S2E2: "Context Is the Moat" | Zach Vidibor

We did something different this time around with Zach, and we were going to do like a little bit of a livestream and mixing up our podcast format with, again, like our webinar series. But yeah, like if you listen to our first season of the GTM Engineer podcast, you know that it was about evangelism and making like what actually was GTM engineering. But in this season, we're trying to shift from hype to operating system. This is just to say that we all know that GTM is here to stay. And so we're done with evangelism. And we're now here for some practical sensemaking. And I think there is no better person to kick this off with today than today's guest. Because if you spent any time in GTM engineering over the past weeks or months, depending at which speed you go, you probably heard the term of context engineering thrown around. And I believe it's becoming one of the main keywords in 2026. But while most people are still figuring out what it actually means. You know, our guest has been actually building the infra for it. And that's why I'm super hyped to introduce Zach Didibor, the co-founder and CEO of Octive, the first context engine that is specifically built for GTM teams and use cases, which again, you know, it's a headline that super excites me as a PMM and content practitioner, but it might even terrify some more old school folks or just confuse them depending on which side of the GTM you sit. But that's what we wanted Zach on the show, you know, Octave acts as the messaging brain behind every GTM team. And it's actually like putting this context into action. Think of it like a GitHub repo for your ICP, your value props, your your competitors, and all structured as context that powers your actual agentic workflows and personalization. So today we'll be covering a lot of ground. We'll dig into how GTM engineering has actually changed over the last year, and we'll be adding also context engineering and going through some real practical use cases. So Zach, amped to have you on the show.

Thanks for having me, guys. Super exciting. So grateful we've been able to partner and hopefully help people, you know, go on this journey. And I, I love what you're saying there of like, let, let's make this the year of like actually, actually getting rubber on the road versus just imagining what's possible. And, and I, I think, and it's what we see. I think people have, there's been a lot of tinkering and experimentation, and that's of course gonna continue to be important as Things move so fast, but I think there is starting to be some real, like, systemic, like, fundamentals, I guess, is maybe, maybe what's starting to emerge where people are gaining more confidence of, okay, here, here we're beginning to, to pull out of that fog of like, what are the systems of the future? What are they going to look like? And obviously we feel, and I think the, the, the market feels like your first-party context, like how you understand the world, how you interpret it. You know, like one way we think about it is like, you know, your context is kind of the lens you put between your company and how you view the markets you operate in. I think people really understand how foundational that is. So we're excited to be a part of this community, hopefully support people and teams as they go on this journey. But yeah, thankful to be here with you guys.

Awesome.

Zach, so you've been on the front You have a front row seat here and so much has changed in the last year. So much has changed in the last 3 months. From your perspective, like what are some of the biggest deltas between go-to-market engineering a year ago versus go-to-market engineering today?

I would say, and I, I don't mean this to be an answer to just like feed into the, the topic of context engineering, but like I, I do think that is a big difference. I think kind of wave 1 of go-to-market engineering was a lot about, we, we have all these pieces of data that we'd like that, like, kind of in the, the world of the past, or like, they, they were like the variables you would love to insert into messages or insert into records in CRM. And I think a lot of the first wave was about like, oh, like, what if we had these like magical workflows that could go get all those fields that we were never able to fill in with information. So I think like that was what we saw a lot of. And I think the, the craft there and the tooling has excelled in ways where people are like, okay, we can do that. What's next? And I do think now, like where things are evolving is the LLMs have improved so much. Everybody, they are ubiquitous. Everyone is using them, you know, like using AI, that's not a differentiator, right? Like you have to put alpha on top. And I think that's now what we're starting to see is like you using Claude, using GPT, using whatever your favorite model workflow coding assistant tool is. Everybody has that, right? So your moat needs to be on top of that. And I think people are recognizing, oh, our moat comes from really deeply understanding our market, how we want to splice it up, how we talk to different customers in really specific ways, how we can serve them in really specific ways. What, what are the customers we don't serve? You know, like, like one of the problems with LLMs is they are very optimistic and they will, they will be sycophants in a certain, they will, they will convince you there are opportunities in markets that you know don't exist. So like, that's where I think the, we're starting to see the real precision come to these workflows people are building where they recognize, ooh, if, if we can bake in our opinions more, these, this, this is how we get to the next level.

