Speaker 1: This is Techstrong TV.

Alan Shimel: Hey, everyone, we’re back. We’re here in Chicago at KubeKon. We’re wrapping up our day two coverage, our last guest for day two. We’ll be back tomorrow, though. But let me introduce you to Kyle Campbell, right?

Kyle Campbell: That’s right.

Alan Shimel: Kyle is the founder of cto.ai and we’re going to find out about cto.ai and a little bit about what they’re doing here at KubeKon. But before we do that, Kyle, first of all, welcome.

Kyle Campbell: Thank you.

Alan Shimel: Second of all, let’s hear a little bit about Kyle.

Kyle Campbell: Yeah, thanks.

Alan Shimel: Tell us your kind of journey.

Kyle Campbell: Yeah, well, first of all, great to meet you in person. I’ve talked in the past. Yeah, so my journey, I’ve told this story before, a little unconventional. I grew up in Nova Scotia in Canada, a small town. Been on the internet since the age of eight and just had no interest in the formal past. So I’ve been building software from the early days of the .com boom. I may not look at it, but I got some of the scar tissue. But I was self-taught software engineer, so open source was the key to my success and good developer tools.

Alan Shimel: Sure.

Kyle Campbell: And I came up through the cloud and open source era and then started founding developer platforms in 2014. The first company I built was a developer platform, the real estate space. Zillow acquired it in about eight months, which was interesting.

Alan Shimel: Very.

Kyle Campbell: And then I bootstrapped a DevOps agency quite successfully and started to find that there was a lot of opportunity for next generation developer platforms, which led me to cto.ai.

Alan Shimel: Excellent, man. What a great story too. You still up in Nova Scotia?

Kyle Campbell: I’m not. I moved to the other side of the country. I live in British Columbia now.

Alan Shimel: Good for you.

Kyle Campbell: Love the outdoors. Spend a lot of time with my son camping, fishing, and trying to get outdoors and just enjoy the beautiful-

Alan Shimel: Loving it. Yeah, no, it’s beautiful. I mean, not that Nova Scotia’s not beautiful. It’s brutal in the winter, but it’s a beautiful country, part of the country.

Let’s talk cto.ai now. So look, I’ve founded multiple companies myself. Every founder I’ve ever interviewed or spoken with in 30 years, they don’t just say wake up and say, “Oh, I feel like founding a company today.” There’s kind of like Richard Dreyfuss in Close Encounters of the Third Kind, right? There’s something driving you like, “I got to do this. This needs to get done.” What was driving you that needed to get done here with cto.ai?

Kyle Campbell: Yeah. I mean, as I described my past, a lot of my journey was self-taught and stand on the shoulders of giants. And really important thing for me was developer experience and ease of use and tooling early on in my career because that enabled me to really drive my competencies as a developer and keep up with these people that had computer science degrees and master’s and all these things, right?

Alan Shimel: Certainly.

Kyle Campbell: So when I thought about that and I also thought about where the future’s going and my passion for platform engineering, it became pretty obvious to me that what was missing in the market was a set of tools that were designed to embrace the future of developer experience and how AI can impact that from code to cloud.

So in 2016 or so, I started experimenting with the idea, and through 2020, I decided to formally launch cto.ai as a developer control plane is what we call it. The way to think about it is it’s a modern CI/CD platform where teams can compose their workflow across build, deployment, test, and preview. And as they work with these tools, they can interact with them in the CLI Slack, GitHub, talk to these workflows through sort of a prompt based model. And we collect telemetry data that allows them to then measure that against DORA metrics, which is-

Alan Shimel: It’s standard.

Kyle Campbell: … yeah, it’s a standard and I think, frankly, an empirical way to measure the developer experience. We don’t try to measure developer productivity. We think that’s the wrong question to ask. The question is how do I measure the experience the developer has in the same way that I would measure the experience my users have with my product? And if what we’re doing is building platforms to enable developer experience, we need a natively integrated way to measure that. And we also think that that measurement is a way to pave a future between how the developers experience those tools and how AI can support the developer experience and enhance developers with, frankly, superpowers over time.

Alan Shimel: So I was recently at a couple of user conferences, big DevOps companies, and it was interesting. Three conferences all use the same metric, which is that developers only spend about 30% of their time developing.

Kyle Campbell: State of DevOps Report 2018, I think?

Alan Shimel: But it was in there and it’s been kind of verified in several others. What do you think about that? Is it good thing, bad thing, something to be proud of, something we should be working on? What’s the deal?

Kyle Campbell: Yeah. Well, I think a pretty practical point of view in that as a software engineer, my goal is to release features that customers love and drive business value. And if I can do that at a higher velocity while maintaining quality, I mean, I think that that is a way that I, as an individual, can contribute to the success of the business and the team.

But I think what often happens is we get really obsessed about the individual developer. And I think any developer who looks at the idea that they only spend 30% of their time adding value isn’t going to like that very much. And I think we need to reframe the conversation away from developer productivity towards developer enablement and look at the tooling and the process that the developer experience promotes and how developers go from code to cloud and ask ourselves as a business leader, as a CTO who we work with a lot, is the tooling and the workflow that we’re supporting our team with and that developer experience, what they’re experiencing, is that driving results?

And I think DORA metrics is an empirical way to measure that, obviously, through anecdotes and surveys, but what we’ve really innovated on is creating a vertical integration with the tool chain that allows you to measure that in real time and then iterate on the tools quickly. And some of the teams can really own that themselves. And what the businesses should be doing is zooming out and asking themselves, “Yeah, how do we maximize the amount of time developers spend without individualizing that consideration?” There’s an innerloop and there’s an outerloop. And what DORA is really good for is measuring the outerloop of how we work in aggregate of teams. We need next generation platforms that make this data and this context more accessible to business leaders.

