s2 wrap up
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Ken Roden: [00:00:00] Hey crafters. Just a reminder, this podcast is for informational entertainment
purposes only
and should not be considered
advice.
Erin Mills: The views and opinions expressed our own and do not represent those of any company or business we currently work with are associated with, or have worked with in the past. for tuning in to the FutureCraft podcast. Let's get it started.
uh, uh, uh, um, uh,
Ken Roden: hey there. Welcome to The Future Craft Go To Market podcast, where we're exploring how AI is changing all things go to market from awareness to loyalty. I'm Ken Rodin, one of your guides on this exciting journey.
Erin Mills: And I am Erin Mills, your co-host, and together we're here to unpack the future of AI and go to market. We'll share some best practices, how tos, and talk to industry pioneers who are behaving the way in AI and go to market. So Ken, normally I ask you what cool new thing you're doing with ai, but [00:01:00] we're at the last episode of the season, so maybe we could talk a little bit about, what we did this season.
Ken Roden: I love it. Let's dive in.
Erin Mills: what surprised you the most about how things have changed between January and now?
Ken Roden: Okay, so real talk. I was really surprised when the season started. Some of the first guests we had, Jonathan and Liza said. We're not that far along and we thought we would be further along in this journey. But now that we're several months in, I think there's been a lot of news about how AI pilots aren't working, and there's been a lot of discussion about where AI's role and investment should be.
For companies, we're actually getting more clarity on what works around adoption as well as seeing things beyond just using AI to help you write an email. It's actually being used in sales and marketing in go to market to drive. Meaningful results around efficiency and productivity. [00:02:00] So we started out slow, but we got a lot better towards the end of the season.
What's your point of view?
Erin Mills: Yeah, I would agree. I think there were a lot of organizations that tried to do pilots that just didn't go anywhere. A lot of pilot purgatory, and I think that teams got frustrated with that. And so we saw that being a prominent theme that we heard a lot about. And the other wild thing is the accordion of tools. It felt like last year there was explosion of tools and then vibe coding became a thing, so people were creating even more and more tools available.
And then it's sort came back to reality, and now it feels like it's picking up again. I think that's been really interesting too, in the sense of there were a lot of organizations that were tool heavy adopters as opposed to focusing on the problems. I think that has really shifted.
Ken Roden: It's funny you say that because one of the things that I'm finding in my research is that companies who focus on the adoption aspect versus the tools aspect are seeing more success in these [00:03:00] pilots. it speaks to what you just mentioned Tools go in and out of fad, but teaching people the fundamentals around how to use AI and how it can help their job is what's gonna drive real change.
Erin Mills: Yeah. The other thing I think that's been really interesting and a shift from last season to this season, I'm curious to get your perspective on this, is it really is, less about, putting something into AI and just getting an output and AI being much more your teammate Liza is a big proponent of this and has been for a while, but are you seeing that in the folks you're talking to?
Ken Roden: Yeah, actually what I've seen is exactly that. It's using AI as a partner, so this sandwich model that we talked about earlier
Erin Mills: Love the sandwich model.
Ken Roden: a good sandwich, a club sandwich, if you wanna get specific, because humans are the bread. AI is the meat, your lettuce, tomato. And so humans start the work.
AI goes and does some tasks, comes back to the human to verify, and then the next steps follow that pattern. And so what's really been [00:04:00] powerful is people trying to see AI more as that partner, more as an assistant. My favorite one right now is an intern with a PhD who doesn't have any business experience, is the best name for AI right now. That's what I'm definitely seeing and it's been really exciting to see people, when they have that perspective, really dive into using it like an intern, which makes them feel more confident. Okay, here's one. I wanna dive into something that I want to call.
They called it. And it's where we have guests who made predictions about what was gonna happen. I want your take on if they called it right. the one that I'm really interested in is from Rachel Tru Air from simPRO. She said, AI SDRs are a win for a company. What's your hot take?
Erin Mills: Yeah, I gotta agree. I think she's onto something. My hot take is we're also experimenting now largely because of that conversation with Rachel that was at the time, not being done [00:05:00] effectively at a lot of organizations. I think we're still trying to figure it out Is it just emails? At what point is the AI more the initiator of conversation then at what point do you have the BDR and human in the loop? I think she's right. a lot of organizations are not there yet, and I think there's still work to be done,
I have one for you, which has been topic of many conversations of ours. We had Chase Hannigan on the show and he was talking about the no code agentic systems and N eight N and how that's the way of the future. What's your hot take?
Ken Roden: Okay, my hot take is Chase. Is brilliant and knows his stuff and I've seen him build incredible things, but I'm gonna call it that Chase is ahead of the curve on this one, on AI agents being usable by most people. it really comes down to something Sheena Miles said a few weeks ago that most teams are in this activate not accelerate, that people might be able to get some of the concepts around how [00:06:00] to build using N eight N, but it's too complicated and intimidating for a lot of people unless they're technical. What I think we're gonna see though, is N eight N in particular is gonna get a lot easier to use. Friendly user interfaces similar to what Relay has, that you can actually use agents to build the agents, and I think you're gonna see it explode. So I'm gonna say Chase wasn't wrong, he was just ahead of the curve.
Erin Mills: I like it. I would tend to agree, except I do love n8n and I think, there are tools out there that go to market teams are more successfully adopting relevance. We've talked about a lot on the show as well as Lindy, there's the crawl, walk, run, and I feel like those relevance and the Lindy's are in the walking and folks that are more in the N eight N are in the running phase.
Agree.
I got another one for you, which I really am interested in your take, especially as you've been doing all this research, and talking to different CEOs, Liza Adams said EQ is the edge. What do you think about that?
Ken Roden: I [00:07:00] am gonna say that it is the edge now we have hit the Edge, Seems to be coming up more and more, but in a different way than I was expecting. Liza said, you're going to need EQ more than ever because technology is gonna be so prevalent in our work that we're going to have to work more as humans.
Totally makes sense. what's been really interesting, talking to CEOs as well as talking to operators, think CMOs or go to market leaders. We're training their employees on ai. They're having to be way more human and way more thoughtful and aware about teaching people new skills because teaching people how to use AI is like teaching somebody how to do algebra.
Like it is foreign at the beginning, and you've gotta ease them into it. And so seen people lean into this eq, as a. Skill and demand. And actually, if you look at, job descriptions now for senior leaders in a lot of go-to-market [00:08:00] roles, they're looking for more soft skills at the top of the job descriptions than before.
It's starting to populate more. So we are in the new world, being human matters.
Erin Mills: it does matter and I think as a professional or a leader, a differentiated candidate because at the end of the day, we're going to have a lot more technical skills, and those are not necessarily the true foundation, but curious to get your take.
I think the EQ is incredibly important as a skill. I think the other one is, curiosity and understanding what. The problem is, or our favorite, Cheryl, quote, which is skate to where the puck is going. yes, she did get it from Gretzky, but I'm gonna give it to Cheryl as well.
I was gonna say the curiosity and understanding context, is equally as important as EQ is what I was gonna get.
Ken Roden: Yes. Completely agree with you and Cheryl. Curiosity is something that's going to take leaders as well [00:09:00] as all levels of employees into this next era of work. What about you? What's your take on this?
Erin Mills: I think that it's such a critical skill because ultimately we're all learning. something new, and if you don't have that curiosity or being able to identify the problems, squint into the future from our Grant Gregorian episode, last season, I think it's gonna be really hard for folks.
