve noticed that in our own reps and in our customers as well.
Doug Landis:
I love that. You start to see the creative ones. You know, kind of push the onward.
Mitch Speers:
And that creativity usually leads to bigger deals.
Claire Maynard (Common Room):
Right.
Lisa Sharapata:
And I’m seeing that more on marketing, too, and frankly, I’m getting to be more creative.
Doug Landis:
than I have in a long time, but…
Lisa Sharapata:
Like, we have a bid agent that’s in there. adjusting bids all day long inside of our campaigns. No human really wants to wake up in the morning and do that all day long, and it does… it gets set aside, right? Maybe you go and check it every 48 hours if you’re lucky, if you have a resource that could do it. But now, if that’s happening, and I can just start to look at what’s working and what’s not working, I can start thinking about the next campaign, the next… you know, strategic thing I want to do, or let’s try this new art, because I think that, you know, we’ve already got the messaging dialed in, we got the audience now, you know, I want to try, you know, another version of it, and see if that makes an impact. And so. That’s… I feel like that’s what’s getting unleashed right now, and… the, you know, what comes from that, I think, is where it’ll be really interesting to see if it can get contained and structured in a way where it’s repeatable and scalable. And I think that’s where… you know, everyone’s hoping, well, especially the VCs and executive boards are hoping that this AI, you know, creates even more efficiency, but I think that we’re in this really messy middle part right now, where There’s so many things you could do, like, really trying to figure out what you should do is… what’s happening?
Doug Landis:
Yeah, yeah. And there’s also, and this came from the audience, but the idea of, like, okay, so if there’s so many tools available, especially in the world of go-to-market, how do you actually segregate and pick the right ones, right? Because, again, if everyone is bringing, like, everyone’s testing new tools and new technology, I think, I think, Lee Margaret, you mentioned the fact, like, it’s like, let’s start with a problem in mind, like, what are we solving for first? What are we really trying to solve for? We’re trying to solve for efficiency, we’re trying to solve for hiring, we’re trying to solve for capacity, execution, what are we really, truly solving for? And then unpack, like, okay, so what kind of tool… because the reality is, is we think it may be a tool, it just might be workflow. It just might be, like, we can pass data faster from, you know, from one side of the organization to the other. What are… what’s… how do you… how do you all unpack the ability to identify what’s the right… right kind of tool strategy?
Leigh-Margaret Stull:
I think for us, it comes back to, to our people, so just, you know, kind of piggybacking off your last, statement, like, in terms of emergent behavior for us, we’re seeing, and we’re also hearing from our clients, there is sort of, sort of a split. So those that were already curious, kind of, to begin with. It’s creating more opportunity, for increased curiosity, but there is another cohort of employees that it’s unsettling.
Doug Landis:
Right.
Leigh-Margaret Stull:
that now have to learn new skills, and the things that got them there, you know, got them here won’t get them there, so I think that that piece, like. I am really curious about the group that, that, will have to have some sort of reskilling. And setting that group up for success, because it still feels like that, like, curious few are leading the pack, and this goes to your last question, in terms of the decision making. That group is driving the decisions also, because they’re out there in it and come with a higher degree of information and insight around the problems and also the solutions, and usually it’s hard for them to separate. They’ve already identified the problem and have a form point of view on the solution before everybody else has come along on that journey with them. So that is something that, again, going back to Really identifying the problem, ensuring that everybody’s got a voice in that problem, and deeply thinking about not an already sort of predestined solution, but what are all the alternatives?
Doug Landis:
Yeah.
Leigh-Margaret Stull:
Have we really reconsidered the whole workflow and how it could be done? Are we just trying to rebuild existing workflows and plug AI in along.
Doug Landis:
Right? God, it’s so true. I love… by the way, I love that phrase, AI curious. We’re gonna… I’m gonna steal that. Because I think one of the things, to your point, that we also can’t forget is, like, have somebody go out and test it and prove it. Prove that it actually works, that it drives some level of efficiency, or…
Leigh-Margaret Stull:
Experiment with it. Go do that.
