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Welcome to "Future Proofed," the podcast for forward-thinking professionals eager to keep their career and company at the cutting edge.
Traditional go-to-market (GTM) strategies have become clunky, inefficient, and bloated. This show explores the intersection of AI and GTM strategies to ensure you cut the GTM Bloat and build a future-ready approach.
Each episode of "Future Proofed" dives deep into how AI redefines what it means to craft effective go-to-market strategies. From actionable insights on integrating AI into your sales, marketing, and product strategies, to expert interviews that shine a light on the new best practices changing industries, this podcast is an essential resource for anyone looking to upgrade their GTM playbook.
Our host, Kyle Coleman, is a seasoned expert in GTM and AI innovation. He breaks down complex concepts into practical, actionable advice. With "Future Proofed," you'll learn how to:
- Leverage AI and machine learning to supercharge your GTM strategies.
- Navigate the challenges and opportunities presented by new technology trends.
- Adapt and thrive in the fast-paced digital economy.
- Foster a culture of innovation and agility within your team or organization.
Don't let the wave of the future leave you behind. Tune into "Future Proofed" and stay ahead of the curve as you learn to leverage the power of AI for your GTM strategy.
Ryane Bohm (00:02)
All right, hey everyone, welcome back to Future Proofed. We are flipping the script and I am going to be interviewing our Nathan. I'm Ryan Fohm, co-host of Future Proofed, joined by Nathan Thompson, who you know and love after the past couple of years here. So, Nathan, today we're talking about the crawl, walk and run of using AI at your companies. I would love to start by just...
You've been talking a lot about the evolution of AI in marketing over the past few years. I would love to learn a little bit more from you before we dive in about that maturity curve that you've been talking about and where are most marketing teams at today?
Nathan Thompson (00:43)
Yes, yeah, we have the go-to-market AI maturity model. And in layman's terms, it really goes from like no AI to everything's AI-ish. But level two, have people that are starting to mostly chat tools. So people like with chat GPT subscriptions, they are not really taking the time to learn how to prompt. They haven't loaded a bunch of context into it yet, but they are getting through things marginally faster. You have ⁓ stage three, which is more people are getting through.
processes less than tasks ⁓ and they are starting to cross a line. So you start to see like marketing and sales are working toward common goals. You have stage four where you see more alignment and more focus on processes rather than tasks. But again also an evolution with teams coming together. So it's not like sales is doing their thing marketing and then customer success. Everything from that itself. And then stage five where you have just everything's kind of in line. We don't see a lot of stage five still yet. It's coming together though. ⁓
Ryane Bohm (01:38)
Yeah.
Nathan Thompson (01:41)
I think we're still seeing people in stage two. I thought it would be a little bit further along by now. I'm going to be totally honest, but I think we're still seeing people in figuring out how to do things with tools like chat, I think.
Ryane Bohm (01:51)
Why
do you think they're stuck in that phase?
Nathan Thompson (01:54)
I think there's two reasons and I'm scared to be honest about one of them. Okay, all right. I think the first reason is it's just easier. It's just so easy to use. You pop in and no one has to tell you what to do. You can just kind of feel, I'm going to type this and get an answer back. And then it's kind of fun. It's like, okay, I can make this work. I think the second reason is whenever we have cross coordination or cross alignment, either between departments or between people.
Ryane Bohm (01:57)
you have to be honest at this point.
Yeah.
Nathan Thompson (02:25)
I think people's processes were a lot less clear than they had hoped or thought. And now that we are trying to codify processes, they're realizing I need a more firm process in place before I start sharing this with other people on the team. And so you have this weird like, I think people have been doing their jobs a lot more intuitively than they've understood or admitted, and now they have to put all that on paper.
Ryane Bohm (02:31)
Yes.
I mean, when I came here, that became very glaringly obvious to me as I started codifying my own workflows of like, but it's here. It's not on paper, but I know exactly what I have to do. And so actually turning that into a process that is used by other people, I thought I was much more documented than I was.
