Capital One operates less like a traditional bank and more like a "technology company that happens to do banking." Ameesh Paleja, EVP of Enterprise Platforms, joins the show to explain how this philosophy empowers their 14,000 technologists to innovate at the speed of a startup despite operating in a highly regulated industry.
Ameesh breaks down how standardization serves as the unsung hero of enterprise scale, revealing how consolidating build processes removes undifferentiated heavy lifting so engineers can focus on creative problem-solving. He also details how his team automates SRE tasks to prevent burnout and outlines a unique funnel strategy for AI adoption that balances cutting-edge experimentation with strict security and governance.
Show Notes
- Learn more: capitalone.com/tech
- Read the blog: capitalone.com/tech/blog/
- Erin Yepis: Connect with Ameesh: LinkedIn | X (Twitter)
Transcript
(Disclaimer: may contain unintentionally confusing, inaccurate and/or amusing transcription errors)
[00:00:00] Dan Lines: Hey, what's up everyone? Welcome to Dev Interrupted.
[00:00:03] Dan Lines: We have an amazing show for you today we are going to be exploring how a highly regulated data-driven enterprise actually ships faster without burning out engineers. Joining me today is Ameesh Paleja, executive VP at Capital One, where he leads enterprise platform technology. His team builds the experiences and paved roads that thousands of Capital One engineers depend on every single day.
[00:00:36] Dan Lines: you did hear me right it is thousand. So Capital One has 14,000 technologists, so about 85% of them are engineers, and they were notably the first financial services company to move fully to the cloud. That legacy of innovating matters, and it matters a lot today.
[00:00:55] Dan Lines: So Ameesh, welcome to Dev Interrupted.
[00:00:58] Ameesh Paleja: Thank you, Dan. I'm really [00:01:00] happy to be here and a big fan of the podcast.
[00:01:01] Dan Lines: Awesome to have you here. We have a bunch of, I think, really interesting topics. We're gonna run through at least three of them, but before we jump in, could you tell us a little bit about yourself, how you ended up at Capital One, you know what your role is?
[00:01:18] Dan Lines: Give us the background.
[00:01:19] Ameesh Paleja: Yeah, my pleasure. So. I'm an engineer by trade, studied computer science at UC San Diego, and, uh, first job outta school was working on the Windows kernel at Microsoft. Um, did that for a few years, was over at Amazon for a long time, about 11 years. So had a lot of time working on everything that didn't go into little Brown box.
[00:01:37] Ameesh Paleja: So if you've ever watched a TV show on Prime video, uh, that's my baby. I was the first person on that team and built that out. Um, and then, uh, did my own startup and went through that, that whole rigmarole, a company called Atom Tickets and, um, ran a TV channel for a little while, which is a little bit of a left turn.
[00:01:55] Ameesh Paleja: And, uh, eventually made my way to, uh, Google. Right before I joined Capital [00:02:00] One, I was the VP of Eng running Gmail calendar and chat. And then here I have an amazing role. my job is to make all our lines of businesses, uh, you know, uh. Harder, better, faster, stronger, uh, you know, do a little Daft Punk reference.
[00:02:14] Ameesh Paleja: Um, but you know, it, it's, my goal is basically to create platforms that unlock, uh, speed and leverage for all the different lines of businesses within Capital One. So, um, it's a pretty big responsibility and I'm grateful for the opportunity to really kind of revolutionize the financial industry.
[00:02:32] Dan Lines: That's amazing, man.
[00:02:33] Dan Lines: It, I mean, your background, I think for our listeners, a lot of people would want to have that type of career. I heard of a lot of interesting things working at Microsoft on the kernel. I heard Prime Video if I got, my kids are watching a lot of Baby Shark, so we have a lot of Prime Video. And now, uh, being at Capital One and you're like.