And so you gotta be a little bit more proactive on your own development and learning. And that comes with curiosity. Now I wanna switch gears a little bit with you. What was one AI thing that just did not land this year or broke?
Ken Roden: What was, a really good one. I'm gonna say what happened at the beginning of the year, all the AI vendor tools were just ridiculous. Everybody put AI on every single feature and product they had. And I think what happened to me is [00:10:00] what happened to a lot of people. They tried them and none of them worked.
I think what you're seeing now is. Real use cases having to be proven by these vendors. it's a really interesting time for vendors who have to show their stuff, buyers are getting way more sophisticated. So I'm gonna say the AI spray and prey market message is a fail for the year. What about you?
Erin Mills: I have a pretty controversial one. I don't know if you're gonna love this one. I know there are folks that will disagree with me. I feel like the custom GPT overload. Is something that is happening to a lot of organizations and I don't think it's good. It's having too many slack messages.
I think it's really hard to keep things updated. I think there are so many better ways of bringing in agents now let's say you use relevance, use a workforce and have all of those agents serving something that's, a little bit more, robust. I heard a stat the other [00:11:00] day, a company we both know has 600 custom GPTs and they're not a huge organization.
So how do you manage all those? How do you keep them up to date? Further, is that really the most efficient way to do business? Because I'm finding that since January things have moved in a much more streamlined way. It's not even a workflow from starting here, ending there.
It's this much more circular piece where we're learning and then applying that getting better and better. And I just think the custom GPT, I gotta say. it's great if that's what people have right now. It's like anywhere you're starting is great, but is it the best case long term?
Ken Roden: I agree with you. I find custom GPT super interesting because as an individual employee, if you have your arsenal of gpt you can get a lot done.
But to your point, when you're thinking about scaling. How many is too many and how many are actually that valuable? When you say 600, even if you told me 50 for, [00:12:00] marketing function or sales function, that's too many like it, those aren't team tools. Those might be individual tools, but that's not scalable.
And to your point, keeping them up to date, but also what value are you actually getting from them? one of the things I'm hearing, a lot of leaders their budgets right now are being asked by their CFOs is. How much business impact are we seeing from all of these AI tools?
Because implementing ChatGPT for your whole company is not cheap.
Erin Mills: Not cheap indeed.
Ken Roden: if your employees are just AIing all day, that's not really helpful. I'm gonna take Your call and agree with you, but here's a question around that. with all of this AI stuff happening, it is really scary for people to dive in because it seems risky.
one of the things that Rebecca, Shaddix said was define acceptable mistakes. what do you think some good guidelines or recommendations are to help companies think about what an acceptable mistake is to get them [00:13:00] comfortable with doing this type of stuff?
Erin Mills: I think it comes back to a lot of what we've been talking about with some of these guests where it solved the problems that you have. Look at some of the boring problems. Don't go for the sexiest thing. I think there's a tendency for us to get stars in our eyes when it comes to talking about ai, and it's like we're gonna automate the whole go to market process
It just doesn't work. When people think about acceptable mistakes, make the pilots about real problems that you have, and then also define, what are we expecting from this outcome? Also when do we call it a failure. sometimes like a stock,
or you get emotionally invested and just keep holding onto it. Sometimes you have to cut bait.
Ken Roden: Yeah. I wanna go into workflows because you brought up N eight N, and there's a lot of 'em out there. But what do you think shifted the game from workflows and agents?
Erin Mills: I think it's the accessibility and companies like Relevance and Lindy and others, where you don't have to be a technical person, who can implement these things and also make it. [00:14:00] understood across an organization. I think one of the things that I learned from Chase and n8n was really what is the foundation of an agent?
I think at the beginning of the year, all of us were scratching our heads of what is like a true agent do, and why do I need it, versus just creating a Zapier or other type of workflow. it really came together for me when I learned it's pretty simple.
It's like you've got your instructions for your agent, you've got tools, you've got a memory, and then you've got the brain, the LLM, and once you get your hands around that, and then the tools can also be other agents, it really helps to connect the dots because you can create a really powerful workforce or a system that helps you automate a lot more than you would've been able to, and certainly helps to define what the. Processes that you want, or in this case, workflow itself? What do you think?
Ken Roden: I think you said at the beginning of this season, that it's not really about the tool, it's how it fits into your system. to [00:15:00] me that shifted the game. It's talking about employees who were a year ago. Building workflows for them. But now companies and teams are building agents that make sense for the output they're looking for.
I agree it's the accessibility, but it's also the thoughtfulness of the orchestration. Think about this as a process and the output you're looking for verse, Hey, I'm just gonna use AI for AI's sake.
Erin Mills: Any other bus that you've seen this year?
Ken Roden: I'll just pour one out for anyone who rolled out a GPT or a LLM to their company and just had really bad usage because 95% of them apparently failed. it's been a hard year to say, Hey, you're rolling out ai. so I think that's one of the things you're gonna see next year a lot more companies being.
Way more thoughtful about if they haven't rolled out ai, how they're gonna do it, or if they have what their rollback looks like and what [00:16:00] they're reentry in. AI's not going anywhere. If it was this bubble would've bursted already. It's not. It's becoming part of our work. We just have to figure out how to land it with people.
Erin Mills: I was reading a stat the other day around 93% of people are saying now that they use AI at work, whether or not their organization has approved it.
Ken Roden: Wow. you and I called it really early on, digital twins are the hero of 2026. I will back this up by a research study that said that when done right, they can be up to 90% accurate.
Erin Mills: Wow.
Ken Roden: I'm like. That's a darn good digital twin. we use them.
I have people raving about their digital twins. It is probably my favorite low entry, easy use case for ai. Everybody should get a digital twin or a digital buyers group. Digital buyers group is amazing.
Erin Mills: Yes, totally agree on the digital buyers group. I think that could be the [00:17:00] winner for 20 24, 25. I do not think digital twin is gonna be the winner next year. I think we're going to do more agent swarms and workforces, and it's gonna be much more about what can the agents learn along.
What they're building and then apply that and continuously improve on their own. digital twins are great for people who have them I love that 90% stat, but I think it's gonna be swarms.
Ken Roden: Okay, I'll wait to be proven wrong, but I'm curious
Erin Mills: We can't always agree, Ken.
Ken Roden: Exactly what about, business impact, how are you hearing others talk about how. TGTM teams are best showing impact to prove continued use or increased budget for next year.
Erin Mills: It depends on the function, but if you think about go to market as a whole, one of the things is really the speed to market. if you think about, you have a product marketing [00:18:00] background where it would've taken months sometimes to get really robust tier one launches put together. And it could be really frustrating, like last minute changes from engineering or product.
And that really ends up pushing out your go live date. I think with ai. The speed to market has, improved exponentially, especially when you have, really good setups, good prompts, good agents, it makes that process so much more seamless. What do you think?
Ken Roden: Yeah, I would agree with you. I think that the two things that I've seen work are measuring a big goal. That you have and saying, Hey, we are trying to decrease the time to market by 10%, of an overall initiative. the other two things I've seen work really well are, having people look at their calendar individually and how they're spending their time.
Erin Mills: Yeah.
Ken Roden: And having teams actually look at how their time. Is invested and where they could potentially use [00:19:00] AI to drive an increase. And having them measure it, and it's been really powerful. The light bulb opens up for them. And if they do it as a team, then they're all bought in.