So, so you can kind of, you can find anybody, you can research anything, right? And you could do this at scale, but the bottleneck then becomes, do you understand your business really well? Your customers really well? The value proposition for each segment. Each of the personas such that you can use all those tools and really get a good response.

Exactly. You know, I think maybe the, like, me not just like rambling on and on, it was like, you know, a year ago it was like, oh, wouldn't it be great if like we could write an email that referenced, we know you have 30 DevOps engineers. That'd be really cool. Like, okay, awesome. Done. Problem solved. Now it's like, What does that actually mean? Like, why is that interesting to us as a business if you have 30 DevOps engineers versus 50 or 100? Like, how, how are we gonna approach you differently, speak to you differently, manage that opportunity or engagement differently? Like, that's where I think people are going now.

If you have a really strong differentiator and you really understand the mindset of your buyer, you can, you can do great things. But without that, you're just sending messages, right?

Right, right. And if you hope the LLMs are gonna think like you do, I would say that that is hopeful.

And you know, they'll fill stuff in, but it may just be fluff, right?

Right. And you know, like, don't get me wrong, they're amazing. They're probably right 80% of the time, but that, that 20% is where all, all the magic and difference is made.

And just to flip it, if go-to-market engineering sort of disappeared tomorrow, all the tools suddenly stopped working, it was a Chinese hack to take down the economy, what would you miss the most? Or what would we go back to? What would change?

Oh man, it's hard to even contemplate. Scary world. We hope that doesn't happen. I mean, What would change? I mean, it'd be back to basics. I guess people would be on the phone a lot more. You know, I don't know. You know, it would be back to hand-to-hand combat, showing up at the office with a box of donuts. I don't even know.

All right, could be good. Could be good.

All right, let's separate a bit more like hype from reality. So like, given again, like where you stand at Octave, you know, you now have like a 15-people team, you're at the cutting edge again of personalization and outbound, how does GTM engineering feel like a step change and where is it actually being oversold?

Where is it being oversold?

Hmm.

Oh, you're saying versus like where I gotcha. I would say, I mean, where it is 100% real is the ability to fuse the strategy with the execution is now like possible in a way that was just not feasible before. You know, there, there was so much, you know, in the, the going back, you know, many more years, like to my past, you know, working at sales teams at, you know, companies I would call excellent at go-to-market, you know, LinkedIn, DocuSign, Dropbox. There was so much that had to be diffused through people, you know, like literally have to get in a room, explain the strategy, workshop it, reinforce it in your weekly team. And there was so much lossiness and delay and inefficiency in like rolling that out, getting feedback from the market, understanding where to iterate. And like, that is where go-to-market engineering is real, is you can really start to have like true coordination between like, what's our hypotheses? Like, what do we want to test? And like, how can we deploy that in market through our team, get signal very quickly and build this dream flywheel of every go-to-market org of highly responsive to your market, your customers, your prospects, and always refining, right? Like go-to-market is never this equation you can just balance once, you know, you're, you're, you're always tinkering with it. So I, I, I think like we're so excited about that because the potential of go-to-market engineering is this kind of, this handshake between the strategy and execution and systems that just couldn't even dream of it years ago. Where maybe oversold is, I think there is sometimes a, I, I would say sometimes you hear in conversations, I would, I would say an over-indexing on like what, what the tech can do without people, you know, like this, the, the best go-to-market engineering teams, they are all hyper aware of like these things all need human in the loop. They all need to be, guided, crafted, you know, like you've heard other people say in, in, in other contexts of like, you need to treat your AI just like an employee. You need to train it, manage it, encourage it, let it know where it's wrong, give it feedback. And like, it, it's, you know, it's like one of these truisms, but I think it's really true. And, you know, the best teams we see and have the, the, you know, good fortune to work with, none of them want a black box. Like they know it doesn't work. They need their hands in there. They're trying to look for ways of like, How do we get our fingerprints more on this machine? Obviously do it in a very efficient way and like find out more and more things that can be automated. But I would say that's sometimes where you hear in the conversation a bit of the panacea being sold that we're, you know, we're not there yet, but like, that's okay. Like, like what's happening now is freaking incredible. Like this is, this is progress, you know?