Nathan Thompson (03:13)
Yes, and I think everybody does. And I don't know if this happened to you, so I'll throw myself under the bus and I don't want to lead you to an answer or anything, but what happened to me is a lot of times if a workflow isn't giving me the quality, by nature I just grew up with religious guilt. So I always assume things are my fault. And so when I look at a workflow and the output's not there, I think what did I not tell it? Nine times out of 10 it is because I had some knowledge up here that I didn't share with it in the workflow.
Ryane Bohm (03:15)
Yeah.
Nathan Thompson (03:40)
Nine times out of ten, it is my fault. ⁓
Ryane Bohm (03:43)
Your
polite Canadian is showing again. ⁓
Nathan Thompson (03:47)
But it is true and it's, gosh, it's almost an advantage. Any other system like that type of self-deprecation, I totally get it. It does hold you back in the career. All that stuff, that imposter syndrome. With AI specifically, defaulting to this is probably my fault is actually kind of a good call on this stuff.
Ryane Bohm (03:49)
it is.
I mean, at this point too with it, it's kind of crap in, crap out. Like if you're not in the chat, in the crawl phase at least, if you're not prompting it and feeding it with everything that you need, it will hallucinate. It's not gonna give you the context you need. There's a lot that's needed there.
Nathan Thompson (04:21)
And then if you start to chain that output, if you take that chat and then you talk about building a workflow where you have a series of those prompts together, if you have something that's kind of weak upstream and all that, then everything downstream is going to be worse off. And so it's really important on like, we've got to get this process done. How do we make a blog post? ⁓ Lisa Cole on 2X talks about this. She said every CMO should totally understand the process and handoffs
Ryane Bohm (04:44)
Okay.
Nathan Thompson (04:51)
for how everything gets made. So when we make a blog post, where does it start, who does it go to, how does it end? She said a lot of CMOS don't actually know the process for how these things are getting created, and so there's a ton of inefficiencies getting lost in the cracks.
Ryane Bohm (05:03)
I'm honestly not surprised to hear that.
Nathan Thompson (05:06)
Yeah, what are your reactions? You come from some bigger companies as well, so you've probably seen this firsthand even pre-AI, not to throw anyone under the bus.
Ryane Bohm (05:16)
I mean, yeah, but the bigger companies very much have the textbook, how do you do a product launch? What does a sales playbook look like? And those are very well documented when you're at the big companies. And that's where you learn how to do formal by the books, X, Y, and Z, product launches, blog posts, whatever it may be. But then as I came with that playbook to smaller companies throughout my career, progressively getting smaller as I'm here with Copy AI, Series A.
as the founding PMM, it looks so different. take flavors of it and it's the essence of what worked there, but you can't translate a company with 70,000 employees down to a company with 40. It's very, very different. You know, that essence is always going to be there, but you know, learning how to adapt that and build new processes and feed new prompts is huge.
Nathan Thompson (06:09)
It is huge and it's also, I feel like there's an advantage and a disadvantage to being small. Because if you're smaller, don't, I think, I feel like even smaller companies, have so much more freedom in designing the pipes. There's just less good tape.
Ryane Bohm (06:20)
Yeah. yeah.
There, a lot of times there's no red tape, which is great because, hey, run fast. We trust you to do this thing. What works? If it doesn't work, do it different next time. Kind of love it though.
Nathan Thompson (06:34)
Yes. Yeah, well, I telling my brother, he has
a coffee shop in Sacramento, and I was like, dude, do you know how much time it's gonna take Starbucks to implement this because they are so big? Like, it's almost their disadvantage because they have the red tape, they have the legal, they have to get a process that works for the whole company, every franchise, sorry, everything. He could just go with it. Yeah, yes, Tandem Coffee in Sacramento, Tandem Coffee in Sacramento, yeah. Yeah, he's our sponsor today.
Ryane Bohm (06:50)
Right. Shameless plug for the coffee shop because I am pro coffee shops.
