Jun 9, 2026 · 48 min · 11 segments
Mark Deacon, CRO of CaniBuild, has gone further than most leaders talking about agentic GTM. He's actually built it, measured it, and has the numbers to back it up: a 400% improvement in revenue per…
Mark DeaconGuest
Noah MarksHost
Andy MowatHost
But I'm curious, how did you do that eval in your mind? Or do you feel like we're not all there yet in terms of the tech to be able to build that from scratch?

Uh, and you know, whenever we have a pain point within the business, we're looking to solve it.

Now we always going AI first pathway in, uh, in, in what we're doing and, you know, with everything we are going through that process of trying to decide, you know, do we buy or build in this scenario? My, uh, own principle is around, you know, not to build everything.

Um, you know, I think it's easy to underestimate the cost and time to like maintain these tools.

And because the technology is evolving so quickly, if you build it, you can build a version one, but then as things evolve, as things get better, new features, new functionality, like with the AISDR, say 11X, they're constantly developing new features and releasing new features now.

if we're building that we would have to be the ones continuously thinking about the tool what new features building that and then maintaining it you know if it's connected and if it's connected into other tools like if they update their api you're going to have to read uh rebuild it as well and so When it comes to tools that are more complicated, that are reliant to be 100% reliable and uptime is critical as well, we've defaulted down the buy route.

When it comes to other tools, like if it's to do with say like automated reporting or, you know, with our AI operating system that we've built where it's like creating, helping automate the whole marketing stack and auto create, we're building like an AI ad factory that like automates like meta campaigns and everything else, which I guess isn't as critical to like have like 100% uptime.

And it's something so custom that it's better to build than we go down the build path.

personalization component, I think is never going to be solved by the vendors at this point.

So I'm curious then on your, can you describe what your tech stack looks like and how it's changed over the last year or two? I'm curious where you've gone Fender versus build.

So we were fortunate that our CEO within the company was very bullish on AI, very supportive, able to carve out budget to be able to deploy in this area.

And so we uh we went all in to focus on how do we now start being an ai first organization not just from like a product perspective but also from a operations perspective as well and so the approach we took was rather than just going you know what ai tool sounds great and we should sign up to we actually just went through the normal business process you would within any quarter and go okay what are the you know in our quarterly planning like what are the main challenges for our business right now what are the main problems what are the main opportunities And rather than defaulting to a non-AI solution, we go, well, how do we solve this with AI? So one of the pain points we were facing at the time was this whole like speed to lead piece that I mentioned.

But I'm curious, how did you do that eval in your mind? Or do you feel like we're not all there yet in terms of the tech to be able to build that from scratch?

Uh, and you know, whenever we have a pain point within the business, we're looking to solve it.

Now we always going AI first pathway in, uh, in, in what we're doing and, you know, with everything we are going through that process of trying to decide, you know, do we buy or build in this scenario? My, uh, own principle is around, you know, not to build everything.

Um, you know, I think it's easy to underestimate the cost and time to like maintain these tools.

And because the technology is evolving so quickly, if you build it, you can build a version one, but then as things evolve, as things get better, new features, new functionality, like with the AISDR, say 11X, they're constantly developing new features and releasing new features now.

if we're building that we would have to be the ones continuously thinking about the tool what new features building that and then maintaining it you know if it's connected and if it's connected into other tools like if they update their api you're going to have to read uh rebuild it as well and so When it comes to tools that are more complicated, that are reliant to be 100% reliable and uptime is critical as well, we've defaulted down the buy route.

When it comes to other tools, like if it's to do with say like automated reporting or, you know, with our AI operating system that we've built where it's like creating, helping automate the whole marketing stack and auto create, we're building like an AI ad factory that like automates like meta campaigns and everything else, which I guess isn't as critical to like have like 100% uptime.

And it's something so custom that it's better to build than we go down the build path.

personalization component, I think is never going to be solved by the vendors at this point.

So I'm curious then on your, can you describe what your tech stack looks like and how it's changed over the last year or two? I'm curious where you've gone Fender versus build.

So we were fortunate that our CEO within the company was very bullish on AI, very supportive, able to carve out budget to be able to deploy in this area.

And so we uh we went all in to focus on how do we now start being an ai first organization not just from like a product perspective but also from a operations perspective as well and so the approach we took was rather than just going you know what ai tool sounds great and we should sign up to we actually just went through the normal business process you would within any quarter and go okay what are the you know in our quarterly planning like what are the main challenges for our business right now what are the main problems what are the main opportunities And rather than defaulting to a non-AI solution, we go, well, how do we solve this with AI? So one of the pain points we were facing at the time was this whole like speed to lead piece that I mentioned.
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