Chapter 1: What is the main topic discussed in this episode?
Well, friends, this is The Change Log. I'm Adam Stachowiak, editor-in-chief here at changelog.com. And today on the show, I'm talking to Ajay Kalkarni, co-founder and CEO of Tiger Data. We trace his path to becoming a CEO. We dig into the themes that have shaped his career. And we explore how founder values end up forming company culture.
From his enterprise days to building Timescale, renaming to Tiger Data, we cover the whole journey. And here's where it gets really, really interesting. Agents in the database. Not the hype, the real thing. The real thing, baby.
We get into how fast you can go from idea to shift these days, what it actually means to talk to your database, and the whole API, CLI, MCP skills landscape we're all working in. Ajay drops this gem, build skills, not agents, and we unpack that in this episode.
Chapter 2: What journey led Ajay Kulkarni to become the CEO of Tiger Data?
A massive thank you to our friends and our partners at fly.io. That is the home of changelog.com. It could be your home too. Learn more at fly.io. Okay, let's talk agents and the database.
Chapter 3: How do founder values shape company culture?
Well, friends, I'm here with a good friend of mine, again, Kyle Galbraith, co-founder and CEO of depot.dev. Kyle, we are in an era of disruption, right? I would also describe it as rethinking what we thought was true. And I guess that's kind of the definition of disruption.
Chapter 4: What was the evolution from Timescale to Tiger Data?
But from your perspective, how are teams, reliability teams, CICD, pipeline teams, how are they all rethinking things? And where does depot fit into that?
In the conversations that I have with customers, a lot of DevOps teams, platform teams, site reliability teams, they're really looking at this new era of software engineering that we're all living in. And they're starting to question like the bottleneck is no longer the act of writing code. The bottleneck is shifting. The most time consuming part is integrating the code.
It's everything that comes after. It's the build, it's the pull request review, it's the deployment, it's the getting it into production.
Chapter 5: What does 'Agents in the database' really mean?
Once it's in production, it's scaling up support teams to support it, it's adding documentation, all of these downstream problems. And so through the lens of Depot, what we're really starting to think about is there's a very realistic possibility that
within the next two to three years, maybe even sooner, that we're going to enter a world where an engineering team of three people could theoretically have the velocity of an engineering team of 300 people. And what's the consequences of that? What's the consequences of the code velocity spiking up to that level with such a small team?
Chapter 6: How can you rapidly go from idea to shipped product?
There's no way three engineers are going to be able to code review all of the code that's being created If there's three engineers and 297 agents also creating features and fixing bugs. So that's just like from a pull request perspective.
But then you think about it through a build lens, too, of if your builds take 20 minutes with three humans and now you're going to have three humans and 297 agents also running. Well, like you definitely don't want your builds taking 20 minutes because now like the entire pinch point is the build pipeline.
And so we're starting to think a lot about how do we eliminate the bottlenecks that come downstream? And what can we do with Depot that streamlines that?
So obviously, friends, we are in an era of disruption. Things are changing. You know it. I know it. That's how it is. And the thing with production and what Kyle's talking about here is how in the world do you get your bills to be faster?
Chapter 7: What does Ajay mean by 'build skills, not agents'?
How do you get them to be more reliable, faster, more observability around those deployments? You need it. It's required. And Depot is there to help you. So a good first step is to go to depot.dev, get faster, try their trial. It's too easy. Again, depot.dev is where to go. It all begins at depot.dev.
So, friends, we're here with Ajay Kulkarni, a new friend of mine from Tiger Data, previously Timescale. We've had this relationship. We work with you as a sponsor. And I've been a fan, obviously, of Time Series Data.
Chapter 8: How is the landscape of databases changing with AI?
And I had ideas for you all. I've been working with Isabel behind the scenes. And then it finally came back to this moment here where you have agentic Postgres, which is just super interesting to me. So I thought we would dive deep into who you are, Ajay, what your journey might be and how you've come to love building databases. So let's start there.
Yeah, yeah. I'll try to give you the short term. I assume you love building databases. You know, I love building databases. I love building and I love solving problems. Databases are interesting, right? But it would not be the only thing I've done in my career.
I've been in love with technology since I was a kid and I remember using the internet for the first time in high school in 1995, 1996 and thinking, I don't know what this is, but this is fun. Yeah. And I was a pre-med at that point applying to colleges and I switched to computer science, went to MIT and I guess the rest is history. Uh, MIT is where I met my co-founder, by the way.
So that's how we know each other for 28 years.
That's wild to know a co-founder of 28 years. I mean the history and the, The level of trust and maybe somewhat antitrust. I don't know if that's the case.
It's not antitrust, but you know what it is? Vulnerability is what I mean by that. When he and I started working together at this point, probably 10 years ago, I remember thinking, I know what I like about Mike, and I know what I don't like about him. And I want to work with this guy. And I'm sure he felt similarly. And I think it's a little bit of like a...
I don't want to call it a spousal relationship, but almost, you know, you're like, hey, like, like, I like you for who you are, the whole package, even though sometimes that package annoys me. And I'm sure you say the same thing about me.
Well, Mike is not here, so we can't speak for him, but I'm assuming he might say something like that. So CEO of Tiger Data, you were under a different name, a different moniker before. I do want to go there, but I kind of want to zoom back out a second just to kind of identify who you are. But, you know, more so how you got here.
You mentioned MIT, Long Road, 20 years knowing Mike, met him at college, university, college. You know, what was the journey from there to go into, I suppose, your career? And what are some of the things you've done that you really feel have defined or identified who you are today?
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