Bring it on. Yeah. And if I have to play back at you, you know, like where it's real in one word is efficiency. And progress, right? You know, like, or removal of waste, right? You know, like, uh, no more waste, no more delays, uh, tighter, you know, more efficient and effective systems, right? But then, uh, you know, like, and I'm totally with you about the, you know, we can call, call them out AI SDRs, uh, or, you know, like these, uh, you know, PM, uh, porn workflows that we all see on LinkedIn that, uh, you know, like, uh, they do everything on their own, which we all know they don't. But no, so is like, help us understand or help us, our listeners understand that is really GTM engineering then, or like a GTM engineer, one person that can do the work of 10, or is that just a work framing, a wrong framing?

I would, I'd probably go with the latter in like, I think probably the wrong frame. I think in a simplistic sense, if you were, if you were to like You know, a lot of people, they like starting with the like outbound use case because it's high leverage. If you do it well, very high ROI. And so like, yeah, there, there is this easy, like old world, new world, like, oh my God, we used to have all these SDRs and like, if they were the best in the world, they could get out 15 really high quality emails and LinkedIn messages a day. And now look at this. We can do 150. There we go. Like 10, the work of 10, you know? So like, I feel like that's the easy way of like framing it. I think the latter is like, well, what's possible when we have 8? Like, why are we even thinking in terms of how many humans this replaces? Like, let's dream up like what our ideal go-to-market motion is with all of these new capabilities and tools and like, it's just, it is, I think truly like we're moving into a new world where it's like, if we're, if we're just trying to replicate all the workflows of predictable, predictable revenue era with AI tools, we're, we're going to miss out on like what's possible. You know, I think the, again, the best teams are just like clean slate. Like let's revisit, let's not try and like automate and like plug into all these like long dusty old workflows of like, ooh, what, what are the little steps we can optimize? Like, Okay, great. You'll, you'll, you'll eke out efficiency in this assembly line, but it's like, well, what about instead of an assembly line, we 3D print this thing? You know, like I think that's the, that's the future. And it just looks the, the apples to apples comparison won't be there, but that's fine because it's going to be the world we all want to live in.

So yeah, it's less about replacing people into and converging them into one, but it's more about, uh, redefining what's the ceiling, right, of the use cases, of the capabilities that we can enable, which I think is like a much more, you know, yeah, like a positive sum, you know, way of going about it.

And much, much crisper way of saying that.

And I mean, I really wanted to hear your thoughts on this one as well, because we're clearly in the last two weeks, in cloud code hype peak phase, right? You know, like I've been personally on it for the last 2 weeks, changed my life, you know, as an operator, as a consultant. And I just want to hear your thoughts on it broadly. What do you think about it and how is it impacting you and how do you see it, you know, impacting the industry at large? And especially in the context of, you know, GTM engineering or vibe coding.

Yeah, I think it's awesome. First of all, like, you know, we are as the Octave team internally, like we need to be, but like we are excited to be like using all these things ourselves and trying to, you know, dream big and see what is possible. We have some cool use cases already of, you know, slight tease here, but we'll have some cool like Octave plus Clog code tools coming soon. Like we're very excited about it. I guess to more like directly answer your question, I mean, what we're seeing is it's another step function change in like allowing people to very quickly, like what we were talking about a second ago, like uncover the new earth of like what's possible. Like it is clearly a different experience than having nodes and workflow tools with LLM prompt steps, you know, there is something magical and different about working in Claude code. Now, I think where things are like yet to shake out is like, it's very easy if you're a solo operator, a smaller startup. As you start to move into a larger like enterprise context, I don't think we know what that world looks like yet. You know, if we have lots of people in Quad Code all trying to dream up workflows and different ways of like interacting with our, like, there's going to be a lot of collision there in terms of data and processes. And so like, that's what like we're trying to think through a lot is like, okay, what does this look like in a scaled up world where there are like gravitational forces that need to be thought about of like, okay, we have We have 500 sales reps. We have defined territories that are really complex and we have like multiple product lines and we have inbound SDRs and outbound SDRs that have all these like relationships of how they support AEs. And like, that's something that's like really hard. Like it's hard for orgs to understand. Like they have rules of engagement that are 50-page documents of all these things. And like, those are things that like, It will be interesting to see like how the like Claude code, we can build anything, any workflow potentially merges with some of the like on the ground reality of sales teams and like when you need levels of, you, you need real scaffolding in place. And I think it, it, it can be dangerous for a sales team of like jerking the wheel back and forth every day of like, oh my God, this is po— hey, I built this thing last night. Like, go try this. Like, We're going to need to find an equilibrium where it's like, okay, how do we, how do we have teams that are just like dreaming up what's possible? We can vibe code it overnight and actually then deploy that into a, you know, scaled up team. Like that will be, I think that will be probably the, the story of this year is like, what, what are the new frameworks and abstractions and tools that like start to emerge and processes that like, okay, we can take this insane potential and like get it to work really well and not, not cause too much chaos. Some chaos is probably good. Like change will be good. Entropy is good, but you can't have too much.