So then they can together build workflows and processes. So it's a little bit of, leading the group together.
Erin Mills: I think I'll have to revisit that with my team.
Ken Roden: It's really fun. Most people get really into it. There's been some research that is saying people are tired of hearing about wins only and they want to know about the failures. I have seen that come up with. AI training specifically where people will do, the best failure award.
they'll share the. Biggest flop that they had. And people will try to one up each other it's about taking pride in what's not working so that you know it doesn't work. And you can try other things I found it a fun way to build camaraderie and also not take this stuff so seriously.
Erin Mills: [00:20:00] One more thing to bring up is really the analytics. And insights themselves. in the past there's two pieces that I think have been really hard for folks.
One is if you're not an analytics, aficionado, it can be really hard to get your insights without leveraging a data scientist or somebody else on the team who has that expertise. AI has really unlocked that for a lot of folks, and think about Salesforce reporting in the past and you had to build, 10 different reports to get.
A couple of different insights, whether it's, win rates for a particular industry or velocity it was really hard to get that all in one place and without having to do several iterations of something. You don't have that barrier, which is really incredible.
So you think about time saved and business impact. If I can get smarter about what I'm doing understand what's working and what's not, and where to make more investments, and I don't have to spend, weeks or months to figure that out, that's pretty powerful.
Ken Roden: Yeah. Oh, hey. I actually caught up with a, executive circle here in Boston a few [00:21:00] weeks ago, and they had a question that I meant to ask you. I know that you're in quite a few communities for leaders. How are leaders using AI in ways that employees might not be? And the reason why this came up was, I talked to specific executive and they said, I love how my employees are using ai, but I'm not building go to market plans or campaigns or content, but could I use AI in a meaningful way?
And I was like, let me get back to you 'cause I've gotta talk to Erin Mills.
Erin Mills: Yeah, I think the spectrum is pretty wide on that. you have the folks that are just dipping their toes in and starting to use Chachi PT for the first time, or building their first digital twin, and maybe the first digital twin is not that great. And then you have folks that are building their own, agent tech workforces
I think it really depends on how comfortable you are with diving in. For me personally, I love getting my hands into the AI tools and understanding really what are the mechanics of making them work. and I think it really depends on the community too. For example, Chris Penn's analytics community, [00:22:00] they are talking about things that are much more advanced than you might see in, other communities that are a little bit more generically focused
marketing as a whole. it depends on how comfortable somebody is in working with the tools. you can make it as big or as small as you want. to the leaders you're talking about what are the problems that you're trying to solve for?
And if you're looking for, Hey, I need to understand whether this strategy is viable or not, you certainly can leverage AI to help and do a lot of deep research, which really came on this year in a big way,
Ken Roden: Deep research.
Erin Mills: Tell me, what have you used deep research for that you've been most excited about?
Ken Roden: the thing that I have found deep research to be the absolute best for is understanding yourself because deep research is able to take a look at your brand persona but also able to look at. Whatever you feed into it, it can analyze and benchmark you. I've used it to help define brand voices for [00:23:00] individuals, for founders in their go to market as well as companies.
So assess my brand positioning. help me understand how it fits into the market and where there's white space deep research is really good at telling you the holes you can't see. I'm amazed by how accurate and Believable. It is. one of the obstacles when doing things like deep research, which is a little bit like a black box, is executives believe it because it is sourced, but the way that it's presented is logical.
It's not hallucinating. It's spending the time to really think about it. that's been the biggest one I've seen. How about you?
Erin Mills: Yeah, I think that's a really spot on example. Chris Penn, came on and did a great example. Getting competitive analysis insights in a way that's so much faster and so much more in depth than before, I think is super powerful. Aside from just deep research in general, goes to trust.
And what's really interesting is our [00:24:00] conversion rates on. Prospects coming from LLMs is so much higher. They spend 600% more time on our site than if they came from a more traditional, direct or paid search. I find that interesting because it's where we feel that the AI is delivering a more accurate response than if we just did a single search alone or deep research taking that into making buying decisions. might be the key takeaway of the year.
Ken Roden: I wanna talk about next year, if we're looking at 2026, what's coming that GTM leaders need to think about now?
Erin Mills: So I'm gonna go back to the preview I gave a little bit earlier. The agent swarm workforce, whatever the term is going to be, it's creating agents who are really good at something very specific, being able to leverage them for multiple things so that you have this motion that all works together.
if you think about the example that Chase Hannigan gave us with the assistant. Agent that he built [00:25:00] you start with the top level agent who is the project manager and decision maker, then you have an agent that does email and calendaring and then you have, all these expert agents.
It's like that, really smart college graduate that comes to you. if you give them a giant project to do, they're gonna fail. But if you give it something very narrow and they're smart and they are equipped with the right tools, probably gonna have a much better result. It's similar to what we learned last year in terms of prompting and making sure you know how to prompt.
I feel like we've gone so much better than just learning how to prompt it's a piece of the sandwich. It might be the lettuce, but the other pieces to the sandwich and all the other accoutrements are the tools and the brain and all the things that go along with it.
Along with giving very clear. Instructions on what the outcome is that you're trying to get to. And coming back to the whole agent side of it is what the agent learning and iterating on to get better and better? And that is, I think, where we're going. But what do you think?
Ken Roden: [00:26:00] So I've got two, I think we're going to see the emergence of closed. LLMs specific to companies. I think companies are going to want their own closed environments and, anthropic and Claw are going to start selling them way more, actively because there's just so much out there and employees are using it so much more.
We're going to see these closed instances, which is then going to allow companies to think about knowledge management in a way they haven't Before Claude came out with skills this past year. It's been really incredible to think about even writing a job description.
Erin Mills: Oh yeah.
Ken Roden: people, write job descriptions, that's one of the biggest pains a manager deals with.
It's now simplified with this one skill. The other thing is related to what you talked about. I think we're going to see a shift in how organizations and teams are structured. I think we're gonna see a lot more employees or contractors, fractional talent show [00:27:00] up with their own team of agents and maybe one or two other employees, and they're gonna come work on a project Specify everything to your team, and then when it's done, they're out of there. And that, I think is actually where we're gonna see new roles emerge of these like fractional ai. Go to market experts in different areas. And so it's really gonna take into what you said as well as the people aspect. I just think there are, there's a growing community of AI enthusiasts who have learned how to fine tune their trade around, go to market, and they're gonna be so valuable that they're gonna be plugging in and working with companies, and maybe they'll sell their agents as well, but we're looking at a, I think a new industry and ecosystem.
Erin Mills: It reminds me of something that Coach said during our interview with him where he was talking about coming in and being Iron Man and plugging in the Iron Man suit. I think that's what's gonna happen. the SaaS industry as a whole is ready for a shakeup functions within go to market are as well
Coming to the [00:28:00] end of our recap episode. Wanted to get your take on a few different things. Is that all right?
Ken Roden: Yeah,
Erin Mills: Okay. What was one thing that you changed your mind about this year?
Ken Roden: AI and SDRs, I would totally bet wrong on that. I thought it was completely over promised and committed, but, since Rachel came and actually shared some results, I've done my own research and it's very true and it's again, complimenting the SDR role.
I totally got that one wrong. What's one thing you changed your mind about this year?
Erin Mills: I think I'm gonna go back to the GPT thing where, it was such a huge thing last year and for me it's just. It's the what's the next thing? And the next thing is more on the agentic side. I think the other thing, that I really actually love, and it's not necessarily a changed my mind from an AI perspective, but I think just as a industry as a whole and marketers [00:29:00] or go to market folks, I think that people are so willing to share what's working and what's not in these different communities.
