Fireside Chat — Rewiring the Messy Middle of GTM

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Doug Landis: And we are transitioning into a fireside chat on the season.

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Julia Nimchinski: Welcome to the show. Zach Lendis.

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Doug Landis: This is… this is… come on, Julie, you know me, I don’t do fireside chats. We have conversations.

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Katie Nocerino: Oh my god.

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Julia Nimchinski: I… yeah, coffee talk.

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Doug Landis: Yeah, coffee talk. Coffee talk, exactly.

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Doug Landis: Exactly.

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Julia Nimchinski: So, I guess, like, I can introduce you now as the CRO and co-founder of StormyPath.

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Doug Landis: I mean, you kind of can, I mean, we’re kind of, yeah, we’re quietly coming out of stealth mode, if you will.

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Julia Nimchinski: Awesome. And we have Katie Nocorino, correct me if I’m wrong, Katie, but I believe I pronounced it right. GTM at One Mind, and we have a session here that our community was so excited about, rewiring the messy middle of GTM.

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Doug Landis: John, what?

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Julia Nimchinski: Welcome.

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John Brunswick: Hello.

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Doug Landis: What’s up, Johnny?

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John Brunswick: Ayy.

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Katie Nocerino: Yeah.

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Doug Landis: Julia was quietly leaking this idea that we started this little company called StoryPath, which is pretty cool.

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John Brunswick: Thank you so much.

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Katie Nocerino: your soft launch. Here we are.

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Doug Landis: Yeah, come on.

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John Brunswick: Kind of.

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Doug Landis: Yeah, kind of. I mean, Katie, it’s only appropriate because we were all together in Santa Monica, what, like, 3-4 months ago, when it was still… we were super stealth.

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Katie Nocerino: There you go. Yeah. Excited to see how far you’ve come.

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Doug Landis: Me too. Me too.

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John Brunswick: I’ll put the, background here, sorry. There we go.

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Doug Landis: It’s all good. Cool. Well, why don’t we… why don’t we kick it off? I’ll kick it off with some just quick intros and give everyone a little background. Katie, I’m sure everybody already knows who you are, because everybody knows what One Mind is all about.

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Katie Nocerino: Joe, why don’t we start with you, and then John and I’ll tell a little bit about our background, and…

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Doug Landis: And then we’ll kick it off. I have some really fun, interesting questions for us, because this isn’t a fireside chat, this is just a fun coffee talk about, you know, AI and the world of go-to-market and the messy middle.

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Katie Nocerino: Yes, grab your beverage of choice, and let’s… let’s get into it.

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Doug Landis: All of our friends in Europe, like, you can have a pint, it’s cool, no biggie.

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Katie Nocerino: Yeah, exactly, exactly. It’s 5 o’clock somewhere. I’m so excited to be here. I am Katie Nasciarino, and

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Katie Nocerino: Yeah, I hope that everyone knows about OneMind. If you don’t already, you will, soon, today. But I lead the go-to-market team here at OneMind. I’ve spent the last 15 years or so in go-to-market tech, starting with Responsys, back when we were addressing the campaign canvas, and then moving on to Oracle Marketing Cloud, Eloqua, worked abroad in Sydney, and then most recently.

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Katie Nocerino: At Sixth Sense.

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Katie Nocerino: Where we were really laser-focused on helping customers find buyers with predictive analytics and intent data. And now, you know, after many years of obsessing over how to improve the customer journey and helping companies scale as efficiently as possible, I couldn’t be more thrilled about what we’re building here at OneMind.

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Katie Nocerino: So, quick plug, we are creating what we call go-to-market superhumans. So they look, sound, and engage like a human, but the difference being that they’re on 24-7, they have no capacity limitations.

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Katie Nocerino: They are highly skilled and can go very deep on all of your products and services, and they can be trained to play multiple different roles across the go-to-market. So whether that’s a seller that is your best SDR and salesperson on the top of funnel.

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Katie Nocerino: a solutions engineer that’s in deal rooms or addressing the messy middle, which we will talk about in depth today, or post-sale, you know, engaging the long tail, where you can’t really justify putting a human, or supporting your customers. There’s a lot of exciting opportunity to help companies just scale, so…

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Katie Nocerino: Thrilled to be there, and yeah, excited to chat today.

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Doug Landis: It’s so interesting, as you were talking about all the different use cases, I was like, wow, that actually makes a ton of sense, because, you know, when we’re asleep, who’s working?