[00:02:56] Dan Lines: Leading this massive team. I have to ask you, and [00:03:00] this is un unscripted, uh, question, do you have any career advice for maybe someone that is, you know, a leader in the industry, but but wants to have a career journey like you, you has, is there anything, any tip that you would give to someone that's kind of trying to progress the way that you did?
[00:03:18] Ameesh Paleja: I would say I have two tips. Um, and given, given the audience is like, we're, we're all engineers on the call. Like, I, I want to say first and foremost, you gotta be a great communicator. Um, oftentimes we, we put that stuff on the side, but being a great storyteller, being able to connect with, different, uh, functional roles.
[00:03:38] Ameesh Paleja: Your, you know, product management, your business leaders, your, you know, your finance leaders. Really being able to understand and empathize what they're going through, I think is incredibly important. And in the second, and I think the most powerful piece of advice I can give is get comfortable being uncomfortable.
[00:03:53] Ameesh Paleja: The biggest compliment I've ever gotten from my, from my mentor was. Uh, Ameesh is so, [00:04:00] uh, confident in his abilities that he is willing to leave a good thing to try and get something even better. And so I try to put myself in situations where I'm flexing muscles that I don't, um, I don't normally use because it helps me become more well-rounded.
[00:04:15] Ameesh Paleja: Right? So, uh, going from consumer apps to enterprise apps, going from startups to big companies, you know, I'm really trying to like push myself to say, what, what am I not? Comfortable with And how do I kind of lean into that? Kind of like, it's almost like exposure therapy, but, uh, professionally, so I would say get comfortable being uncomfortable and learn to communicate really well.
[00:04:37] Ameesh Paleja: And I think the, the world is, is full of great opportunities.
[00:04:41] Dan Lines: That's amazing advice. Really appreciate it. It sounds like there's a, a triple threat, first of all. Yeah. We come from an engineering background, so most people listening have that. Uh, but then you mentioned, I think this is what's hard, being a great communicator probably to the business and, [00:05:00] uh, going outside that comfort zone.
[00:05:02] Dan Lines: Really appreciate you sharing, uh, that with us Before we dive into our first topic, but now our first topic's here and. This topic is going to be around standardization and at Capital One, hopefully I have the numbers right. Let's say that there's 14,000, we're calling them technol technologists, but 85%, uh, if I have this right, are engineers.
[00:05:26] Dan Lines: Right? A lot of people here are leading like engineering, uh, organizations that, that are listening today and standardization. I come from a background of being a VP of engineering. There's usually pros and cons, or when we think about developer experience, there's like, okay, standardization. It can really help maybe in some areas, uh, not so much, or we might get some of that, uh, negative feedback from from the developers.
[00:05:52] Dan Lines: But I wanna kick us off like this. How does standardization become the unsung hero that [00:06:00] truly unlocks like massive scale automation and what role does it play with like platforms and deploying and automation? I can't even like fathom this, uh, how it would work for Capital One.
[00:06:14] Ameesh Paleja: I mean, look, this is, this is a big question and, and really core to, to my role here, um, particularly at the size and scale that Capital One is operating. Uh, you know, we. We're a large, uh, corporation that has an incredible responsibility to our customers, right? I mean, we deal with people's money. So like people buy their gas or groceries with us, we have to get it right all the time.
[00:06:34] Ameesh Paleja: And when we think about standardization, it really, you know, kind of comes to how do we stay well managed with 14,000 developers, writing code, shipping code, deploying code? How do we make sure that we don't have high severity incidences? How do we make sure that. You know, when we say, uh, you know, I've, you know, debited a dollar from your account or added a dollar to your account, that it's always correct.
[00:06:56] Ameesh Paleja: It's always resilient when AWS has an outage [00:07:00] or some, you know, some other place, uh, has issues I like, there's a lot of. Opportunity for us to create the right systems and platforms that enable, better resiliency, better security, better kind of well-managed systems operations. But also, once you have all that in place, it unlocks the capability to actually develop, develop features and functionality that help customers and the businesses grow.