Yeah, I love it. And again, like with, with so much layers and complexity and, you know, like, uh, obviously the market going at breakneck speed, right? Like, uh, What do you actually optimize for? You know, like, is it like, again, flexibility? Is it speed in and on itself as a muscle? Defensibility, I think, is a huge topic now. Or again, costs and efficiency. What do you have to say about that?

I mean, it's a good point because I think that is, that's probably where teams get stuck is they go, we want to do AI. And to your point a second, what do you want? Are you trying to eke out costs? Are you trying to deliver more speed? Are you trying to deliver more agility, more precision? You know, like these are, they're kind of like esoteric concepts at that level, but they're like really important to like get the org aligned around, you know, like there are things that are potentially more expensive, but the yield is going to be crazy, you know, and really having the, the team aligned around like, what's our goal here? You know, is it, and I, I don't honestly see many companies doing this, but it's like, all right, is, is the goal to eliminate human-staffed sales roles on the revenue team? Like there are, there are companies that do it. I'd say we, I don't see that that much. I think it's, if anything, it's just like, how do we keep the team we've got and make them 10 times more productive versus cut, but like, You need to be very clear with yourself upfront of like, you know, what is the goal? Like if the goal is cut, that looks a lot more different than like, hey, we want to drive more growth potential through going extremely deep on every account. And hey, we're going to reimagine our go-to-market. It's no longer SMB, mid-market, and enterprise, how we slice up the world. We're going to slice it into 50 sub-verticals that we're able to go incredibly deep on and under, like, that's just a completely different set of tools and architectures and processes you'd build versus you go, hey, like we think we can get away with 10 SDRs instead of 30, you know, or whatever. Love it.

So clarity, if I have to sum it up.

Yeah. Yeah, for sure.

Yeah, the problems at large enterprises that you're describing, uh, so much different than startups using you know, trying to apply the same toolset.

Right.

Let's switch focus now a little bit from sort of AI and go-to-market engineering in general and down to talk about context engineering. And, you know, we kind of touched on this earlier, but 2026 might be the year of context engineering. And I bet that for some of the listeners, they've only heard it once or twice and they're a little fuzzy on what that means. So what is it? Why should you care? And then in the org, maybe big and small, who owns this?

Hmm. Who owns it question is TBD. That is a complex one, I think, yet to be determined. It could be go-to-market engineering. I think there's a strong case to be made. This is the evolution of PMM and like the product marketing org. I think it's going to be, it is going to be foundational. I think who owns it in this like sea of like everything moving and changing so fast and cloud code, it's probably not the first thing you need to do is like nail down who owns it in terms of org structure. You just need to have somebody that is like, your mandate is you're the one thinking about this and like building a plan.

All right, well, let's first even just define real clearly why anybody should even care about who owns it.

Yeah, I, I think simply put, like, context to us at least is like, it— this is where you need to go from all of the rows and columns of data that exist in your, you know, structured databases, right? So your, your CRMs, your data warehouses, you know, there you, you have lots of context that exists in structured ways. You have a lot of context that exists in unstructured formats, you know, call recordings and you have contracts and you have Slack messages and you have emails, right? And like the list goes on forever. So context engineering to us is like, all right, we all as humans and as the org and the company, like we've developed ways of like interpreting all these things we do into how we act and operate. And there's a lot of like unwritten assumptions in many go-to-market teams. Like for example, yes, exactly. It is, it is locked up here. So you might have an org that, for example, we know historically, like we don't sell to higher education. They're a bad customer for blah, blah, blah, blah reasons. And that's just like institutional knowledge, but it's like, that's not written down anywhere for like an AI to really like interpret in a way that like, oh, it, it, no, there's kind of like this. This, this commandment in the org. So like, that, that's like one granular example, but like context engineering is like, okay, how do you start codifying into these systems the way your team thinks about problems? Hey, how do we think about when we go after a digital native fintech business that is issuing credit cards to consumers in Latin America? Versus we go after Square, you know, could, could almost be considered a, I wouldn't consider them legacy, but very mature fintech, right? And like your org is going to have a detailed point of view if you're selling into these markets, like how do we think about them differently? And like that stuff needs to start getting codified and like that's the job of context engineering is like, how do we actually like codify that stuff, create systems and tooling to like curate and manage that understanding over time. So then we can feed it not just to AI workflows and agents, but also people, you know, like people are involved in all these process processes too. And like everyone needs to be, excuse me, you know, singing from the same sheet of music.