And I love that these AI communities have. Sprouted and it's like everybody, it's new to everybody. And so everybody wants to learn from one another in a way that wasn't really the case. Coming up as a marketer. It was really hard sometimes to find, insider baseball kind of knowledge. And I feel like the floodgates have really opened with that.
And that is, I think, one of my favorite things about AI and how things have changed.
Ken Roden: The communities have been really powerful. I think that's been one of the most exciting parts.
Erin Mills: So tell me what was maybe the hardest lesson you had to learn with AI this year?
Ken Roden: The hardest lesson learned this year was around deploying AI to teams. Everybody's starting in a different place and moving too fast. can hurt the team and the results you're looking for. So I think learning how to properly pace a rollout was [00:30:00] my biggest learning for the year. What about you?
Erin Mills: I think that's spot on. assuming that people were further along than they were, and not understanding the starting point. Thinking everybody is talking about AI like we are all the time. And that people are a little bit further along on their AI journey or understood concepts that might've, been just really fresh to them.
coming back to the importance of change management, I would say, 90% of the time when we first started ai, we were talking about What can we do? And 10% maybe on the people.
I think that narrative needs to shift to 80% focus on the people and 20% on the execution.
If you had to rebuild your entire go-to-market org, what would you do first?
Ken Roden: I'd get the team together first and we would vibe code A GTM org. That's how we would learn how we're going to use AI at the company. it would be an offsite workshop somewhere really cool I don't know, like Aspen or somewhere by beach. And we would just spend [00:31:00] a lot of time together working and figuring out, hey, this is our North Star.
What are we going to accomplish and how are we going to use AI to do it? Maybe a little altruistic, maybe a little too kumbaya, but that's what I would do. I wanted to ask you something. given everything you've done with ai, what was your biggest personal unlock this year
Erin Mills: Ooh, that's a tough one because there have been so many. Both work related, but also just even personally, one that I'll share that's just a personal one and I talked about it earlier in the season, is the types of things you can do for other people is just really incredible. So one example I gave was creating, this personalized book for my niece and she has now the whole series and she loves it
It's a great way to impart, the idea of being able to spend time with her family. 'cause we live far away. I think the other thing, is, my mother-in-law who is in her eighties, is using ChatGPT every single day.
I think for her it's been really great. It's like, how do I fix [00:32:00] this thing? how do I get to the answer faster without having to sift through a million different things?
But what about you?
Ken Roden: I think the biggest personal unlock I had using AI this year was around self-regulation. With ai, you can do everything, and what I realized was. That can burn you out. focusing on what's most important for me, both personally and professionally, and how am I gonna use AI to do that, but I actually don't need to be in every channel.
I think that's something that the more people use ai, they're gonna have to come to terms with, is if they keep using AI all the time, they can actually burn out from it. So that's my thing for the year.
Erin Mills: I love it. I'm gonna totally take your usual segment and do a lightning round with you. Are you ready?
Ken Roden: Yes,
Erin Mills: what is the most over-hyped AI buzzword of this year?
Ken Roden: A IEO
Erin Mills: Okay. And what's mistake that we still see [00:33:00] everywhere?
Ken Roden: Rolling out ai, not rolling out Upskilling.
Erin Mills: what is the best use of AI in your own go-to-market motion?
Ken Roden: Digital twin or content creation workflow.
Erin Mills: what are you experimenting with in the beginning of the year and that we'll be talking about when we pick up season three in March.
Ken Roden: Human agentic workflows, like using the sandwich model with stopgaps, for human verifying.
Erin Mills: Ooh, I love that.
Ken Roden: Okay. Erin, are you ready for your go?
Erin Mills: I am ready. It's like the hot sea is burning. I'm ready.
Ken Roden: What is the most overhyped AI buzzword of 2025?
Erin Mills: I don't know if it's overhyped, but one that I use constantly is vibe coding. That would be like a regular part of my vernacular.
Ken Roden: What is the most underrated tool or workflow right now?
Erin Mills: Underrated. I really think I know. I think [00:34:00] it's N eight N I'm gonna keep going back to it. You knew I was gonna go for it. I just think there's so many capabilities and being able to go to GitHub and pull down a, JSON file and have it build the agents for you is pretty rad.
Ken Roden: What's one GTM mistake? We still see everywhere.
Erin Mills: I think I'm gonna do the same it's a little bit the adoption, the curve, and spending not enough time on the people, more time on the tools.
Ken Roden: What's the best use of AI in A GTM motion?
Erin Mills: I think creating continuity between marketing and sales, you're all singing from the same playbook and being able to do one-to-one at scale.
Ken Roden: What are you experimenting with AI in Q1 of 2026.
Erin Mills: I'm going swarm crazy. I'm trying to figure out how to make that feedback loop more meaningful with my agents and get them better and better. I do think there's an opportunity for more. [00:35:00] Types of interactions. we use 11 labs for a lot of our voice stuff. I think there's more in video to be done.
I think there's more with voice that can be done. I'm still not bought into the SDRs live calling. That being said, I think that for onboarding, for interviews, I listened to recently Planet Money's. Segment on AI recruiting and fascinating. I will link it in the show notes.
But it was saying that folks that chose to interact with the ai, recruiter were, more likely to stick around get the job and be better employees. So they had three groups. One that was assigned ai, for a recruiter, one that had a live person, and then the third group got to choose.
Something like 78% of the folks chose the ai and those people did do better. it helped to eliminate bias, which is interesting because a lot of times we hear, AI is super biased, for women, being interviewed, they wanted the AI agent because they felt it would remove that bias.
I just [00:36:00] found that to be very interesting. I do think there's more capabilities out there with, coming in to different modalities of using ai.
Ken Roden: If you could DM every go-to-market professional something, what would you DM them?
Erin Mills: If I had to DM every go to market professional, I think it's get your hands dirty. there's a tendency, especially as you get more senior in an organization, to focus on the strategy and certainly the people. I think there, because this is new to everybody.
There is this real need for you to understand what your team is going through, both the upside of, being able to move faster, but also like we were talking about some of the failures and pitfalls, that is probably what I would DM people because if people haven't started now, oh, let's face it like blockbuster, all these other, like the brick and mortars, that's the same thing. it would be a combination of get your hands dirty and gotten in there yet, giddy up.
Ken Roden: Giddy up. Erin, thank you for such a great season.
Erin Mills: Thank you. What a fun lineup we had, and thanks to our [00:37:00] guests, we had amazing guests and a much longer season. really appreciate everybody who came on the show this year.
Ken Roden: Yeah, and we will be back for season three and we wanna make sure that we're listening to what you all want. So please DM us, find us on LinkedIn, hit us up in any way, smoke signal, text message, whatever works for you. let us know what you wanna see next season, 'cause we're gonna be putting it together over the next couple months.
Erin Mills: Yeah, and a big thank you to our listeners. I think that is one of the things that helps us to really keep this podcast going. aside from it just being a personal passion project for Ken and I, and also the opportunity for me to get to spend more time with Ken, which is one of my favorite things.
the opportunity to democratize AI for everybody and be part of that larger community and mission has been one of the greatest things. So thank you to all the listeners.
Until next time.
Ken Roden: Let's keep crafting the future of GTM together.
Erin Mills: Bye-bye.