Love it
Nathan Thompson (07:03)
No, but there's such an advantage. On the other hand, the larger companies have an advantage where they have money and documentation on how to scale all of this with data to back it up that they're making the right calls. I think the only thing right now, the only wrong thing to do is nothing, like no movement, and that's what's weird to see.
Ryane Bohm (07:24)
Yeah, the no movement is like it's ship up or ship out. Like everyone's doing it. Yeah.
Nathan Thompson (07:28)
Exactly.
Yes. Yeah. yeah, sorry, I'll shut up there. My my pedestal, I'll get off of it.
Ryane Bohm (07:36)
And no, that's what we're here for.
Nathan Thompson (07:38)
Yeah, I know. just get frustrated. I've said this before, but like, I know in 2024 there was even at the crawl phase of like, should we use AI or shouldn't we? There was like a lot of AI can't do this, AI can't do this part of my job, AI can't do this. Now those same people are making posts on, let me teach you which LLM to use for this task that last year I told you do. I'm just getting really frustrated by that. I'm not going to lie. Today it's particularly on my mind and I'm getting mad at like,
Ryane Bohm (08:00)
Oh my gosh,
Nathan Thompson (08:08)
people listening to that crawl walk run narrative from people who were telling people to not even join the race last year. It's very frustrating.
Ryane Bohm (08:18)
I feel like now we're in ⁓ that part of the hype cycle where it's becoming operationalized. Like, yeah, maybe it was a little hypey last year, but now it works. Now it works. Yeah.
Nathan Thompson (08:30)
Now it works, and now it's- and which we're bringing to life with PartyBot, which you absolutely
crushed on that PartyBot has proven.
Ryane Bohm (08:37)
Shameless plug for PartyBot, the other sponsor of this podcast today.
Nathan Thompson (08:40)
Yeah, I love it. Love it. ⁓
Ryane Bohm (08:43)
Okay, so back to the crawl walk run idea. So
when you see a team ready to move beyond crawl, get a little bit more advanced than chat, what's changing? Like, is this introducing probably the agent functionality? What are you seeing as the next step?
Nathan Thompson (08:59)
I love our content agent studio for the walk phase, especially because now we can attach, they're called pre-processing workflows, but really it's just a workflow that gets you a detailed campaign brief for whatever you want to make. The reason this is really cool is workflows, they're just super intimidating if you're new. It's a different way of doing work, Like you just, especially if you're not technical, if you've never really opened the Zapier dashboard and seen like the, okay, this step leads to this step, which leads to this step.
Ryane Bohm (09:18)
Yeah.
Nathan Thompson (09:29)
It can be intimidating. With Content Agent Studio, you just need three examples and a clear idea of what you're trying to make. then if you build that agent, you really only need one person who's kind of technical to build the pre-processing workflows. And then the rest of your team just needs these agents that they can build by themselves, run by themselves, but it's still got that unified messaging because it's connected to the processing workflow, if that makes sense.
Ryane Bohm (09:56)
I mean, as the product marketer, that unified messaging is really, I mean, I care about a lot of things, but that is what I care about the most of anything.
Nathan Thompson (10:07)
And I want to pick your brain here, not to steal the interview receipt back from you, but as we move from crawl to walk to run, like as the speeding ramps up, I do think that that's where messaging tends to get disjointed because people start doing things on their own. From a product marketing standpoint, what do you see the dangers of those silos between marketing sales, customers for all that stuff?
Ryane Bohm (10:32)
Well, then you're scaling either misinformation or incorrect positioning 10 times faster. If you are living in a silo, your core messaging or what is true to your products that you're talking about could be misinterpreted. like I said, you scale the wrong message 10x faster and it could be very damaging. It could be amazing if you have it right. It could also be very damaging to your brand.
Nathan Thompson (10:58)
Yes.
It's a big if. Someone was talking to me about AI's ability to scale indiscriminately, almost sociopathically. It's not taking into consideration if it should or shouldn't. It's not making those types of decisions. It just does. It just does. And so if you say, go write me 10,000 blog posts, if they're not really written in the right way or by the same tone or with the same guidelines, they're going to come out a bunch of different ways and to your point with different... That would be fun to read, right?