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Doug Landis: well, I guess Mindy is. Mindy’s working no matter what, especially when you’re a small company like ours. You know, where, like, when eventually we go to sleep, which is usually, you know, for John, it’s like 4 in the morning, but, you know, from 4 to 7, right, there’s a good little window where Mindy could help.

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Katie Nocerino: And part of the messy middle, like, people… it’s not their… it’s not their full-time job to evaluate software. It’s usually after hours, it’s on the weekends. So, we’ll do it, but yes, to your point, that’s exactly right.

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Doug Landis: That’s a good point. John, what’s up, buddy? Tell everybody who you are.

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John Brunswick: Store that.

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John Brunswick: Great, great to meet everybody. I’m John Brunswick, the CEO and co-founder of StoryPath, and I’ve spent my entire career figuring out the most compelling ways to communicate and share these technology solutions with buyers.

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John Brunswick: And along that journey, it’s led me into areas related to behavioral science, deep into technology and how companies are actually using it to align to their business needs.

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John Brunswick: And StoryPath looks at taking that difficult, messy middle and giving us, essentially, a GPS to help us navigate it. Something that, you know, at first, you think about the first time we all used GPS. It was a… it was a strange and novel experience, but soon we used it to go to the, you know, shopping mall up the street, and we’re asking ourselves, wow, why did I throw GPS on for it

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John Brunswick: this. But the further you go, and the more complex your route, it becomes really, really important to have that expert guidance. And so, if you think about the whole area of guided selling and allowing people to communicate in the most compelling way possible across that, that’s what StoryPath’s all about.

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Doug Landis: Red.

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Doug Landis: Awesome. Hi everybody, Doug Landis, co-founder of StoryPath with John, something we’ve been working on for a while. We’re not really fully… well, we’re live, we’re in market. Go to StoryPath.ai and check it out. I’m a sales professional wrapped in a marketer’s body that has been thinking about storytelling probably since I was 5 years old and took my first acting class.

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Doug Landis: And, you know, this whole notion of, like, story is… I fundamentally believe in this world where product parity exists across every industry, I don’t care what industry you are. Truly what differentiates you as a seller and as a human is both trust and story. That’s my core thesis, that’s our core thesis at StoryPath, and yeah, that’s what we’re all about. But this isn’t about StoryPath, this isn’t so much about one mind, this is about our thoughts on the messy middle.

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Doug Landis: And where AI technology can actually really fit into the world of go-to-market. Before I get into the first question, I want to share something that I read this morning, actually. It’s a study from OpenAI’s economic research. They did an economic research study, and they found it’s crazy, a staggering 70% of all consumer GPT conversations as of July this year were not related to work.

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Doug Landis: What were the most common things that were related to work? Writing, of course. All of our marketers, yep, there you go. BDRs, AI, you know, SDRs are writing right, using technology to write. But that’s dwarfed by the number of queries that are related to personal guidance and information seeking. It’s like the new Google, which is really crazy. And so if you think about that, I believe, like, this economic discourse that we’re all worried that AI is gonna augment or automate our jobs away.

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Doug Landis: maybe it’s not as accurate as, you know, the way in which we’re using, you know, AI technology for personal decision-making.

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Doug Landis: And so, the interesting thing is they broke down the categories of interactions, and I think it’s appropriate for the messy middle that we’re about to talk about here.

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Doug Landis: And what they found is most of the users using ChatGPT are doing three things. Asking, you know, seeking information and advice, like, okay, what, you know, what objections might I potentially face? What do I need to know about this customer? What questions should I ask in this conversation?

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Doug Landis: doing, or they’re actually requesting a tangible output, like, write an email, write some code, summarize something, whether, like, if you’re using Gemini or a notebook.

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Doug Landis: And then expressing, which is a personal reflection of joy. And so, what’s really interesting is, like, basically AI is playing this role as, like, an advisor. And so, if you think about, you know, kind of AI technology and go-to-market in the messy middle, it begs the question.

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Doug Landis: is there a there there? Like, does AI have a place in the messy middle? And before we kind of launch into that question, I think it makes more sense for us to kind of define the messy middle. So I’d be curious to how you both kind of define the messy middle and, like, what pictures come to mind, so we can get on the same page.

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Katie Nocerino: Yeah, I’ll hop in there. I think, the messy middle is, like, when you’re thinking about these complex.

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Katie Nocerino: consultative, often B2B cycles, it can get really convoluted. I mean, not only do you have a million different questions coming at you from 10, 15, 20 stakeholders, I mean.