[00:38:00]
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Ken Roden: [00:00:00] Hey crafters. Just a reminder, this podcast is for informational entertainment
purposes only
and should not be considered
advice.
Erin Mills: The views and opinions expressed our own and do not represent those of any company or business we currently work with are associated with, or have worked with in the past. for tuning in to the FutureCraft podcast. Let's get it started.
uh, uh, uh, um, uh,
Ken Roden: hey there. Welcome to The Future Craft Go To Market podcast, where we're exploring how AI is changing all things go to market from awareness to loyalty. I'm Ken Rodin, one of your guides on this exciting journey.
Erin Mills: And I am Erin Mills, your co-host, and together we're here to unpack the future of AI and go to market. We'll share some best practices, how tos, and talk to industry pioneers who are behaving the way in AI and go to market. So Ken, normally I ask you what cool new thing you're doing with ai, but [00:01:00] we're at the last episode of the season, so maybe we could talk a little bit about, what we did this season.
Ken Roden: I love it. Let's dive in.
Erin Mills: what surprised you the most about how things have changed between January and now?
Ken Roden: Okay, so real talk. I was really surprised when the season started. Some of the first guests we had, Jonathan and Liza said. We're not that far along and we thought we would be further along in this journey. But now that we're several months in, I think there's been a lot of news about how AI pilots aren't working, and there's been a lot of discussion about where AI's role and investment should be.
For companies, we're actually getting more clarity on what works around adoption as well as seeing things beyond just using AI to help you write an email. It's actually being used in sales and marketing in go to market to drive. Meaningful results around efficiency and productivity. [00:02:00] So we started out slow, but we got a lot better towards the end of the season.
What's your point of view?
Erin Mills: Yeah, I would agree. I think there were a lot of organizations that tried to do pilots that just didn't go anywhere. A lot of pilot purgatory, and I think that teams got frustrated with that. And so we saw that being a prominent theme that we heard a lot about. And the other wild thing is the accordion of tools. It felt like last year there was explosion of tools and then vibe coding became a thing, so people were creating even more and more tools available.
And then it's sort came back to reality, and now it feels like it's picking up again. I think that's been really interesting too, in the sense of there were a lot of organizations that were tool heavy adopters as opposed to focusing on the problems. I think that has really shifted.
Ken Roden: It's funny you say that because one of the things that I'm finding in my research is that companies who focus on the adoption aspect versus the tools aspect are seeing more success in these [00:03:00] pilots. it speaks to what you just mentioned Tools go in and out of fad, but teaching people the fundamentals around how to use AI and how it can help their job is what's gonna drive real change.
Erin Mills: Yeah. The other thing I think that's been really interesting and a shift from last season to this season, I'm curious to get your perspective on this, is it really is, less about, putting something into AI and just getting an output and AI being much more your teammate Liza is a big proponent of this and has been for a while, but are you seeing that in the folks you're talking to?
Ken Roden: Yeah, actually what I've seen is exactly that. It's using AI as a partner, so this sandwich model that we talked about earlier
Erin Mills: Love the sandwich model.
Ken Roden: a good sandwich, a club sandwich, if you wanna get specific, because humans are the bread. AI is the meat, your lettuce, tomato. And so humans start the work.
AI goes and does some tasks, comes back to the human to verify, and then the next steps follow that pattern. And so what's really been [00:04:00] powerful is people trying to see AI more as that partner, more as an assistant. My favorite one right now is an intern with a PhD who doesn't have any business experience, is the best name for AI right now. That's what I'm definitely seeing and it's been really exciting to see people, when they have that perspective, really dive into using it like an intern, which makes them feel more confident. Okay, here's one. I wanna dive into something that I want to call.
They called it. And it's where we have guests who made predictions about what was gonna happen. I want your take on if they called it right. the one that I'm really interested in is from Rachel Tru Air from simPRO. She said, AI SDRs are a win for a company. What's your hot take?
Erin Mills: Yeah, I gotta agree. I think she's onto something. My hot take is we're also experimenting now largely because of that conversation with Rachel that was at the time, not being done [00:05:00] effectively at a lot of organizations. I think we're still trying to figure it out Is it just emails? At what point is the AI more the initiator of conversation then at what point do you have the BDR and human in the loop? I think she's right. a lot of organizations are not there yet, and I think there's still work to be done,
I have one for you, which has been topic of many conversations of ours. We had Chase Hannigan on the show and he was talking about the no code agentic systems and N eight N and how that's the way of the future. What's your hot take?
Ken Roden: Okay, my hot take is Chase. Is brilliant and knows his stuff and I've seen him build incredible things, but I'm gonna call it that Chase is ahead of the curve on this one, on AI agents being usable by most people. it really comes down to something Sheena Miles said a few weeks ago that most teams are in this activate not accelerate, that people might be able to get some of the concepts around how [00:06:00] to build using N eight N, but it's too complicated and intimidating for a lot of people unless they're technical. What I think we're gonna see though, is N eight N in particular is gonna get a lot easier to use. Friendly user interfaces similar to what Relay has, that you can actually use agents to build the agents, and I think you're gonna see it explode. So I'm gonna say Chase wasn't wrong, he was just ahead of the curve.
Erin Mills: I like it. I would tend to agree, except I do love n8n and I think, there are tools out there that go to market teams are more successfully adopting relevance. We've talked about a lot on the show as well as Lindy, there's the crawl, walk, run, and I feel like those relevance and the Lindy's are in the walking and folks that are more in the N eight N are in the running phase.
Agree.
I got another one for you, which I really am interested in your take, especially as you've been doing all this research, and talking to different CEOs, Liza Adams said EQ is the edge. What do you think about that?
Ken Roden: I [00:07:00] am gonna say that it is the edge now we have hit the Edge, Seems to be coming up more and more, but in a different way than I was expecting. Liza said, you're going to need EQ more than ever because technology is gonna be so prevalent in our work that we're going to have to work more as humans.
Totally makes sense. what's been really interesting, talking to CEOs as well as talking to operators, think CMOs or go to market leaders. We're training their employees on ai. They're having to be way more human and way more thoughtful and aware about teaching people new skills because teaching people how to use AI is like teaching somebody how to do algebra.
Like it is foreign at the beginning, and you've gotta ease them into it. And so seen people lean into this eq, as a. Skill and demand. And actually, if you look at, job descriptions now for senior leaders in a lot of go-to-market [00:08:00] roles, they're looking for more soft skills at the top of the job descriptions than before.
It's starting to populate more. So we are in the new world, being human matters.
Erin Mills: it does matter and I think as a professional or a leader, a differentiated candidate because at the end of the day, we're going to have a lot more technical skills, and those are not necessarily the true foundation, but curious to get your take.
I think the EQ is incredibly important as a skill. I think the other one is, curiosity and understanding what. The problem is, or our favorite, Cheryl, quote, which is skate to where the puck is going. yes, she did get it from Gretzky, but I'm gonna give it to Cheryl as well.
I was gonna say the curiosity and understanding context, is equally as important as EQ is what I was gonna get.
Ken Roden: Yes. Completely agree with you and Cheryl. Curiosity is something that's going to take leaders as well [00:09:00] as all levels of employees into this next era of work. What about you? What's your take on this?
Erin Mills: I think that it's such a critical skill because ultimately we're all learning. something new, and if you don't have that curiosity or being able to identify the problems, squint into the future from our Grant Gregorian episode, last season, I think it's gonna be really hard for folks.