Ryane Bohm (11:27)
Honestly, that could be fun to read.
Nathan Thompson (11:31)
Different value propositions, different audiences being targeted, different benefits are...
Ryane Bohm (11:34)
Yeah. Yeah.
Yeah. Okay. Let's think about run. So we've gone through chat, through content agent studio, or just agents in general. So when teams are actually able to run, say we adopted everything, we're ready to completely overhaul our business, operationalize everything. Is it just automation or is this something bigger?
Nathan Thompson (11:59)
I think it's something bigger, but that's just me. Look, I think to me, run is full automation for almost everything traditional. Full automation for your, full automa, excuse me, no, that's not fair. Nearly full automation, I think as humans, always in the loop. And so I always said whatever you're creating something, anything at all. It's like you have the strategy, the first draft, the editing, and the publishing.
Ryane Bohm (12:07)
Mm-hmm.
Nathan Thompson (12:28)
I think full automation on that first draft is important, but I don't think there should ever be full automation on strategy. I don't think there should ever be full automation on publishing. I think there should be mostly automation on first draft. I think there should be a layer of AI work on the editing. But I do think that humans are needed in steps one, three, and four. I know this is sounding more like tin foil Hattie as I keep talking like, but.
Ryane Bohm (12:52)
No, you
said it before and it really landed with me of AI is not the one pushing publish. Like the poor content problem is a human problem. It's not an AI problem. They are not publishing it, you are.
Nathan Thompson (13:00)
Exactly it.
Yes. And I don't think that should change no matter how good this gets. It's very important ⁓ that there is this strategy on the front end and then the polish on the back end. And so I think people have the wrong idea of run. I think they're hoping that all four of these get done. ⁓ If that is the case, then all of us are out of a job. that's everyone is out of a job if it's doing all four of those by itself. And it's not even so much that I don't think it, I don't think it can.
Ryane Bohm (13:10)
I agree.
Nathan Thompson (13:35)
Because I don't think it, like I said, it's kind of sociopathic in how it's treating your customers. It doesn't value the same thing. It doesn't value anything. It values what you tell it to, if that makes sense. And so I think the strategy will always be very huge.
Ryane Bohm (13:45)
Yeah.
We're gonna revisit this episode in five years from now, see what it looks like actually in practice.
Nathan Thompson (13:56)
That's a great call, yes, we will see what happens. I am curious to see. If I had to guess, I would be willing to bet that there will be a bunch of products coming out that do full automation and they're gonna be super popular for three to six months and then they're just not gonna do what they, it's kinda like we saw with those auto email senders and they were really good for the first couple months, but then you hit your entire total addressable market. it's, ⁓ one of our competitors has option to in spam the tam.
Ryane Bohm (14:23)
And then what, yeah.
Nathan Thompson (14:26)
and it's gross. Yeah.
Ryane Bohm (14:28)
Yeah,
I've seen that at a couple places actually. That's not unique.
Nathan Thompson (14:32)
And I think that's
why full automation won't work. It's just gross, right? ⁓ But I think that's why full automation won't win. I don't think it'll work.
Ryane Bohm (14:38)
Yeah, yeah, yeah.
don't think it would work and I don't think it should work until we can actually give AI emotions and feelings and you know, that ability to like read a customer. It's not gonna work.
Nathan Thompson (14:55)
Yeah. OK, so I want to know, though, from a... Sorry.
Ryane Bohm (14:57)
Okay, so do you think that... ⁓
Go for it, all you.
Nathan Thompson (15:04)
I want to know from your perspective what run like from an ideal product marketing manager. What does run look like? Like you're looking across the team. You're looking at sales, you're at like marketing, from your standpoint, what does run look like?
Ryane Bohm (15:19)
Okay, so I have this dream of like my product marketing dashboard when I wake up in the morning and I see that AI has synthesized everything that the competition is doing, has suggested next best content for the field. So, hey, we're going to update the core positioning to include this differentiated edge that you didn't know you needed, but we saw in the change log from X company that they released this.