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Katie Nocerino: There’s also reps. I kind of define the messy middle being

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Katie Nocerino: human-inflicted, like, self-inflicted. We withhold… I mean, it’s true. We withhold information, we’re desperate to maintain control, we throw food around at our competition, we plant landmines, we do all these things to just make people so…

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Katie Nocerino: confused, and, like, overwhelmed, and like I said earlier, it’s not their full-time job to evaluate software, so…

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Doug Landis: Literally.

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Katie Nocerino: end up just, like, almost by design, unintentionally, but, like, we’re all kind of, as sellers, like, trained to go do these things, run all the different plays, like, go methodically surround the buying groups, and,

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Katie Nocerino: you know, it’s… it makes it really tough to buy software, and so I think that is what explodes in the middle of a cycle.

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Katie Nocerino: it’s just this, like, insane amount of information. You don’t know who to trust or what to believe. And so I think of that as the messy middle, where it is really challenging to think about, like, okay, how do I… you know, I’m so desperate for control, but how do I now wrangle this all in and try to have an impact on

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Katie Nocerino: the outcome, the decision. So, that is kind of what comes to mind for me when I think about it.

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Doug Landis: Katie, that’s so crazy how… I think oftentimes we think of the messy middle as, like, it’s kind of… it’s buyer-driven or buyer-led because of the complexity on their side, but one of the things you just called out is the fact, like, oh no, sellers kind of make it really dirty, if you will. They, like, make it really messy, and so that’s another… that’s a great another angle and perspective about this, for this conversation. John, what’s your thought on the messy middle?

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John Brunswick: Yeah, I’m gonna give a hot take here that’s maybe a little atypical. I see a huge opportunity in the messy middle, and here’s why. Think about everything that is expected in a sales process. That’s happening in every cycle. As products race to parity, we’re looking at two things when we look at vendors. Do I trust these people, and do I want to work with these people?

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John Brunswick: And in the messy middle, when things get dynamic, when they get challenging, that’s actually our opportunity to shine and demonstrate that we deeply care about the buyer. And that’s actually where I’m so excited for AI technology, because I think we finally have a story to tell in a way that can make a difference, where classically, you just needed to maybe phone that expert and see if they were available.

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John Brunswick: So I just see a lot of room for, success and for new wins because of the messy middle.

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Doug Landis: So interesting. You both highlighted trust as, like, a core element to this middle, this… whatever kind of mess is created, whether by its rep or buyer or situation or economics, but trust is such an important element. I think the complexity in the middle itself is the fact that you… Katie, you alluded to this, tons of stakeholders, so lots of… I fundamentally believe one of the issues in the messy middle is problem alignment.

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Doug Landis: Everybody has different priorities, right? You’re talking to your buyers, and you’ve got… every deal over $10,000, there’s 10 to 15 people involved in buying decision. You gotta get everybody aligned on the problem, and how they define it, and, you know, how does that fit in their priorities? And so, you know, building that level of trust is so critically important. Katie, I’m sure… I’m curious, like, when you see… like, first of all, I guess, where do you see deals most often getting stuck?

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Doug Landis: And then, how do you… how do you unstick it? How do you unstick deals? And by the way, can Mindy help?

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Katie Nocerino: Mindy is our superhuman, for those that don’t know that. Every company we work with gets to, you know, brand their own superhuman.

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Doug Landis: Jeezable.

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Katie Nocerino: And my god, she is the best solutions engineer on sticker, if we’ll call her that. Yes, she absolutely helps to compress our cycles.

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Katie Nocerino: I think they get stuck where,

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Katie Nocerino: where we… buyers underestimate the amount of resources, time, effort that it takes to truly evaluate software, and, like, the amount of people they have to get pulled in to get this to move forward. So.

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Katie Nocerino: Where… and it’s funny you mention trust, because I always get asked, like, oh, will people trust AI? And AI is less biased than a human, a seller, with commission on the other side of things. So, like…

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Katie Nocerino: defining trust could be a topic probably in and of itself, but I would say that for us, like, Mindy helps to compress cycles because she’s available 24-7, and has deeply technical knowledge of our own product, and our case studies, and all of the FAQs, and our pitch decks, and all of that in her brain.

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Katie Nocerino: And so the number of times we see executive stakeholders that still don’t want to talk to us, or can meet, but in 3 weeks, they go talk to her on a Wednesday at 11pm, when my reps are…

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Katie Nocerino: sleeping, you know, that’s… that’s critical. We see them upload their requirements, upload their business case, go ideate on different problems that she can… that we can solve, and she is crushing those conversations, and then nicely packages it up for the reps. They wake up in the morning, and it’s like, oh my goodness, that was the call I was supposed to have in 3 weeks.