Doug Landis:
Totally. Don’t be afraid of that.
Claire Maynard (Common Room):
I think one… one thing we… noticed across our customer base when they’re experimenting with these new tools is they jump to the solution, the automation, right, first, versus really thinking about their data foundations, and do they have all the things set up and accessible and unified in one place before you go and roll out, you know, an AI SDR. It’s like, it’s never gonna work if that AISCR doesn’t have access to your sales force, is your Salesforce clean, right? So, I think that there’s a lot of this, like, let’s jump to the easiest thing that sounds really cool and sort of sexy, and it’s going to automate everything, but before kind of reflecting and looking at, you know, do we actually have the right foundation that can take longer, to be honest, to build out and unify, and that’s kind of the hard work that teams really have to look at.
Jay Hallberg:
Doug, I was gonna say, I love the, the use of bend in that question, because we all have our singularity visuals behind us, and I think, you know, something we’re seeing and thinking a lot about is really, you know, we think we’re going through kind of a generational change in what the UI is, and the experience, and so I think that is, you know, to me, something I’m looking at is, even as we evaluate, is sort of, you know, who’s thinking about how different it’s going to be, because I think it’s, you know, we’re finding a lot of the traditional application workflows, even that we’ve built in our own product. people just aren’t thinking that way anymore. It’s, you know, how does this all work in a highly interactive. Yeah. Chat-trained, environment.
Doug Landis:
Yeah. Well, and we’re still learning, actually, what the modern UX looks and feels like, and how it actually works most appropriately. I’m curious, do any of you have a strategy in terms of, like, where do you choose to, like, go buy a solution from a brand name that maybe, that’s more, much more familiar with or comfortable with, versus, like, a new, nascent… you know, small little AI shop that somebody’s built this new technology, versus building it yourself. So there’s, like, there’s, like, three pillars you could potentially evaluate when it comes to maybe trying to solve. for a particular solution in your organization, how do you all think through the, okay, can I just build an extension, or does Common Room have a new extension that I can leverage, versus actually going out and, you know, hiring an AI SDR, versus, like, going out and building my own custom GPT with MCP connected to my own data? Like, how do you evaluate those decisions?
Mitch Speers:
We’ve looked at… we’ve looked at all of those, and, you know, kind of stumbled a fair bit. And we ended up buying one piece of technology from a startup. where I just happened to, you know, have a relationship with the founders, so I kind of trusted them. And, you know, it showed great promise. It’s like, you know, mass personalization at scale for our outbound campaigns, and it was really impressive. But at the end of the day. It was meant for a different use case than ours, and we kept having to try to bend it to our use case, and…
Doug Landis:
Can’t do that.
Mitch Speers:
That was kind of an expensive mistake.
Doug Landis:
Yeah, yeah, that’s… It goes… we continue to say this, it goes back to, like, let’s get really clear about the problem we’re really.
Leigh-Margaret Stull:
You’re trying to solve.
Doug Landis:
Right? And then, like, alright, work our way backwards. Is it, like, can I use, like, a traditional SaaS product that has an AI, you know, kind of, bolt-on? Is that gonna be… is that good enough? Do I want to go through the process, and do we have the time and the capacity to actually go do a whole new evaluation? Yeah, it’s a…
Leigh-Margaret Stull:
For us, it was very similar. Like, it’s evolved a lot in the last 18 months. When we started, we definitely were… We’re curious about the small, very, very small startups, and really understanding what new tech… because there’s just a lot of inspiration to draw there, but as we got more centered around an approach of defining the problem, then you’re educated enough to say, well, could we do this with our own MCP server? Should we look at an existing tool that already has those capabilities and expand, or do we actually need Yet another, you know, net new, solution to plug in here.
Doug Landis:
Alright, and tool fatigue is becoming a real thing already.
Leigh-Margaret Stull:
That’s a question, right? Very, very real.