And then, so how do you think about, how do you break down a project that, that has context engineering at the, at the center of it? What are the phases of, of such a project?

I guess there, there are some like fundamental, like early steps of just like, what do we have? Like, you know, taking catalog of like, what are all the assets? What are the information? What's good? What's bad? You know, I'd say a lot of people have discovered over the last year like, oh, it's, it's really easy to hook up your entire Google Drive to any of these systems, like, is that what you want to do? Like, I can tell you the answer, like, no, you know, but like, those are the, like, some of the, like, tactical steps, like, you need to, there's a lot of existing stuff you need to prepare. And then just like the conversation we were talking about before, like, breaking it down into projects that are realizable, that have real goals, like, okay, what, What is our goal? The goal could be we have a large existing customer base. You know, a lot of our revenue is through an expansion motion versus net new coming in the door. Like project one might be about how do we go deeper with all our customers? How do we turn the QBR session that all our CSMs schedule from this like perfunctory, we're gonna present usage and how many seats are active on your account. And, but like, how do we turn that into like a true value-add experience that like are excited to come to and they're gonna learn and like, we want to prepare them with points of view on the market and where they can go and where they can take our technology and like, all right, there's gonna be a boatload of context engineering in there of like, how do we execute on that? Like, what do we wanna share with them? What is our point of view? And so like, I think it comes down to like establishing like, what are some of these work streams of like, what is it? Is it outbound? Is it inbound? Is it lead qualification? Is it building? AI chatbots that are able to have really deep conversations and not just push people to a demo, you know, a scheduling link, you know, I don't, there, there's like, the challenge here is like you can do a million different things, but pick a few, understand what you have, be very aware of, you know, I think the, the number one we think, we think, we, we, we tell our customers to think all the time is don't, don't just expect the models to know what you know. You know, like you really need to like catalog all of those assumptions. Like that's, that's the hard part of the work. And like right now that is like, you know, guess what humans are really good at is, you know, like understanding those like multivariate problems and like cataloging that and then defining that in systems, whether that be tools like Octave or something you build or, elsewhere.

So it's, uh, figuring out which needle you, you want to move and then honing in on the, the data that you need to ingest around that. Maybe it exists already. Maybe there's a new process of creating that data if it's, if it's oriented a different way. And then you got to put it somewhere. Um, and everybody's got to know. Uh, and obviously Octave is, is, is, is one of those places where where we could store this and it could be the brain. Yeah.

Right. The, yeah, I mean the, you know, like Matteo said earlier, yeah, like one of the ways we like frame our dream is like we want to be the GitHub for your go-to-market context. You know, like there's a reason teams don't build their own GitHub, you know, like it's a core piece of infrastructure. It has all these primitives and APIs and ways to integrate with it so we can, it can have a shared repository, right? That everybody's working from and like, we think these agents and workflows, that there's gonna be a, a similar pattern in these things that are developing. And we know we have agents too, but we're very clear-eyed of like, we're not gonna build and sell you every agent a mature company has, right? They're gonna have thousands. But like, what is at the foundation of a lot of this, there is shared context that needs to be consistent around all these tools. You don't want to keep rebuilding it every time. Oh, for the, the CSM bot, it has its own repo. For the outbound bot, it has its own. For the web chat, for the, for the, you know, like you don't want to keep repeating that, that same problem instead of work and having that, that shared repo is like, yeah, what we think is really important. 'Cause then you can iterate in one place and everything has that new context immediately.

Can, can you walk through one company who's done this really well, uh, who, who's really fed it everything it needs to know to, to move a certain needle and then hooked up their other systems agents and, and how long did that take and what, you know, were there any particular obstacles that they faced that you think other people would face in getting that done?