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Katie Nocerino: we managed to get that done. So, it’s about meeting the buyers where they are, when they’re ready, because the second you’re needing to align calendars, herd cats, all of that is, like, time kills deals. We all know that.

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Katie Nocerino: So, I think it’s just a matter of, like, how can you meet them in the moment they’re ready, whenever that may be, across 15 different stakeholders. Like, that’s where, for us, you know, the magic starts to unfold.

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Doug Landis: That’s… that’s pretty awesome. I think what’s interesting, I think in the world of AI technology when it comes to trust, it’s more about accuracy of information versus, you know, like, you’re right, a rep, you know, they’ve got some… maybe they have some alternative motives because they really need that commission.

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Doug Landis: You know, to pay their rent. So it is more a matter… it feels like it’s more a matter of accuracy of information. So, John, I’m curious, from a technology perspective, because you were the one that built StoryPath for us.

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Doug Landis: God bless you. Why do you think technology has avoided tackling this part of the funnel? The reality is, if you look at most of the world of go-to-market technology, it’s all focused on top of the funnel, which I would argue is relatively easy. No offense to all of our friends that are in the world of building AI tech for go-to-market.

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Doug Landis: But it’s like, there’s a lot of pattern recognition, like, okay, we know the companies you want to target, that’s your ICP, we know your buyer personas, now let’s craft some emails, let’s follow a pattern, whether it’s why you, why you now, or whatever it is.

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Doug Landis: Why is the middle so much harder, and why are people kind of… why have people kind of somewhat avoided it, I guess?

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John Brunswick: Sure. Well, if we think back to where SaaS anchors itself, it’s anchored in data and process. And when you have technology that is delivering something for data and process, how do you measure and work with it? In two ways. Activities.

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John Brunswick: and assets. But back to talking about trust and engaging with buyers, we know those critical moments where we genuinely earn a level of trust that, we rightfully earned, it’s because we were able to communicate and frame things in a really dynamic, challenging situation.

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John Brunswick: And the only tool that we had was our gut and kind of our own personal pattern recognition.

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John Brunswick: And so, I think in this era of all of this new technology, we, for the first time, if you go deep into it and look at how you can use it in novel and innovative ways, you can actually get to a point where you’re solving data and process problems that were previously unsolvable, right?

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John Brunswick: So if we look at companies, for example, like Cursor, that does development, or Harvey for Legal, these are companies that didn’t just wrapper in LLM.

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John Brunswick: they looked at using these as the foundation to genuinely create something that could deliver net new value. And I think this is the point that we’re at in these middle-of-funnel technologies, where for the people that are truly going deep and looking at how far can we press these technologies, we actually have the ability to deliver value that we just couldn’t before. So, it’s a really exciting time, because I would argue that

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John Brunswick: As you said, the messy middle is the most challenging, and you need something of a certain quality to actually deliver the right solution.

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Doug Landis: Yeah, yeah. You and I were talking about this yesterday, about the notion of, like, what Harvey does is really, it actually… it takes on a whole workload. It’s almost like basically creating a full lawyer on its own. You could argue that we do something similar at StoryPath for… in the world of… for revenue teams.

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Doug Landis: What’s interesting, though, is that everybody’s like, oh no, is AI gonna take away my job? But based on the study that we just… I just shared with you earlier, we’re not there yet. Are we gonna be there in 5 years? Probably, but, you know, we’ll see what happens in 5 years. It feels like right now, a lot of organizations are kind of really indexing on speed, right? Speed and efficiency, right? Everyone’s like, oh, I’m gonna use AI so I can drive more efficiency, we can do more faster.

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Doug Landis: What’s the cost, though? It feels like the cost of focusing on speed and efficiency is quality and depth. Do you think organizations, this is for both of you, are organizations over-indexing on, kind of, speed and efficiency, and are we losing the sense of quality and depth?

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Katie Nocerino: I would say what we’re seeing really commonly is that

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Katie Nocerino: everyone now knows they need to implement AI, but it’s more like, let’s just tell our teams, everyone go use AI,

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Katie Nocerino: And now we’re at this, like, sprawl of too much AI, and it’s all really inconsistent, it’s all unregulated, and everyone’s off doing their own thing. So I think we’re now kind of coming to this inflection point of… and to your point, like, yes, there might be an increase in speed.