Doug Landis:
Do any of you have any frameworks or guardrails that you’ve implemented to prevent, actually, your AI-powered go-to-market motions from actually sounding really generic and not actually speaking to your buyer? Because that can happen, right? You know, there’s so many tools out there right now that are writing emails for scale, and you look at the emails, you’re like, oh my gosh, this sounds so terrible. You know, whether they’re… whether, by the way, somebody’s built that from their own custom GPT, or you guys have actually implemented tooling or technology, but do you have any guardrails or frameworks to evaluate, you know, kind of the output, if you will, of this AI, you know, powered go-to-market motion, so that you can determine whether or not it actually really matches the tone that you’re looking for?
Leigh-Margaret Stull:
I mean, some of that goes back to training of the model, right? So as we train our LLMs, we feed lots of content into it so that the voice and the tone and all of that sounds very much like we would want, and then on the back end, you’ve got to audit to see if that… not just the voice, but also if the content even makes sense. I mean, we’ve definitely seen hallucinations from, different tools, including our own, of the output, which at some point, a human at some point has to look at it to see, does what we’re producing make sense?
Doug Landis:
Yeah.
Lisa Sharapata:
Yeah. Totally. I think it’s important…
Doug Landis:
and Claire, what do you guys think, as marketers, like, how do you evaluate that they’re not, like, you know, tweaking your messaging or, you know, they’re outbound in a way that’s like, wait a minute, what? This doesn’t sound like us at all.
Claire Maynard (Common Room):
Yeah.
Lisa Sharapata:
I think it’s important to just first define, is it human in the lead for this? or human in the loop for this? Where are those stopgaps? Are you treating this agentic system as a workflow, and then it’s a human in the loop that’s checking things, or… Is it a human in the lead, let’s say for content creation, that has some agents writing certain things that needs to be checked, like you would check a new copywriter coming onto your team? And so, you know, I think as we start to build out more agents and agentic workflows. that kind of documentation will get created more and more, but I’m seeing best practices really starting to emerge around You know, human in the loop versus human in the lead, and… You know, figuring that out.
Jay Hallberg:
And we’ve done… we’ve done a fair bit with the agents kind of by asset type, all… so multiple agents working on assets with, you know, sort of human in the loop does this, human in the… or the lead, I like that, you know, does this, but then they have specific jobs that are checking on each other with grading rubrics against their jobs, and so… Nice. And so I think that’s… we’ve started to see good results in what we’ve produced around that, but it takes a lot of work to figure out what those rules are, and who’s doing… which agent’s doing which role.
Doug Landis:
Yeah.
Claire Maynard (Common Room):
Yeah. I was just gonna say…
Doug Landis:
Alright, Claire.
Claire Maynard (Common Room):
Sorry.
Doug Landis:
No, no, yeah, no kidding.
Claire Maynard (Common Room):
set up so that, you know, our marketing team and SDR team can actually work together on those plays, right? So we have different plays that each one is working on based on a campaign, and then marketing can actually set the tone and set the AI, you know, orchestration and prompting to make sure it works, but we’re always going to rely on, you know, an SDR to be in the loop and reviewing that. until we feel comfortable. And then, I think for the certain plays where it could be a little bit more simple, we’ve tested this a ton, then we can give, like, a thumbs up and say, like, hey, let’s review this maybe on a weekly basis, but we feel confident now that it can kind of run on its own. So I think it’s just kind of that crawl, walk, run, sort of framework that we use for different segments and plays that we’re running these AI agents through.
Doug Landis:
Smart. I mean, again, we’re keeping… we’re keeping humans in the conversation in all of this, so, like, all this pure AI automation is, is, like, I, yeah, I’ve… been thinking about this for a long, long time. When it was an emergency, we were investing in AI technology over a decade ago, and it’s like, human in the loop is so important, because we’re not gonna fully give up, although my friend Amanda over at OneMind might, you know, diff… might actually think differently. But let’s talk about metrics for a second, because this is an interesting question that came up, which is like, okay, we’re betting on, and Mitch, you even alluded to this, we’re betting on these new technologies from companies that maybe we don’t even know that much about. And the fact is, it’s still really early to determine whether or not there’s actually real metrics, or real impact, or even real case studies. So, how would you coach a leader to balance, kind of, speed, execution, investing in a kind of a new startup, versus experimentation, right, when the risks are really high? Because, like, Mitch, to your point, you said it earlier, like, if something goes sideways, all of a sudden you’ve just wasted all this time and money. Like, what’s changed now in terms of, you know, how you’re evaluating new technology, maybe versus before in the world of SaaS or even PLG?