There's a few companies, um, I might not be able to share names specifically, but let's say a large infrastructure monitoring company. We are working with their growth team. They've done a really excellent job in that their growth team has— they sell to developers. They've, they've done a lot of work to like really understand like what are the different developer personas. You know, like what, what does a software engineer at Ford Motor Company, what do they think about? What do they care about versus a software engineer at Stripe? Right? Like that, that, those are very different individuals. So this company, they're a large scaled up business, hundreds of million in ARR. They have a lot of signups coming through the door, right? So they have a lot of developers signing up. Obviously then they're trying to go higher in the org. What the growth team is, is trying to do is have really thoughtful engagement with all of these different developer personas that sign up. In combination with that, they know they're in a very competitive market with a lot of other tools. And so they, they know a, like when they were setting up this project, key dimension for them was being very thoughtful about like, if we think this is a developer who signed up from a brownfield account, an account where a competitor might be present as well. We want to deliver a very different version of our message, right? And so like, just giving you some of like the color here of like, okay, these are like, they have really, the, the people have really like thought through the problems, thought through the personas, like what do we want to achieve? Is it, is it a meeting? Are we just trying to build goodwill and high quality impressions, right? They've really thought through all of that. And then that did take some time to then codify into Octave. And like, there's no, You know, there's no defined finish line. Like it's always being optimized, like all these things are. But I'd say, you know, we're talking about, this was a month, 6 weeks to like get something initial live and like really systematize all this logic of like, hey, is it greenfield? Is it brownfield? What persona? What do we want to happen? What version of the story? But now they have something that They have an automated workflow. Like every one of these signups that's coming through is getting scored, qualified, bucketed precisely, sent a different version of their story, logged to CRM, shown to the sales rep on that account. Here's exactly why we reached out. Here's the value prop we used. Here's the rationale why, like develop some very, very thoughtful workflows that are yielding them results, right? And the results being people engage, they're asking questions, they want more documentation. Yes, some of them are like, hey, you know, let me get my boss involved. Like we want to do this. But like, they're, they're looking for all those like ways to just drive high quality interactions with their customer. And like, I think that again, like what we talked about earlier was like, they were really clear on that of like, yes, we want demos and we want pipeline. But like right now what we think is like the most exciting thing is like, can we just have more positive interactions instead of just putting people in drip campaigns that like go nowhere and they send the same thing to everybody?

You haven't used the acronym ABM, but like I hear like account-based context engineering, you know, as the background music here.

Yeah, I think that's a great like framework to think about this with, yeah, principles people understand. Like that's what it is.

I love it. And I mean, if you, yeah, if you've been around for like a few years, you even know that like doing outbound for developers was not a thing, you know? Like no one was able to do, even for 2 developers, because they just don't reply to sales emails. The fact that you can do it and you can generate the, you know, like results and measure, you know, like incrementality and all of this stuff, you know, this is again, like, is a testament, I think, to the unlock that GTM engineering is all like bringing to the table here, right?

Totally. And that's like a good lens there of maybe, you know, like wave 1 of go-to-market engineering was like, oh, okay. Like how it at scale, can I like string together this workflow where you can like de-anonymize like GitHub handles into corporate emails? And then they're just like, all right, throw 'em into some campaign. Like finally we know who they are, like send 'em something. And now we're like, there's a, it's exciting cuz I think there's like a level of like thoughtfulness and what, what can we really do now that that's possible? Great, solved. Like what's next?

And to add my two cents to this, you know, like as myself as a PMM consultant, I get so many clients that they want to skip all these foundational investments into ICPs and personas. They just want the pipeline. You know, everyone wants money. You know, we're all in business here. No, we get it. But if you— there's way to go to market and other ways to go to market. If you skip this foundational exercise of understanding your ICP, your competitive landscape, and using these datasets to then build your own messaging, your own value props, your own brand story, and all the good stuff, you know, like then you're just gonna go with a bunch of AI slop and you're not gonna get your your pipeline. So let's think, let's, let's invest in this content, you know, like not just to plug my consulting services in, but, uh, you know, it is, uh, you know, like again, Zach customers also like, uh, speaks for themselves, right?