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Katie Nocerino: But from a quality standpoint, it’s starting to get diminished, or it’s just getting really inconsistent. You think about a field team with hundreds of sellers, you can’t have everyone going and building separate business cases in Gamma.

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Katie Nocerino: Totally. I love Gamma, but giving it the ability to go, you know, create bespoke business cases all over the place. It’s awful for your brand, your narrative, the company, everything.

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Doug Landis: Totally.

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Katie Nocerino: Yeah, so I think we’re now at this inflection point where it’s more around, as leaders, we have to make the decisions, we have to regulate what’s happening, there has to be consistency across the field, and I think there’s always going to be a balance of speed and quality. AI enables both, but it just has to be

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Katie Nocerino: thought through, it has to be intentional, and I think there’s also this shift from being okay with incremental gains to now, like, well, no, with Agentic AI, we need to actually have AI that has a seat at the table, it makes decisions, it’s a part of the team, and it can drive real impact.

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Doug Landis: Yeah, we’ll talk about Agentica here in a second, because I tend to agree with you. Agentica kind of introduces a whole new layer of potential quality and speed at the same time. But John, I’m curious, your take on this, because we’ve talked a lot about

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03:18:16.400 –> 03:18:34.599
Doug Landis: Yeah, like, there’s speed and efficiency, but without quality, like, it goes back to trust. Like, if you deliver information to a rep that they don’t fully trust, if it’s not sourced within the last 30 days, if it’s like, if you’re not sure where this is coming from or why it actually matters, then the reality is, is why is a rep gonna actually buy into this and actually use it?

1151
03:18:35.260 –> 03:18:59.800
John Brunswick: Yeah, well, I think what’s interesting, what you just shared, in my mind, is actually the baseline. So if we think about the way that we’re starting to use the technology, you know, we upload a 10K, we write a prompt, and we get some data back. But the reality is that we need to take a full step back to reassess how we think about cost. And what I mean, classically, quality and speed were mutually exclusive.

1152
03:18:59.800 –> 03:19:01.449
John Brunswick: He kinda needed to pick one.

1153
03:19:01.500 –> 03:19:26.100
John Brunswick: In the AI world, I’m actually going to argue that the best vendors are gonna be able to deliver both to you. Because just having, again, the answers, that’s not actually the unlock. You need to go deeper and further. And when we think about quality, generally, again, that would be really expensive, but if you want to go fast, that is the only thing that’s going to help you to punch through a noisy market.

1154
03:19:26.100 –> 03:19:33.649
John Brunswick: Quality is actually the accelerant, especially when you get in the same amount of time and the same level of actual cost.

1155
03:19:33.650 –> 03:19:54.540
Doug Landis: Yeah, yeah. We often talk about, like, you know, the difference between data and direction, right? You can go into ChatGPT and ask it a thousand questions, you can build your own custom GPT or notebook, but that’s just data. Like, what do you do with that? How does it guide you? How does it contextualize the data into something that is relevant to the opportunities that are in front of you, so you actually get the benefits?

1156
03:19:54.910 –> 03:20:07.080
Doug Landis: Right? I feel like we feel like there’s a lot of benefit, because we get all this information pushed to us using an LLM, but the reality is, now I gotta go do something with that, and it’s not giving me the actual contextualized action to go take, right?

1157
03:20:07.080 –> 03:20:07.430
John Brunswick: I like that.

1158
03:20:07.430 –> 03:20:11.780
Doug Landis: news article. It’s just a news article for the sake of being a news article. Awesome. Thanks, I’ll find one.

1159
03:20:12.090 –> 03:20:30.399
John Brunswick: I’m going to layer on to that. I think, you know, the first time we used ChatGPT, we all remember it. It’s pretty freaking amazing, right? You type in a few things, and you’re like, oh my god, what have I unlocked here, right? But again, that… the more that you looked at the results, the more that you really spent time

1160
03:20:30.620 –> 03:20:36.059
John Brunswick: It wasn’t wrong, but if you’re an expert and you look at it, it’s not quite right.

1161
03:20:36.220 –> 03:20:49.759
John Brunswick: And so, this is an interesting kind of situation we’re finding ourselves in, and again, I think that’s why, for every vendor that’s going really deep into a specialty, they’re going to provide, clear and away, better value.

1162
03:20:49.760 –> 03:20:50.420
Doug Landis: Yeah.

1163
03:20:50.420 –> 03:21:09.810
Doug Landis: Yeah. Let’s shift here and talk about the agentic shift. This is an agentic AI conversation here, and this is, I think, where there’s real potential impact in this messy middle in the world of go-to-market. As we talk about, you know, Agentic AI, the first thing I want to do is just kind of define it and get kind of level set, right? So we’re all kind of on the same page.