Mitch Speers:
Yeah, I mean, we’re… we’re looking… At, you know, we’re re-looking at, pain points. And solving for customer challenges, not our own convenience. And… and… You know, it’s not easy.
Doug Landis:
Yeah.
Mitch Speers:
It really isn’t, but… but… I think that, The… Yeah, I’m gonna stop there, because I could go off a tangent, and I don’t want to waste everyone’s time.
Doug Landis:
I love that comment, by the way, of, like, there’s convenience versus solving for real customer pain points, and that’s, like, that we all have to be really, really mindful of that. Are we just solving because we want to make things easier for our reps, right? So they don’t have to enter as many fields in Salesforce, or they don’t have to actually do as much to create content, but is it really solving a real problem for our customers, or are we just trying to, like. you know, just make things easier for them. I think that’s an interesting… that’s a really interesting, checkpoint to evaluate. Anything else?
Mitch Speers:
Because, because we’re, we’re helping drive our clients, pipeline. We are a lot more focused on the notion of accelerating the velocity of opportunities. Yeah. Rather than, you know, we got… we got this many MQLs, this many butts in seats, yeah, fine, but how quickly… what’s the… what’s the increase in velocity from they showed up to an event to they actually became a customer, or at least got into your proposal? flow.
Doug Landis:
Right. Right. Another question.
Claire Maynard (Common Room):
Yeah, go ahead.
Doug Landis:
No, go ahead, Claire.
Claire Maynard (Common Room):
I was gonna say, like, thinking about metrics and, sort of what we touched on in the beginning is, like, you know, some of these metrics from outbound and MQLs and all of this stuff, like, just seem less important than overall, like, brand. But I’m like, from a marketing perspective, I’m like. Coming back to brand, and how do you measure that? Because it’s.
Doug Landis:
So hardly.
Claire Maynard (Common Room):
perception, right? Your perception.
Doug Landis:
No hers.
Claire Maynard (Common Room):
that is actually way more valuable and important these days because we’re not able to access that customer with the outbound, with the brute force. I think it just… if someone can kind of figure that piece out, that would be really helpful for us.
Doug Landis:
You know what’s interesting? Is this reminds me back to the earlier question in the very beginning, like, the last 18, or 12 to 18 months, what hasn’t changed? Guess what? Attribution hasn’t changed. It’s still really… it’s still really hard!
Claire Maynard (Common Room):
Not really.

Doug Landis:
I don’t care what AI tool you’re using, I don’t care what you’re doing, attribution is still really effing hard, and no one has really solved for this, and, you know, people are gonna be like, we have, but I don’t think you have. Because it’s still really effin’ hard, like, okay, cool, I’m on a plane, I saw a billboard, rad, now I’m gonna go check it out. If you’re in San Francisco, I’m in San Diego, we don’t see any AI advertising, so, like, I don’t know what’s out there. Question, as we’re getting close to time here, which part of, this is for all of you, which part of your sales process is truly automated today? And what’s still pretty manual in your process, and is there… and has there been a singular tool, besides Common Room, that y’all are using, Claire, that has actually really had a meaningful impact in your business? So, this is kind of a two-part question, I apologize. It’s a terrible way to ask a question. But this isn’t a discovery call. Is any part of your sales process, like, truly automated, and then is there other stuff, other things that are really fully manual, or still pretty manual?