Alan Shimel: I don’t disagree with anything you said there, so we’re there with that. What about have you guys released any news or anything? What do you got going on around the show?

Kyle Campbell: Yeah, so for the last while, we’ve been focused on really building a rock solid workflow and tooling to basically set the premise of that next generation composable CI/CD vision. We’ve fed that data into DORA Metrics. You can now report on DORA metrics in real time, save those reports, share them with whoever one-on-ones, retros, so kind of up to you. And we’re starting to experiment with some data science, but something that’s really exciting that we just kind of put into production last week. We haven’t really officially announced, so I guess this is a first is we’ve released our first kind of AI-

Alan Shimel: Heard it here first.

Kyle Campbell: … yeah, heard it here first. Our first AI feature set, which is AI code review. And what we’re doing is we’re letting teams start with these sort of base models for how they can leverage AI in the code review process to get developers’ feedback earlier. But then, we want them to be able to do is enhance that model to really customize it to their preferences on their own kind of hardware, to customize those models to take into consideration their own specialized requirements and obviously protect proprietary information that’s so core to their beliefs. So we launched that into production, announcing it here first.

Alan Shimel: Really?

Kyle Campbell: And we’re looking for early adopters who can kind of test it out and help us stress test it and figure out how do we further enhance the context of that model with some of the information that is derived in these DORA metrics as well.

Alan Shimel: So here, we’re talking to this camera. Developers out there. You’re looking for them to kick this around a little bit. Kick the tires.

Kyle Campbell: That’s right. Yeah.

Alan Shimel: How do they do it?

Kyle Campbell: You’re a developer and you’re interested in how AI can support your CICD workflow, specifically code review, come over to cto.ai, sign up, send a message. I’d love to talk to you personally, software development yourself, and love to hear what you think, what you think are the limitations and hesitations, and more importantly, how do you think we can enhance this with other use cases? Because I think there’s a whole exciting set of use cases for AI and software delivery that is going to help software developers.

Alan Shimel: Absolutely.

Kyle Campbell: We embrace-

Alan Shimel: I had this conversation in an earlier interview today. Look, for people who aren’t tech, you show them an AI interface and some of the kind of parlor tricks it could do and they think it’s magical.

Kyle Campbell: Yes. Arthur C. Clark.

Alan Shimel: Right.

Kyle Campbell: Yeah.

Alan Shimel: Now, we know it’s not magic. It’s just putting one word in front of the other or one… but there are some uses that AI really shine certain. So it’s not meant to replace Google Search nor is it meant to replace software developers.

Kyle Campbell: No.

Alan Shimel: But it can empower software developers to be 10x more effective. And one of the ways it could teach you to code, right? You could put code in there and say, “Explain it to me.” It could review code, right? So either it’s writing code or it’s reviewing code. You shouldn’t have it doing both probably, but…

Kyle Campbell: It’s true.

Alan Shimel: Right. But if it’s using it for review, what a great use of the technology.

Kyle Campbell: Yeah. We’ve seen that the number one thing that slows down time to market in feature sets for developers is waiting for code review. And while I’m not sure that it’ll be the same thing as you and I pair programming and getting into the nitty-gritty details, if we can make sure that every developer can get a code review instantly just by adding a label and then that we can tailor the quality of that code review with more context that is supported by how the team thinks about quality. I think this is an important example of how we can accelerate the needs of developers and the developer experience with AI that still leaves all the control in the hands of the developer to decide, “Is this rational? Is this a hallucination? Is this the appropriate time?” But the feedback loop that we can get from this is, I think, a really great beachhead and why we chose to start there.

Alan Shimel: Absolutely. And we’ll see. I don’t think we scratched the surface yet on how we’re going to use AI, but this is certainly a real definitive first step that I see us going with, right?

Kyle Campbell: I think so. And I think the call to action for other software vendors out there is to think about reinstrumenting what they’re offering to prepare for this because I think there’s a necessary hesitance around AI. I think rightly so. But if we can think about how we can take control of it, how softwares can take control of it. Software engineers are perfectly suited to be some of the first stewards of these problems. Just like we see AI and code generation, I think the next natural step is to support it within code review. And then we’ll start looking at how smarter deployments, smarter rollbacks, and obviously, operations can be enhanced with AI. And this place is a perfect example of people trying to solve that problem.

Alan Shimel: Absolutely. Absolutely. And here’s the other thing. I’ve been in technology a long time. You don’t put these genies back in their bottles.

Kyle Campbell: Right.

Alan Shimel: Once they’re out, they’re out. And so like it or not, they’re here. And I think you could… if you can’t beat them, join them.

Kyle Campbell: You can’t stop Moore’s Law. I mean, this the pathway that the world is on.

Alan Shimel: No, you’re not. You’re just not going to stop it. That’s the way it is. It’s great stuff, man. I love the attitude. I love having you on here. Cto.ai. Again, if you’re looking to help Kyle out, kick the tires on this AI code review product they got coming on, it’s fantastic. So let’s check it out.

Kyle Campbell: All right. Thank you so much.

Alan Shimel: All right. Hey, Kyle, enjoy the rest of your KubeKon. cto.ai wrapping up day two in Chicago at KubeKon. We’re going to be here tomorrow morning. I think we’re on at 10. We’re only here till two tomorrow because it wraps early tomorrow. But we’ll be back with a full load. We hope you’ve enjoyed today. On Demand is available at Techstrong TV. And so if you missed anything, do check it out. This is Alan Shimel. We’re out.