1164
03:21:09.810 –> 03:21:34.789
Doug Landis: Agentic AI, we can think of it as proactive-powered AI approach, where generative AI is a reactive based on a user’s input, right? So, an example of generative AI use case is really all around, like, content creation and analysis, and then you’ve got Agentic use cases are really focused on, like, decision making and problem solving. And I think about Mindy as an example, as being, like, such a great use case or utilization of

1165
03:21:34.790 –> 03:21:44.099
Doug Landis: agentic AI capabilities. So, if you strip away all the buzzwords, and everyone gets all really confused, is it AI native? Is it agentic? Is it generative? Whatever it is.

1166
03:21:44.260 –> 03:21:49.680
Doug Landis: Where does Agentic AI actually fit into the go-to-market tech stack the best?

1167
03:21:50.020 –> 03:21:52.219
Doug Landis: Katia, that’s… that’s… I wanna ask you.

1168
03:21:52.690 –> 03:22:04.100
Katie Nocerino: Yeah, yeah, yeah, my take, great clarification, thank you for that. My take is, think about the outcomes. What are the outcomes we’re trying to drive? If we can improve the buyer experience.

1169
03:22:04.450 –> 03:22:16.360
Katie Nocerino: and we can drive impact for our customers and our own bottom line, great. Like, let’s not talk about, like, defining the type of AI, let’s talk about what we’re trying to do with it. So…

1170
03:22:16.440 –> 03:22:33.769
Katie Nocerino: for us, I mean, it’s pretty clear. It just needs to have a seat at the table, and the goal is to expand and scale exponentially beyond human capacity restraints. So I don’t want to just focus on how do we make every human on the team that much more efficient, effective, productive.

1171
03:22:33.850 –> 03:22:36.770
Katie Nocerino: I want to think about how do we create an autonomous

1172
03:22:37.460 –> 03:22:51.529
Katie Nocerino: in our world, a superhuman, that can go scale well beyond that. Put them where we can’t make justify having a human. Like I said earlier, it’s like the PLG motions, the SMB, the micro… Right.

1173
03:22:51.980 –> 03:23:13.130
Katie Nocerino: there are organizations that are so strapped. Like, I just read a report that customer success is, like, where the most turnover is in every organization, and it’s true. Everyone’s tasked with doing so much, so we need to create AI that has a seat at the table, and can, like, really, truly expand well beyond just making everyone that much more efficient.

1174
03:23:13.690 –> 03:23:14.290
Doug Landis: Yeah.

1175
03:23:14.780 –> 03:23:21.990
Doug Landis: John, what’s your take on the world of agentic AI? You know, if you strip away the buzzwords, like, where does actually.

1176
03:23:21.990 –> 03:23:22.340
John Brunswick: Yeah.

1177
03:23:22.340 –> 03:23:23.789
Doug Landis: In the go-to-market stack.

1178
03:23:24.360 –> 03:23:40.899
John Brunswick: Well, I think… I really agree with Katie, right? At the end of the day, it’s about delivering the best outcome. And if we think about the scenario where, let’s say it’s toward the end of your fiscal, you finally got the big meeting with the key stakeholder, and you get to pick up the bat phone, who are you dialing?

1179
03:23:40.900 –> 03:23:58.810
John Brunswick: That is the power of Agentic. You don’t say, I want the mid-tier player for this, I want the mid-tier player for… No! You want the absolute best in class for every facet of what you’re bringing to the table. That is Agentic. That’s where the value really jumps up.

1180
03:23:59.650 –> 03:24:24.079
Doug Landis: So, for reps… so, interesting question here by our boy John Barrows. So, if you think, like, I fundamentally believe that AI is a superpower for super-seasoned reps, right? Gives you the business acumen, you know, you can build on your experience, you can tap into your experience, you kind of know how to use the incredible nuggets of insight that AI can create for you, but let’s talk about how it actually is maybe helping or shaping a junior rep.

1181
03:24:24.160 –> 03:24:48.009
Doug Landis: a newer rep, an SMB rep that is getting into their career, and I worry about these folks who are coming out of college, they’re like, alright, I need to get my chops somewhere. I got… Mindy and I are kind of competing for business, you know, there’s all these great tools that I could potentially use, you know, to help me get booted up. How is AI helping junior reps? And by the way, does it matter if it’s agentic, or if it’s generative, or…

1182
03:24:48.010 –> 03:24:49.879
Doug Landis: you know, a bolt-on to a SaaS product.