Leigh-Margaret Stull:
So, we’ve automated fully, our SDRs, so we’ve got full agents, from that regard, and that was something that we invested in this year, as we were really focused on creating more of a land motion, than what we had previously. from a… from a more manual perspective, and there’s different things within… within certain parts of the process that we have fully automated in terms of support and Tier 1 and some of those things, which… You know, we were sensitive, too, because we wanted to ensure that we were still… service levels are something that are really important to us, and a key value. In terms of what we provide. But the piece that I don’t… I think that from a metric standpoint and what we’re measuring, to Claire’s point, the upper funnel metrics are all… I mean, upper funnel exploded, right? So, with… the movement from Google and SEM to GPT and all of the optimizations… it’s really hard to optimize anything in the current state, upper funnel. So, we’re… some of the vanity metrics, we’re tossing out the window, and in addition to the upper funnel, and Claire mentioned brand, the lower funnel is actually really fascinating to me in ensuring that our humans are getting with the right humans at the customer account, so we call those business sponsors. And that they’re actually having those strategic discussions that we know our customers expect. And so trying to get to metrics that are signals to us as to how well that’s going in each account is something that we are… that would be on the start list for this year, the quality of those discussions.
Doug Landis:
Yep. Quality conversations. You only got one shot. If you’ve got an Opti, you got one shot to differentiate yourself. So we talk about…
Jay Hallberg:
And we’ve got very far on the content creation by stage, we’re working on demo creation, a lot of the, you know, not enough volume through the pipeline to worry about a lot of that downstream, but that’s… we’ve put our focus actually more on the… those two areas so far.
Doug Landis:
Nice.
Lisa Sharapata:
And I’ll just add, we’re… completely reimagining that playbook, again, to what I was saying in the beginning, where now we’ve got, like, the basic Motion, it’s all automated, but now thinking about, okay, well, someone comes in from the website. that’s a late-stage deal now. That’s not an early-stage deal, and we can track if it came in through, like, ChatGPT, so they’re probably 80% of the way done with their sales cycle, and so that is a different conversation than it was… 9 months ago. And so that’s the part that we’re starting to work on. How do you track that better, take that as, like, the first-party intent. is a much stronger, way stronger signal than it used to be considered more of, like, third-party, keyword searching, like, doesn’t even matter anymore. You can’t even tell what they’re doing, right? They’re in a private LLM. So, like I said, I was, like, blowing it all up and saying, okay. those type of funnel metrics don’t really matter to me either. They never really mattered to the business. It was a way for marketing to try to show that they were making progress towards pipeline, and now it’s like. okay, they’re here, it’s pipeline, how are we helping accelerate it, and moving it through the funnel, and with a sense of urgency and personalization and you know, utilizing these AI tools in ways that really matter to the account and the people that you’re talking to, and are gonna help move that deal along. And I think that’s the… that’s the coolest part to me about this, is that’s more human than it ever was, I think, because you… you have this information now, and you can… you can use it to your, you know, advantage when you’re talking to people to be more human and make that connection, because by the time they come to talk to you now, they really do want to talk. They can buy most everything else out without you.
Doug Landis:
Yeah, totally. It goes back to buyer expectations.
Claire Maynard (Common Room):
Absolutely. I think that the really powerful thing about AI is the ability for it to synthesize data and understand who this person is. and do some of that background, like, research so that, like I said before, like, sellers can be more creative. But, you know, using AI to really identify one person versus, you know, it may be in your CRM, they’re showing up as a lead and a contact and all these different people that you don’t even know, you know, your sellers don’t even know if those are the right people. And so using AI to really be able to identify that person through machine learning and, you know, matching avatars and all this stuff that we can do with our technology so that when a rep reaches out, they know that’s the right person, and they also know everything we know about them, in one place. So I think that that’s how we’re… we’re sort of fully automated that piece of the pie, and it’s kind of like those background tasks That I think, you know, take up a lot of time, and we’re able to… to automate.
Doug Landis:
Cool. Last question in the last couple minutes here. What’s one thing you’re dead sure is still going to matter and go-to-market in 2026? No matter how crazy the tech gets, no matter how automated our jobs all become. What’s one thing that’s taken out?
Jay Hallberg:
Claire touched on brand, I think brand and narrative.
Doug Landis:
Yep, love it.