And so you gotta be a little bit more proactive on your own development and learning. And that comes with curiosity. Now I wanna switch gears a little bit with you. What was one AI thing that just did not land this year or broke?
Ken Roden: What was, a really good one. I'm gonna say what happened at the beginning of the year, all the AI vendor tools were just ridiculous. Everybody put AI on every single feature and product they had. And I think what happened to me is [00:10:00] what happened to a lot of people. They tried them and none of them worked.
I think what you're seeing now is. Real use cases having to be proven by these vendors. it's a really interesting time for vendors who have to show their stuff, buyers are getting way more sophisticated. So I'm gonna say the AI spray and prey market message is a fail for the year. What about you?
Erin Mills: I have a pretty controversial one. I don't know if you're gonna love this one. I know there are folks that will disagree with me. I feel like the custom GPT overload. Is something that is happening to a lot of organizations and I don't think it's good. It's having too many slack messages.
I think it's really hard to keep things updated. I think there are so many better ways of bringing in agents now let's say you use relevance, use a workforce and have all of those agents serving something that's, a little bit more, robust. I heard a stat the other [00:11:00] day, a company we both know has 600 custom GPTs and they're not a huge organization.
So how do you manage all those? How do you keep them up to date? Further, is that really the most efficient way to do business? Because I'm finding that since January things have moved in a much more streamlined way. It's not even a workflow from starting here, ending there.
It's this much more circular piece where we're learning and then applying that getting better and better. And I just think the custom GPT, I gotta say. it's great if that's what people have right now. It's like anywhere you're starting is great, but is it the best case long term?
Ken Roden: I agree with you. I find custom GPT super interesting because as an individual employee, if you have your arsenal of gpt you can get a lot done.
But to your point, when you're thinking about scaling. How many is too many and how many are actually that valuable? When you say 600, even if you told me 50 for, [00:12:00] marketing function or sales function, that's too many like it, those aren't team tools. Those might be individual tools, but that's not scalable.
And to your point, keeping them up to date, but also what value are you actually getting from them? one of the things I'm hearing, a lot of leaders their budgets right now are being asked by their CFOs is. How much business impact are we seeing from all of these AI tools?
Because implementing ChatGPT for your whole company is not cheap.
Erin Mills: Not cheap indeed.
Ken Roden: if your employees are just AIing all day, that's not really helpful. I'm gonna take Your call and agree with you, but here's a question around that. with all of this AI stuff happening, it is really scary for people to dive in because it seems risky.
one of the things that Rebecca, Shaddix said was define acceptable mistakes. what do you think some good guidelines or recommendations are to help companies think about what an acceptable mistake is to get them [00:13:00] comfortable with doing this type of stuff?
Erin Mills: I think it comes back to a lot of what we've been talking about with some of these guests where it solved the problems that you have. Look at some of the boring problems. Don't go for the sexiest thing. I think there's a tendency for us to get stars in our eyes when it comes to talking about ai, and it's like we're gonna automate the whole go to market process
It just doesn't work. When people think about acceptable mistakes, make the pilots about real problems that you have, and then also define, what are we expecting from this outcome? Also when do we call it a failure. sometimes like a stock,
or you get emotionally invested and just keep holding onto it. Sometimes you have to cut bait.
Ken Roden: Yeah. I wanna go into workflows because you brought up N eight N, and there's a lot of 'em out there. But what do you think shifted the game from workflows and agents?
Erin Mills: I think it's the accessibility and companies like Relevance and Lindy and others, where you don't have to be a technical person, who can implement these things and also make it. [00:14:00] understood across an organization. I think one of the things that I learned from Chase and n8n was really what is the foundation of an agent?
I think at the beginning of the year, all of us were scratching our heads of what is like a true agent do, and why do I need it, versus just creating a Zapier or other type of workflow. it really came together for me when I learned it's pretty simple.
It's like you've got your instructions for your agent, you've got tools, you've got a memory, and then you've got the brain, the LLM, and once you get your hands around that, and then the tools can also be other agents, it really helps to connect the dots because you can create a really powerful workforce or a system that helps you automate a lot more than you would've been able to, and certainly helps to define what the. Processes that you want, or in this case, workflow itself? What do you think?
Ken Roden: I think you said at the beginning of this season, that it's not really about the tool, it's how it fits into your system. to [00:15:00] me that shifted the game. It's talking about employees who were a year ago. Building workflows for them. But now companies and teams are building agents that make sense for the output they're looking for.
I agree it's the accessibility, but it's also the thoughtfulness of the orchestration. Think about this as a process and the output you're looking for verse, Hey, I'm just gonna use AI for AI's sake.
Erin Mills: Any other bus that you've seen this year?
Ken Roden: I'll just pour one out for anyone who rolled out a GPT or a LLM to their company and just had really bad usage because 95% of them apparently failed. it's been a hard year to say, Hey, you're rolling out ai. so I think that's one of the things you're gonna see next year a lot more companies being.
Way more thoughtful about if they haven't rolled out ai, how they're gonna do it, or if they have what their rollback looks like and what [00:16:00] they're reentry in. AI's not going anywhere. If it was this bubble would've bursted already. It's not. It's becoming part of our work. We just have to figure out how to land it with people.
Erin Mills: I was reading a stat the other day around 93% of people are saying now that they use AI at work, whether or not their organization has approved it.
Ken Roden: Wow. you and I called it really early on, digital twins are the hero of 2026. I will back this up by a research study that said that when done right, they can be up to 90% accurate.
Erin Mills: Wow.
Ken Roden: I'm like. That's a darn good digital twin. we use them.
I have people raving about their digital twins. It is probably my favorite low entry, easy use case for ai. Everybody should get a digital twin or a digital buyers group. Digital buyers group is amazing.
Erin Mills: Yes, totally agree on the digital buyers group. I think that could be the [00:17:00] winner for 20 24, 25. I do not think digital twin is gonna be the winner next year. I think we're going to do more agent swarms and workforces, and it's gonna be much more about what can the agents learn along.
What they're building and then apply that and continuously improve on their own. digital twins are great for people who have them I love that 90% stat, but I think it's gonna be swarms.
Ken Roden: Okay, I'll wait to be proven wrong, but I'm curious
Erin Mills: We can't always agree, Ken.
Ken Roden: Exactly what about, business impact, how are you hearing others talk about how. TGTM teams are best showing impact to prove continued use or increased budget for next year.
Erin Mills: It depends on the function, but if you think about go to market as a whole, one of the things is really the speed to market. if you think about, you have a product marketing [00:18:00] background where it would've taken months sometimes to get really robust tier one launches put together. And it could be really frustrating, like last minute changes from engineering or product.
And that really ends up pushing out your go live date. I think with ai. The speed to market has, improved exponentially, especially when you have, really good setups, good prompts, good agents, it makes that process so much more seamless. What do you think?
Ken Roden: Yeah, I would agree with you. I think that the two things that I've seen work are measuring a big goal. That you have and saying, Hey, we are trying to decrease the time to market by 10%, of an overall initiative. the other two things I've seen work really well are, having people look at their calendar individually and how they're spending their time.
Erin Mills: Yeah.
Ken Roden: And having teams actually look at how their time. Is invested and where they could potentially use [00:19:00] AI to drive an increase. And having them measure it, and it's been really powerful. The light bulb opens up for them. And if they do it as a team, then they're all bought in.
So then they can together build workflows and processes. So it's a little bit of, leading the group together.