1183
03:24:51.290 –> 03:24:58.960
Katie Nocerino: I think that, this might sound controversial, but, like, it can do the job of junior reps.

1184
03:24:58.960 –> 03:25:01.969
Doug Landis: So what you’re saying is we no longer need junior reps?

1185
03:25:01.970 –> 03:25:12.910
Katie Nocerino: There’s a bigger, you know, conversation that needs to be happening around, do we, or do we need to spend more time up-leveling them so that they can go have a more strategic role?

1186
03:25:13.820 –> 03:25:24.590
Katie Nocerino: They can… AI can do the job. It does the job. It does the things the junior reps does. Like, think about an integration with StoryPath that feeds those stories straight into a superhuman, and…

1187
03:25:24.760 –> 03:25:34.319
Katie Nocerino: it’s gonna do a pretty dang good job. So, you know, there’s… there’s a… there’s a… that’s obviously a very big conversation, not one that we’re gonna have in the next 4 minutes.

1188
03:25:34.330 –> 03:25:41.139
Doug Landis: But I think going back to the point around, you know, are we as leaders, do we want to.

1189
03:25:41.170 –> 03:25:49.760
Katie Nocerino: develop those people and have those roles, because we believe in those roles, and that’s what we want to do, and we just want to make them a little bit better? Or do we want to…

1190
03:25:50.010 –> 03:25:53.129
Katie Nocerino: Think about how we could augment our go-to-market entirely.

1191
03:25:53.560 –> 03:26:05.019
Katie Nocerino: by uncovering where there’s AI that can do the job, and then repurpose those people and spend that money and those resources in up-leveling them. So it’s a bigger conversation.

1192
03:26:05.020 –> 03:26:23.489
Doug Landis: Yeah, yeah, yeah, and John, I’m curious your thoughts, because you and I have talked about the fact, like, well, what if you do replace the junior reps, and you turn them into more, like, broader account managers? They’re there to nurture the relationship, you know, to shake hands, kiss babies, what you, like, build that connection that is necessary for, like, that’s necessary

1193
03:26:23.490 –> 03:26:32.729
Doug Landis: from a human perspective, because we all… we buy from people that we like and we trust, right? And so we want that level of relationship. John, I’m curious your take on this from a junior rep perspective.

1194
03:26:32.730 –> 03:26:57.220
John Brunswick: Again, I’ll try to keep this really brief. I think if we look back through history, we can see a number of reference points that directly map. I remember, this is gonna date me, I was in college, and Google came out, and I started using it for computer science. Some people looked at that, and they felt, is that cheating? You’re going and kind of getting all the answers. So, I think one of the biggest things with all this technology is the change management

1195
03:26:57.220 –> 03:27:01.750
John Brunswick: On the human side, and how we work will actually start to shift.

1196
03:27:01.750 –> 03:27:23.270
John Brunswick: The same thing happened with accountants when spreadsheets came around, right? What do I do now as an accountant? Last time I checked, there’s still a bunch of accountants. So, I think we have yet to kind of have the wave of change in how we work, and in a way, junior reps might almost be focused in a better direction, because they’re focused on the customer problem.

1197
03:27:23.510 –> 03:27:45.329
Doug Landis: Yeah. Katie, I have a question for you. This is a build on this, actually. And then, John, one last question about the Ferrari principle. So, okay, so Katie, if we’re gonna replace the junior reps with a product or an agent like Mindy, how do the experienced reps, or how, like, how do we fill that gap for reps to become experienced reps? Do you know what I mean? Like, where do their experienced reps come from?

1198
03:27:46.390 –> 03:27:51.109
Katie Nocerino: You know, I think… I think it was John Barros that shared the original question, right?

1199
03:27:51.110 –> 03:27:51.820
Doug Landis: Yeah, yeah.

1200
03:27:51.820 –> 03:28:05.019
Katie Nocerino: His role just got that much more important. Enabling people, like, they’re gonna get experience with experience. It’s not necessarily fair to say that if you come from a small company that gets our junior reps, you’re gonna have a… sorry, you’re the guinea pig.

