 Hi this is Yoho Sapin Bharti and we are back with our predictions series and today we have with us Johnny Dallas, CEO and co-founder at ZIT. Johnny, it's great to have you on the show. Hey Sapin, it's great to be here. I'm excited to chat today about some of the predictions we see for 2024 in DevOps. Of course, I'm going to ask you to grab your crystal ball and share your predictions. But before that, just quickly tell us what is ZIT all about? Yeah, happy to. So I'm Johnny Dallas and the co-founder and CEO of ZIT. ZIT is a CICD and deployment platform for Kubernetes and cloud native applications. Essentially, we help teams deploy and operate their cloud infrastructure as efficiently as possible, ensuring that you have the best field of productivity you can, high-quality security, and high availability for all of your cloud infrastructure. Now it's time for you to pick your crystal ball and share your predictions with us. Let me dive into my crystal ball. I've got a couple of predictions for you in terms of what we expect to see in the cloud and DevOps world in 2024. The first one of them is one that we've been talking about for a while now actually, but we're really starting to see pick up in 2024. That's the rise of specialized clouds. At ZIT, we work with a bunch of different cloud providers and you typically think about the big hyperscalers, the big three clouds. We're seeing more and more cloud providers that are starting up that are specialized on one specific thing, whether it's Linode Akamai's connected cloud specializing on network and security, or GPU-centric clouds like CoreWeave or even front-end clouds at Versailles and Netlify. We're seeing more and more cloud providers that are doing one thing really, really well as opposed to trying to be your all-in-one cloud provider. In addition to specialized clouds coming up in 2024, I think the big thing on everyone's mind for 2024 is AI and how is AI going to disrupt every industry. Really, when we look at AI in DevOps and in cloud infrastructure, we see the fields of MLOps and LLMOps, some of these new industries that are starting to form about how do we do AI at scale? What are the right operations around these new AI paradigms? We're going to see them get a lot more mature this coming year. We predict that we'll see things like LLMOps and MLOps get to the same level of maturity or approaching the same level of maturity as what we see with DevOps today. There's going to be some very different structures in there, very different to run an agent or an LLM than running that typical web service. There's going to be a lot of innovation that we'll figure out there. In a similar vein on the AI track, I think one other big change that we're going to see in 2024 is there's going to be a lot more code written by AI. For a long time now, we've had generated code, we've had generators, we've had autocomplete, and we've started to see more and more tools like GitHub Coat Pilot coming out that's making it easier to write code. But in 2024, we think that's really going to hit the stride. We're going to see the vast majority of code bases really be written by AI as opposed to by humans. One downstream effect of that, as we see, say, 80% or more of code bases being written by AI, is we're going to see bigger code bases. We predict that in 2024, there's going to be a five to 10x increase in the average size of a code base. We're going to need better tools to handle code bases of that size. AI is going to make it easier to write it fast and it's going to make it easier to analyze it fast and operate on it quickly. We're going to see bigger code bases, more code written by AI. We're going to need to see new tools come out that help us manage that more effectively. Now, last but not least, as we head into 2024, well, everyone's very excited about some of the technology that's coming out and some of the scale that that's going to enable. We're still seeing from engineering leaders some reticence around budget. I think the last thing that we're going to see in 2024 is going to be teams that are looking to scale primarily from tooling rather than headcount. We're seeing teams that are going to need to be doing more with the same resources they have or even less resources than they currently have, and we're going to be finding creative solutions to accomplish those business goals. The way that this gets done is software, it's tools, it's these platforms and existing paradigms and existing workflows that abstract away some of the work that would be manual otherwise. And so we're going to see a lot more investment in depth tooling and teams looking to scale with the existing headcount or smaller headcount accomplishing more. Now, in light of these predictions, can you also talk about what kind of challenges you see will be there for the market, for the users, for the ecosystem, and even for a company like Zit to tackle? I think two of the big challenges that we're going to see in this coming year, and we're seeing both across our market and in our customers, but we're also looking at ourselves. One is the budget piece that I mentioned a moment ago. Teams are really going to have to figure out how do we take advantage of this AI innovation? How do we stay at the cutting edge without going and building giant teams around it? There's just not enough people to go around, there's not enough money to go around and there's too much to build. So I think that's going to be something that the whole industry has to grapple with and figure out how do we get there. The other piece is a challenge, but it's a bit of a double-edged sword because I'm an engineer by trade. It gets me excited as well, which is figuring out what does AI ops look like? We're at a new frontier at a golden age of let's figure out what these things look like, how do we run them at scale? We don't really know yet. There's unsolved problems in there. And while that's both a challenge, it is also really exciting proposition. And so I think that's something that we're thinking about a lot on our roadmap is what are the challenges that our customers are going to face there? What can we innovate on? What can we be creative? Because it's going to take a lot of creativity and innovation that's coming here to make this all work. And what is going to be the focus of Zed or your focus this year? Our focus this coming year is very similar to what it always is, which is customers. We need to stay as tight as we can, take the hip to our customers, make sure that we're solving the most pressing problems for them, making sure that they're informing us what are the real problems that they're cutting edge. And it's always easy to imagine problems or start working on things that don't actually matter. But especially when these customers are getting tighter on budget, especially when there's more that they're trying to accomplish and especially when there's these new AI paradigms coming out, we need to make sure that we are as tight as possible to these customers and making sure we're serving every one of their problems as effectively as we can. So I think that's going to take us in a lot of different interesting areas. But the biggest thing that we're telling our team this year is if you're talking to customers once a week, talk to them twice a week. If you're talking to them twice a week, talk to them four times a week. But we need to be talking to them as much as we can and making sure we're as tight as we can with them. Johnny, thank you so much for taking time out today and sharing your predictions with us. I would love to have you again next year, not only to just check how many of your predictions turn out to be true, but also get the next set of predictions. But I really appreciate your time today. Thank you. Awesome. Thanks for having me. It was great to be here. And I look forward to seeing exactly what happens this coming year. Happy to come back on and see what did I make a mistake on? What was I right on? What did I underestimate? If it's going to be 100 exercise, good basis, not 5 to 10x. Let's see.