Erin Mills: I think I'll have to revisit that with my team.
Ken Roden: It's really fun. Most people get really into it. There's been some research that is saying people are tired of hearing about wins only and they want to know about the failures. I have seen that come up with. AI training specifically where people will do, the best failure award.
they'll share the. Biggest flop that they had. And people will try to one up each other it's about taking pride in what's not working so that you know it doesn't work. And you can try other things I found it a fun way to build camaraderie and also not take this stuff so seriously.
Erin Mills: [00:20:00] One more thing to bring up is really the analytics. And insights themselves. in the past there's two pieces that I think have been really hard for folks.
One is if you're not an analytics, aficionado, it can be really hard to get your insights without leveraging a data scientist or somebody else on the team who has that expertise. AI has really unlocked that for a lot of folks, and think about Salesforce reporting in the past and you had to build, 10 different reports to get.
A couple of different insights, whether it's, win rates for a particular industry or velocity it was really hard to get that all in one place and without having to do several iterations of something. You don't have that barrier, which is really incredible.
So you think about time saved and business impact. If I can get smarter about what I'm doing understand what's working and what's not, and where to make more investments, and I don't have to spend, weeks or months to figure that out, that's pretty powerful.
Ken Roden: Yeah. Oh, hey. I actually caught up with a, executive circle here in Boston a few [00:21:00] weeks ago, and they had a question that I meant to ask you. I know that you're in quite a few communities for leaders. How are leaders using AI in ways that employees might not be? And the reason why this came up was, I talked to specific executive and they said, I love how my employees are using ai, but I'm not building go to market plans or campaigns or content, but could I use AI in a meaningful way?
And I was like, let me get back to you 'cause I've gotta talk to Erin Mills.
Erin Mills: Yeah, I think the spectrum is pretty wide on that. you have the folks that are just dipping their toes in and starting to use Chachi PT for the first time, or building their first digital twin, and maybe the first digital twin is not that great. And then you have folks that are building their own, agent tech workforces
I think it really depends on how comfortable you are with diving in. For me personally, I love getting my hands into the AI tools and understanding really what are the mechanics of making them work. and I think it really depends on the community too. For example, Chris Penn's analytics community, [00:22:00] they are talking about things that are much more advanced than you might see in, other communities that are a little bit more generically focused
marketing as a whole. it depends on how comfortable somebody is in working with the tools. you can make it as big or as small as you want. to the leaders you're talking about what are the problems that you're trying to solve for?
And if you're looking for, Hey, I need to understand whether this strategy is viable or not, you certainly can leverage AI to help and do a lot of deep research, which really came on this year in a big way,
Ken Roden: Deep research.
Erin Mills: Tell me, what have you used deep research for that you've been most excited about?
Ken Roden: the thing that I have found deep research to be the absolute best for is understanding yourself because deep research is able to take a look at your brand persona but also able to look at. Whatever you feed into it, it can analyze and benchmark you. I've used it to help define brand voices for [00:23:00] individuals, for founders in their go to market as well as companies.
So assess my brand positioning. help me understand how it fits into the market and where there's white space deep research is really good at telling you the holes you can't see. I'm amazed by how accurate and Believable. It is. one of the obstacles when doing things like deep research, which is a little bit like a black box, is executives believe it because it is sourced, but the way that it's presented is logical.
It's not hallucinating. It's spending the time to really think about it. that's been the biggest one I've seen. How about you?
Erin Mills: Yeah, I think that's a really spot on example. Chris Penn, came on and did a great example. Getting competitive analysis insights in a way that's so much faster and so much more in depth than before, I think is super powerful. Aside from just deep research in general, goes to trust.
And what's really interesting is our [00:24:00] conversion rates on. Prospects coming from LLMs is so much higher. They spend 600% more time on our site than if they came from a more traditional, direct or paid search. I find that interesting because it's where we feel that the AI is delivering a more accurate response than if we just did a single search alone or deep research taking that into making buying decisions. might be the key takeaway of the year.
Ken Roden: I wanna talk about next year, if we're looking at 2026, what's coming that GTM leaders need to think about now?
Erin Mills: So I'm gonna go back to the preview I gave a little bit earlier. The agent swarm workforce, whatever the term is going to be, it's creating agents who are really good at something very specific, being able to leverage them for multiple things so that you have this motion that all works together.
if you think about the example that Chase Hannigan gave us with the assistant. Agent that he built [00:25:00] you start with the top level agent who is the project manager and decision maker, then you have an agent that does email and calendaring and then you have, all these expert agents.
It's like that, really smart college graduate that comes to you. if you give them a giant project to do, they're gonna fail. But if you give it something very narrow and they're smart and they are equipped with the right tools, probably gonna have a much better result. It's similar to what we learned last year in terms of prompting and making sure you know how to prompt.
I feel like we've gone so much better than just learning how to prompt it's a piece of the sandwich. It might be the lettuce, but the other pieces to the sandwich and all the other accoutrements are the tools and the brain and all the things that go along with it.
Along with giving very clear. Instructions on what the outcome is that you're trying to get to. And coming back to the whole agent side of it is what the agent learning and iterating on to get better and better? And that is, I think, where we're going. But what do you think?
Ken Roden: [00:26:00] So I've got two, I think we're going to see the emergence of closed. LLMs specific to companies. I think companies are going to want their own closed environments and, anthropic and Claw are going to start selling them way more, actively because there's just so much out there and employees are using it so much more.
We're going to see these closed instances, which is then going to allow companies to think about knowledge management in a way they haven't Before Claude came out with skills this past year. It's been really incredible to think about even writing a job description.
Erin Mills: Oh yeah.
Ken Roden: people, write job descriptions, that's one of the biggest pains a manager deals with.
It's now simplified with this one skill. The other thing is related to what you talked about. I think we're going to see a shift in how organizations and teams are structured. I think we're gonna see a lot more employees or contractors, fractional talent show [00:27:00] up with their own team of agents and maybe one or two other employees, and they're gonna come work on a project Specify everything to your team, and then when it's done, they're out of there. And that, I think is actually where we're gonna see new roles emerge of these like fractional ai. Go to market experts in different areas. And so it's really gonna take into what you said as well as the people aspect. I just think there are, there's a growing community of AI enthusiasts who have learned how to fine tune their trade around, go to market, and they're gonna be so valuable that they're gonna be plugging in and working with companies, and maybe they'll sell their agents as well, but we're looking at a, I think a new industry and ecosystem.
Erin Mills: It reminds me of something that Coach said during our interview with him where he was talking about coming in and being Iron Man and plugging in the Iron Man suit. I think that's what's gonna happen. the SaaS industry as a whole is ready for a shakeup functions within go to market are as well
Coming to the [00:28:00] end of our recap episode. Wanted to get your take on a few different things. Is that all right?
Ken Roden: Yeah,
Erin Mills: Okay. What was one thing that you changed your mind about this year?
Ken Roden: AI and SDRs, I would totally bet wrong on that. I thought it was completely over promised and committed, but, since Rachel came and actually shared some results, I've done my own research and it's very true and it's again, complimenting the SDR role.
I totally got that one wrong. What's one thing you changed your mind about this year?
Erin Mills: I think I'm gonna go back to the GPT thing where, it was such a huge thing last year and for me it's just. It's the what's the next thing? And the next thing is more on the agentic side. I think the other thing, that I really actually love, and it's not necessarily a changed my mind from an AI perspective, but I think just as a industry as a whole and marketers [00:29:00] or go to market folks, I think that people are so willing to share what's working and what's not in these different communities.