Claire Maynard (Common Room):
Deeply understanding customer journeys, you know, that’s not gonna go away, right? Empathizing with our customers and the pain points they’re going through.
Mitch Speers:
Getting in a room with… with your prospect. You know, and doing so in a way that the organizer is offering benefit first before expecting a return of their engagement in your event. And that kind of, you know, think about what’s in it for the customer first.
Doug Landis:
Before he…
Mitch Speers:
you think about what you’re going to get out of it, it works. It will continue to work.
Doug Landis:
So, what do you got?
Lisa Sharapata:
brand…
Doug Landis:
Okay. Lee and Margaret?
Leigh-Margaret Stull:
This, for me, it would be human alignment. I think that humans, will still have to interact with humans, and we’ll continue to think of AI as an unlock towards that, but helping humans, whether it’s with each other or with their customers, that human alignment piece will not go away.
Doug Landis:
And I will leave it with, the story actually matters. It’s no longer about pushing product and pushing demos, you actually have to be able to tell a story that builds empathy, demonstrates credibility, and it’s something that your buyers can actually tell internally, because 90% of the deal is done when you’re not in the room. guess what? They can’t retell all those speeds and feeds that we like to show everybody, so… Build out those stories. That’s connected to your brand, that’s connected to your value, that’s connected to, you know, how you solve things for other people who are similar, in a similar space.
Mitch Speers:
100%.
Doug Landis:
Julia, I think we… how’d we do on time?
Julia Nimchinski:
Love it. Phenomenal panel, so many questions, and Yeah, Doc, tell us more about what you’re building.
Doug Landis:
At StoryPath? What are we building? Yeah, you know, we’re solving for the fact that, like, enterprise deals are lost mostly based on the quality of research, narratives, and actions that reps take, so we built an AI Seller Action Hub that helps salespeople actually get real work done. Building the right narratives that actually connect to buyers, help them to understand, you know, how to actually align what they’re trying to do to their buyers so that they can actually craft a narrative together. I loved how Lee and Margaret, you keep talking about co-creation. I mean, that’s, at the end of the day, what selling really is all about. It’s about creating that trusted advisor relationship that we’ve all struggled with for so long, but now we can actually do that. That’s what we built.
Julia Nimchinski:
Amazing, and what’s the best way to support you? Where should our community go?
Doug Landis:
Well, me, just go to StoryPath.ai if you want to code, or just follow me on LinkedIn. And Claire, we’re gonna talk, because I think we need common room.
Jay Hallberg:
Yeah.
Julia Nimchinski:
Everybody go to a common room, and let’s just do a round of support.
Doug Landis:
Love it. Jay.
Julia Nimchinski:
Where should you go?
Jay Hallberg:
Pardon.
Julia Nimchinski:
Websites, LinkedIn, what’s the latest and greatest?
Jay Hallberg:
Yeah, a velocity engine to help you go to market in minutes, not months. We’ve got a campaign kit giveaway if you want to get started, so… Or LinkedIn.
Julia Nimchinski:
Awesome. Lee Margaret.
Leigh-Margaret Stull:
mural.co is our website, but obviously hit me up on LinkedIn. I’m excited to hear from anybody.
Julia Nimchinski:
Lisa.
Lisa Sharapata:
Yep, LinkedIn’s the best place to find me, and metadata.io for more information about metadata.
Julia Nimchinski:
Claire?
Claire Maynard (Common Room):
Yeah, I think you know, commonroomroom.io. Also, I love talking to prospects, I love talking to customers. If you have feedback, hit me up on LinkedIn.
Julia Nimchinski:
Amazing, and last but not least, Mitch?
Mitch Speers:
Yeah, LinkedIn for sure, and also, our two company sites, buyerforesight.com and, mzai.ai, either of those, I think… I think you’ll find it interesting.
Julia Nimchinski:
Amazing. Thank you so much again, and we are transitioning to our next panel.
Doug Landis:
Brad. Thanks everybody, you guys are great.
Jay Hallberg:
Thank you, bye.
Doug Landis:
station.
Claire Maynard (Common Room):
Bye.