It is a foundational step. If you skip, you will regret. Work with Matteo, but, but, but seriously, you know, like the, the problem, if you just Skip straight to, yes, we, we all want pipeline, we all want more deals. Got it. Like that's just inherent in the atmosphere. If you approach these new tools with, without having at least a hypothesis, like the thing with ICP is like, it's never finished, but it's a hypothesis at this point in time. Like what do we believe is true? What do we have the most conviction around? Like, let's go test it. If you don't have that and you start leaning into these tools, like guess what? They do have an opinion, might be right, might be wrong. You'll keep asking them to iterate. GPT, like it'll keep splitting an atom until infinity, right? Like it has no idea when to stop. What's like, you, you need these opinions and structures so you can grade yourself, evaluate progress. Do not skip ICP. Please. Yeah.

And again, like with AI, you know, like again, and GTM engineering, the job market is clearly having a moment. You know, we all, we all got that. Everyone's doing everything. Everyone's expected to do everything. We even talked about it, market moving at breakneck speed. So like, how do you at Octive actually, you know, structured your GTM organization and where does GTME sit within that? You know, like, I think like it's important to give our listeners an example of, uh, you know, what the cutting edge of the early stage is doing at the moment on, uh, in terms of like org design and, uh, talent.

Yeah. Um, happy to share, of course, with the slight asterisk of, you know, we, we have kind of a hybrid go-to-market engineering team that We have our, our own internal efforts for our own growth and pipeline efforts and all that. We also, this same shared team is working with our customers, helping them, you know, the, the forward deployed engineer concept that obviously many AI native companies are going to market with because this stuff is so new for customers. They, they know they, they can't realize some of these possibilities because they just, they don't have the internal skillset. They haven't built these things before. So they need help. So our go-to-market engineering team, how we, they are responsible for pre, you know, pre-sale, like think of solution engineering would be kind of like the way to think of it in the past. They're also supporting customers post-sale as part of a like customer success motion as well, in addition to supporting our own internal efforts. Right now for us, at least in, in this world, like we have it, that team kind of reporting through sales, cuz it, it feels like that's where so much of the activity and learning is happening, right? Is like being embedded with these customers, going deep with them. Like we learn as well, but like, yeah, being at the tip of the spear of like our engagement with customers, trying to figure out like, what are people trying to do? What are, what are all the tools they're trying to integrate with? So we want, we want to push them forward as much as possible. And I think that's, you know, every company sales org is kind of the tip of your spear. So that, that's like functionally like where we have them reporting, but at least in our scenario, there is a, a lot on their plate in terms of pre and post-sale and our own internal efforts too.

Very cool. And like when you hire for new talent, like what's their background and where do you actually, actually what separates, you know, the good from the great in your experience?

I think the, I'll take the second question first. The great comes from having some level of sales and marketing savviness. You know, like you've seen some of these stories before, like you know where the things go off the rails in teams. So you, you have some of those understandings and then obviously the technical proficiency as well. Like when you, when you have both of those things, you have a pretty magical, you know, very valuable person. I don't think you can't learn one or the other, of course, but like, you know, right now if you have the person who's like, hey, I've been a seller, I've been a marketing ops person, I've been a PMM, and I've like just my own curiosity has like driven me into these tools and I've made myself super pro— like if you find one of the, hire them. In terms of like where you're gonna find those people, where we found that people, those people, you know, I think obviously, you know, Clay has been the, you know, like kind of lightning rod that has like catalyzed and really formed this community. So like our go-to-market engineers were, were people we found, you know, in this community doing freelance Clay work themselves, you know, working as, you know, this first incarnation of like the go-to-market engineer at companies internally. And so, you know, we were, we were lucky to find people that way. And I think like that will probably be the like place to find the most like sought after individuals is like the people who are active in the community because stuff is changing so quick. So like if, if you're, if you're looking for somebody that's going to be that true difference maker, like you want somebody that's like exposing themselves to the outside world and all the change and all the tools and everything that's happening. Versus the, and I'm not saying this person isn't great too, but versus the like, all right, I'm just a, I'm a go-to-market engineer at X company. I go, I go hunt them as a, you know, title on LinkedIn. I think you want to go after the people who are really out and active in the community right now.

I love it. And if I have to bring it to sum it up into two main things I picked up, taste. So like the ability to understand, to head, Exposure, you know, like to been there, done that, know the nuances of the space, the persona, the industry, or the ability to discern what's good and not good. And the systems, like that's the second, like system design, system thinking, thinking modules or capabilities and be able to understand how to sequence them up and build them out.