And I love that these AI communities have. Sprouted and it's like everybody, it's new to everybody. And so everybody wants to learn from one another in a way that wasn't really the case. Coming up as a marketer. It was really hard sometimes to find, insider baseball kind of knowledge. And I feel like the floodgates have really opened with that.
And that is, I think, one of my favorite things about AI and how things have changed.
Ken Roden: The communities have been really powerful. I think that's been one of the most exciting parts.
Erin Mills: So tell me what was maybe the hardest lesson you had to learn with AI this year?
Ken Roden: The hardest lesson learned this year was around deploying AI to teams. Everybody's starting in a different place and moving too fast. can hurt the team and the results you're looking for. So I think learning how to properly pace a rollout was [00:30:00] my biggest learning for the year. What about you?
Erin Mills: I think that's spot on. assuming that people were further along than they were, and not understanding the starting point. Thinking everybody is talking about AI like we are all the time. And that people are a little bit further along on their AI journey or understood concepts that might've, been just really fresh to them.
coming back to the importance of change management, I would say, 90% of the time when we first started ai, we were talking about What can we do? And 10% maybe on the people.
I think that narrative needs to shift to 80% focus on the people and 20% on the execution.
If you had to rebuild your entire go-to-market org, what would you do first?
Ken Roden: I'd get the team together first and we would vibe code A GTM org. That's how we would learn how we're going to use AI at the company. it would be an offsite workshop somewhere really cool I don't know, like Aspen or somewhere by beach. And we would just spend [00:31:00] a lot of time together working and figuring out, hey, this is our North Star.
What are we going to accomplish and how are we going to use AI to do it? Maybe a little altruistic, maybe a little too kumbaya, but that's what I would do. I wanted to ask you something. given everything you've done with ai, what was your biggest personal unlock this year
Erin Mills: Ooh, that's a tough one because there have been so many. Both work related, but also just even personally, one that I'll share that's just a personal one and I talked about it earlier in the season, is the types of things you can do for other people is just really incredible. So one example I gave was creating, this personalized book for my niece and she has now the whole series and she loves it
It's a great way to impart, the idea of being able to spend time with her family. 'cause we live far away. I think the other thing, is, my mother-in-law who is in her eighties, is using ChatGPT every single day.
I think for her it's been really great. It's like, how do I fix [00:32:00] this thing? how do I get to the answer faster without having to sift through a million different things?
But what about you?
Ken Roden: I think the biggest personal unlock I had using AI this year was around self-regulation. With ai, you can do everything, and what I realized was. That can burn you out. focusing on what's most important for me, both personally and professionally, and how am I gonna use AI to do that, but I actually don't need to be in every channel.
I think that's something that the more people use ai, they're gonna have to come to terms with, is if they keep using AI all the time, they can actually burn out from it. So that's my thing for the year.
Erin Mills: I love it. I'm gonna totally take your usual segment and do a lightning round with you. Are you ready?
Ken Roden: Yes,
Erin Mills: what is the most over-hyped AI buzzword of this year?
Ken Roden: A IEO
Erin Mills: Okay. And what's mistake that we still see [00:33:00] everywhere?
Ken Roden: Rolling out ai, not rolling out Upskilling.
Erin Mills: what is the best use of AI in your own go-to-market motion?
Ken Roden: Digital twin or content creation workflow.
Erin Mills: what are you experimenting with in the beginning of the year and that we'll be talking about when we pick up season three in March.
Ken Roden: Human agentic workflows, like using the sandwich model with stopgaps, for human verifying.
Erin Mills: Ooh, I love that.
Ken Roden: Okay. Erin, are you ready for your go?
Erin Mills: I am ready. It's like the hot sea is burning. I'm ready.
Ken Roden: What is the most overhyped AI buzzword of 2025?
Erin Mills: I don't know if it's overhyped, but one that I use constantly is vibe coding. That would be like a regular part of my vernacular.
Ken Roden: What is the most underrated tool or workflow right now?
Erin Mills: Underrated. I really think I know. I think [00:34:00] it's N eight N I'm gonna keep going back to it. You knew I was gonna go for it. I just think there's so many capabilities and being able to go to GitHub and pull down a, JSON file and have it build the agents for you is pretty rad.
Ken Roden: What's one GTM mistake? We still see everywhere.
Erin Mills: I think I'm gonna do the same it's a little bit the adoption, the curve, and spending not enough time on the people, more time on the tools.
Ken Roden: What's the best use of AI in A GTM motion?
Erin Mills: I think creating continuity between marketing and sales, you're all singing from the same playbook and being able to do one-to-one at scale.
Ken Roden: What are you experimenting with AI in Q1 of 2026.
Erin Mills: I'm going swarm crazy. I'm trying to figure out how to make that feedback loop more meaningful with my agents and get them better and better. I do think there's an opportunity for more. [00:35:00] Types of interactions. we use 11 labs for a lot of our voice stuff. I think there's more in video to be done.
I think there's more with voice that can be done. I'm still not bought into the SDRs live calling. That being said, I think that for onboarding, for interviews, I listened to recently Planet Money's. Segment on AI recruiting and fascinating. I will link it in the show notes.
But it was saying that folks that chose to interact with the ai, recruiter were, more likely to stick around get the job and be better employees. So they had three groups. One that was assigned ai, for a recruiter, one that had a live person, and then the third group got to choose.
Something like 78% of the folks chose the ai and those people did do better. it helped to eliminate bias, which is interesting because a lot of times we hear, AI is super biased, for women, being interviewed, they wanted the AI agent because they felt it would remove that bias.
I just [00:36:00] found that to be very interesting. I do think there's more capabilities out there with, coming in to different modalities of using ai.
Ken Roden: If you could DM every go-to-market professional something, what would you DM them?
Erin Mills: If I had to DM every go to market professional, I think it's get your hands dirty. there's a tendency, especially as you get more senior in an organization, to focus on the strategy and certainly the people. I think there, because this is new to everybody.
There is this real need for you to understand what your team is going through, both the upside of, being able to move faster, but also like we were talking about some of the failures and pitfalls, that is probably what I would DM people because if people haven't started now, oh, let's face it like blockbuster, all these other, like the brick and mortars, that's the same thing. it would be a combination of get your hands dirty and gotten in there yet, giddy up.
Ken Roden: Giddy up. Erin, thank you for such a great season.
Erin Mills: Thank you. What a fun lineup we had, and thanks to our [00:37:00] guests, we had amazing guests and a much longer season. really appreciate everybody who came on the show this year.
Ken Roden: Yeah, and we will be back for season three and we wanna make sure that we're listening to what you all want. So please DM us, find us on LinkedIn, hit us up in any way, smoke signal, text message, whatever works for you. let us know what you wanna see next season, 'cause we're gonna be putting it together over the next couple months.
Erin Mills: Yeah, and a big thank you to our listeners. I think that is one of the things that helps us to really keep this podcast going. aside from it just being a personal passion project for Ken and I, and also the opportunity for me to get to spend more time with Ken, which is one of my favorite things.
the opportunity to democratize AI for everybody and be part of that larger community and mission has been one of the greatest things. So thank you to all the listeners.
Until next time.
Ken Roden: Let's keep crafting the future of GTM together.
Erin Mills: Bye-bye.
[00:38:00]