And here's how you respond. I am seeing it like automatically doing this research for me, understanding what the competition is doing and suggesting changes that I probably wouldn't have even noticed. And it's stuff that I can prompt AI to do. I could build a workload, do that now. But I want that full experience of it knows before I even know to ask it to.
Nathan Thompson (16:14)
I love that. I want to go build it right now. That's really great. And you really could.
Ryane Bohm (16:18)
The best
part about that is like, I think you probably could build this right now. So maybe I'm actually just creating my copy AI workflows that I would like you to build for me. ⁓
Nathan Thompson (16:22)
You totally could, you just-
No, no, that's
brilliant because you could take the RSS feed to a changelog. Anytime there's an update to that changelog, it triggers the workflow to look for whatever change was made and then pings you in Slack to say, hey, know, ex-competitor just added this to their changelog. This is how it fits into your roadmap. Maybe you need to reprioritize. That is awesome. I never even thought of that.
Ryane Bohm (16:49)
I've been dreaming this up for a while now of like how do I equip our teams with the best because it's such a it's a hugely saturated market right now so I'm trying to figure out how to sell or to help our team sell.
Nathan Thompson (17:03)
Oh, we can totally build it. We're doing it!
Ryane Bohm (17:03)
Okay, so this isn't a dream anymore. Apparently you
could do this with a product and I accidentally just pitched it. Awesome.
Nathan Thompson (17:09)
That is
super cool. Yeah, we're doing that. Okay, sorry. That's all I'm going to think about for the next few minutes. That's great.
Ryane Bohm (17:14)
I'm excited, cool. So, you my answer is completely, it doesn't make sense anywhere because it is reality. It is real. I would love to do that. But to your point, it's not fully automating everything, but it is getting to the point where I no longer have to ask it a question. It's proactively giving you suggestions on next things to do and how to do them, where all I have to do is, yeah, great idea, go.
Nathan Thompson (17:22)
It is reality. We're gonna hit running. That is super cool. That's awesome.
Ryane Bohm (17:45)
Let me edit this. Let me tweak it for my voice. It's connected to my messaging, my positioning.
Nathan Thompson (17:53)
That's exactly what I want and I'm starting to think, again, throw myself under the bus. I really am just looking for an invisible assistant with a photographic memory that makes me look awesome. And I feel like we have that. Kind of cool. Like we do, yeah, you can totally that.
Ryane Bohm (18:07)
Yeah, we do. It's the cheat code
again. I'm going to keep saying that, but it really is.
Nathan Thompson (18:13)
But it's not cheating if you're telling it to do the right things and that's what's so great. Okay. All right. Sorry. This conversation opened up so many other conversations that we'll have to revisit in future episodes because it really got my wheels turning on some of this stuff.
Ryane Bohm (18:15)
I know.
I know.
And apparently
in a potential like pitch deck because I am, I am live building product right now. Yeah. Yeah.
Nathan Thompson (18:29)
and a potential, yeah, because that is so cool.
That is really cool. Okay, I'm gonna think about that.
Ryane Bohm (18:38)
All right, cool, well tune in next week to see how we bring this to life in a workflow.
Nathan Thompson (18:44)
Yes. Yeah. Maybe in the show notes, you'll have a workflow that you go use to anybody listening. That's cool. Check the show notes and see if we pulled it off. That's cool.
Ryane Bohm (18:52)
I love it. Okay, well with that, let's wrap this one up. Any final words, Nathan, that you want to share about Crawl Rock Run and how to get our listeners started?
Nathan Thompson (19:04)
just to revisit the idea that as you're speeding up, speed with AI is somewhat equivalent to scale. so just make sure you don't have too many weak links in the chain upstream, because it will just everything downstream. It will be worse for it.
Ryane Bohm (19:15)
Yeah.
Yeah, yeah. All right. All right. Until next week. All right. Thanks, Nathan. Talk to you soon.
Nathan Thompson (19:23)
Thank you so much.