Absolutely. Yeah. Good, good summary.

And what do you think again, like is the one highest leverage skill that, you know, like among all this noise, you know, GTMEs should invest this year?

Well, from where I'm sitting right now, getting Claude Code, get, getting Claude Code if you're not like, as you know, it's, it's the, it's the hype train of the moment, but you know, it's, that's probably a good place to start.

Not, let's not go into Claude, ClaudeBot.

Yeah.

Let's stick with Claude Code for now.

For now. Yeah. Yeah. But yeah, I think people that are also, I'm trying to think of the, like, uh, something more interesting here to say, you know, you, you want people that are trying to think deeply through where do people and humans meet, you know, like, like it's interesting. I think there's like, I think when the First, when, when Gen AI, when ChatGPT hit mainstream, I think the conventional wisdom was like, oh my God, sales is dead. All those knuckle draggers, like all they do is write emails and update CRM. Like AI is going to decimate them. What's interesting is like kind of what's happened is like software engineering, which like would be looked at a much more like, oh my God, the, the level of skill, proficiency, like literally the, the thousands of hours you need to be highly skilled, like that's what's getting chewed up first because there is, there's syntax, there's language, there's rules that can be relied upon and like the model's really good at that. Go-to-market is super quantum and changing every day. So, you know, finding people that are, um, understanding of that like reality, like That, that's where the, the fun's gonna come. And I know that's kind of like an open-ended abstract statement, but like, I think, I think the people that really understand that are going to be the most, uh, effective.

All right. So I think we're coming near to the close of the episode here. Thanks so much. So, uh, for sharing your wisdom, Zach, couple of more questions.

Hopefully it's useful.

Yeah, it is fascinating. If you were advising a VP of marketing or revenue today, like what's the one thing they should stop doing immediately because of how go-to-market is changing?

Stop doing immediately. Good question. I think the, the expectation that you have time to sit and have extremely high conviction around every decision, that world is gone. You need to act. You need to act decisively. You need to try new things. You are going to have 10 new competitors by the end of next quarter. Like, that's the world. So like, use that as the lightning rod of like, okay, we're gonna, we're gonna have 10 new competitors that we need to be thinking thoughtfully about and like have an approach for next quarter. Like, what are we gonna do? Like, we do not have time to let, let things breathe the way they used to, right? So I, I would say get, get rid of that assumption that you have time. Like it, it's is, I just had a post the other day. I was like, I was like trying to think about like, how do you frame this? It's like the, like the resting heart rate of the market has gone from 60 to 120 beats a minute. And like, you, you need to act as if, or like it will be impossible to be a leader. Like everyone is shipping so fast and you need to be on top of that because who knows, like maybe 4 weeks from now there is, it isn't Claude Code, it's something new none of us had heard of. And like, You're gonna need to shift on a dime, right?

So retire your set it and forget it mindset.

Yes. If you have one. Yes. That, that if you, if you had that, if that still remains, get rid of it.

Where can, uh, our audience connect with you, Zach, and any, any specific, uh, events or, or promotions or launches or anything coming up you want people to know about?

We have some cool launches coming up. We'll be, uh, Happy and excited partners of, uh, Go-To-Market Engineer School Cohort 3. Sign up there. You'll be able to work with me and our go-to-market engineering team. LinkedIn's the easiest. Please connect with me. Love hearing what people are up to. Of course, if we could be helpful, Octave is free. Get started, sign up, tell us what you think, give us feedback, book some time with our team. We're happy to help, you know, build out some cool workflows and show you what's possible. But, um, yeah, in general, excited to, uh, engage with community and, and have conversations. So find me on LinkedIn.

Awesome. All right. Fantastic. So, uh, to wrap then today, we, we dug into go-to-market and context engineering and how they're, they're really about turning your, your hard-won knowledge. That's step one. Your ICPs, your personas, your market point of view, uh, into a moat on top of increasingly sort of commoditized AI tools. And, and so if there's one takeaway, it's that the teams who win, they, they're not gonna just bolt on AI onto old playbooks. They have to, they'll codify what they know. They'll keep humans in the loop and, and design brand new motions with AI as a smarter partner, but not a replacement.

Well put.

All right. Awesome. Well, thanks again, Zach.

Thanks for having me, guys. Really appreciate it.

Thank you so much, Zach. It's been awesome as always.