1201
03:28:05.190 –> 03:28:14.690
Katie Nocerino: train them. I don’t know. You know, figure out another role for them. You mentioned account management, there’s strategic BDR roles that I think will still exist, like, there’s still definitely a place to…

1202
03:28:14.750 –> 03:28:25.270
Katie Nocerino: farm your next level of talent, but I also think there’s a lot out there in the form of enablement that can, like, help people up-level, and it’s gonna continue to…

1203
03:28:25.270 –> 03:28:42.230
Katie Nocerino: divide the workforce into, like, those that are really focused on their success, and they have the grit, they have the determination to go become an experienced rep with just fewer at-bats, and you know, we also have to take some bets on people, maybe. I think there’s a lot to still figure out, but yeah.

1204
03:28:42.570 –> 03:28:59.349
Doug Landis: Hey, so John, last question in the last 30 seconds here. You talk a lot about this Ferrari principle, right? So I think a lot of companies right now are thinking, like, oh, I can go build my own AI solution, my own agentic AI solution. Talk to us about, like, how that applies in the world of go-to-market, and how they may want to think about build versus buy. And Julia, then we’ll shut up.

1205
03:28:59.570 –> 03:29:18.119
John Brunswick: We’re in the early… we’re in the early innings with this technology, and if we think about application servers, word processors, and CRMs, there was a point in time which companies actually built their own. But then they realized it wasn’t a strategic advantage, and so if we think about race cars, they’re trying to build the best vehicle.

1206
03:29:18.120 –> 03:29:30.490
John Brunswick: They don’t build their own brakes, they don’t build their own wiring systems or paint. They work with the best-in-class providers. And I don’t know about you all, but I am not interested in the second fastest race car.

1207
03:29:32.790 –> 03:29:43.889
Doug Landis: I think that’s a really good place to end. We could talk for hours about this subject. The middle is complex. Agenda can certainly help, especially with one mind and story path at play.

1208
03:29:44.210 –> 03:29:45.330
Doug Landis: Appreciate y’all.

1209
03:29:46.010 –> 03:29:52.639
Julia Nimchinski: Appreciate you, too. Thank you so much, Doc, Katie, and John. Doc, before we wrap this up, people want to know.

1210
03:29:52.840 –> 03:29:55.719
Julia Nimchinski: Can AI effectively tell stories?

1211
03:29:56.290 –> 03:29:58.010
Doug Landis: We can help!

1212
03:29:58.010 –> 03:30:22.129
Doug Landis: Absolutely. So it’s interesting, we actually run our product against Gemini and OpenAI, and I tell you, I think there’s a real difference between just data. So, can OpenAI craft a story for you? Sure. Is it really contextualized about the opportunity, or the person, or the persona, the problems that they may be struggling with? No. So, that’s part of what we’ve built, right, is this whole guided selling and storytelling platform that actually allows you to build stories on the fly.

1213
03:30:22.130 –> 03:30:32.660
Doug Landis: Because story is truly the most human and effective way to communicate. So, yeah, there’s some nuance to the way in which you leverage these models to actually craft really, really compelling stories.

1214
03:30:32.670 –> 03:30:36.079
Doug Landis: If you want to know more about it, just go check out storypath.ai. Whaaat?

1215
03:30:36.080 –> 03:30:38.060
Katie Nocerino: Five! That’s it!

1216
03:30:38.060 –> 03:30:38.940
Julia Nimchinski: Awesome.

1217
03:30:41.000 –> 03:30:43.879
Julia Nimchinski: Can Mindy, support that, replace that?

1218
03:30:44.430 –> 03:30:49.249
Katie Nocerino: Honestly, she tells some really good stories. You ask her for analogies, examples, like.

1219
03:30:49.690 –> 03:31:04.960
Katie Nocerino: It empathizes, it’s… Doug, you say people buy from people they like and trust. I think they buy from the companies that get them accurate information, empathize with them as quickly as they can. I think it’s 78% of people buy from the company that reaches out and responds first, so…

1220
03:31:05.130 –> 03:31:10.700
Doug Landis: TV. That’s a… yeah, yeah, speed, you know, time kills all deals. I love it.

1221
03:31:11.310 –> 03:31:11.999
Katie Nocerino: But I think…

1222
03:31:12.000 –> 03:31:15.050
Doug Landis: We’ll do a bake-off between Mindy and StoryPath in our story.

1223
03:31:15.050 –> 03:31:17.269
Katie Nocerino: Yeah, let’s this integration making.

1224
03:31:17.410 –> 03:31:21.120
Doug Landis: Yeah, I totally agree. Amanda, you heard that. Yeah.

1225
03:31:22.640 –> 03:31:32.799
Julia Nimchinski: Thanks again, Doug, Katie, John. And we are transitioning to our next session. Scott Brinker and Carrie Cunningham. Welcome! The godfather of MarTech.