[00:07:26] Ameesh Paleja: Right? It's, it's a huge opportunity. And when you think about standardization, imagine if I had everybody to say, Hey, I, I don't like S3 as an example, I'm gonna use a hyper, a hyperbolic example here. I'm gonna build my own storage solution. People will look at me like I'm crazy, right?
[00:07:41] Ameesh Paleja: Uh, because there is a standard there that is well governed. It, it's understandable. The APIs are there, there's a lot of tools and functionality built around it. And so when you take that example to extend it all the way across your entire stack, there is very clear opportunity opportunities to create scale and
[00:07:59] Ameesh Paleja: take, kind of [00:08:00] the mundane, undifferentiated kind of heavy lifting off of people's plates. You know, what I find is that engineers want to build cool things. Oftentimes they kinda get stuck in a little bit of a rut of, you know, I wanna debate the, the, the pros and cons of like Kafka versus Kinesis. But really that's not the thing that the customers are gonna love.
[00:08:21] Ameesh Paleja: That's not the thing that like. You know, my mom and dad are gonna be like excited, like, oh my son built that. Right? So I wanna help people think about standardization as a pathway to automation that takes the mundane work, the undifferentiated lifting work, you know, the arbitrary uniqueness out of the stack so that we can have a standard set of reusable and, uh, powerful components that are operationally excellent and highly performant.
[00:08:47] Dan Lines: I like the way that you explained it, and I think for the listeners there's something really, really important context wise that we have to reiterate. We're talking about Capital One, we're talking about people's money. People don't mess [00:09:00] around with their money all the way down to the individual person.
[00:09:04] Dan Lines: Uh, Hey, Ameesh, don't mess up my money, please. But also all I, I'm sure you're working with like businesses and all of, all of that money is super serious, uh, in America and around the world. So for the listeners, it's like in this whole context of the conversation, think about components of your product that you have to get right.
[00:09:26] Dan Lines: There's no room for this is experimental or Yeah, we're just trying to move fast. And if a bug gets released, okay, we could just fix it, you know, within an hour. We're not in that mode, we're in money mode. So that, that's the mindset. Um, now with that, I wanna ask you, is there. One, maybe like specific example that you could think of at Capital One, uh, where you came in and said like, Hey, this thing wasn't standardized before.
[00:09:58] Dan Lines: I know you probably can't share everything with us, but [00:10:00] one example like, Hey, this thing wasn't as standardized as we'd like it, and you dedicated effort, uh, to making it standardized. Is there something that comes to mind there?
[00:10:11] Ameesh Paleja: I would say, um, a great example of where we went from kind of good to great, um, is our kind of operations and SRE uh, team.
[00:10:21] Ameesh Paleja: When you think about standardization, you have to start all the way at the bottom of the stack and say the, our data, our logs, right? Data's growing so fast these days. It's like a 25% year on year, uh, CAGR and like you think about, um, I wanna say the last stat I saw was like. We're, the world is creating like 180 zetabytes of data a year, growing at 25%.
[00:10:44] Ameesh Paleja: It's wild. Like,
[00:10:45] Dan Lines: yeah. Like you can't even comprehend like that. My brain doesn't work on zetabytes. Like I Yeah, right.
[00:10:52] Ameesh Paleja: You know, even, even exabytes are hard to kind of imagine. Uh, you know, so when you try to grab zetabytes, it's wild. And then, you know, the [00:11:00] other fascinating stat was, uh. In the last three years, something like 90% of the world's data historically was created in the last three years, right?
[00:11:09] Ameesh Paleja: So of all data, of all time, that's such a wild thing. And so when you think about just a simple foundational piece of like, where do I put my logs? Like I'm collecting more and more things, quick streams, events, I'm, I'm collecting, you know, uh, uh, instrumentation and, and, uh, longitudinal data and. How do we keep it organized?
[00:11:28] Ameesh Paleja: How do you know? So we start off with great, get great data, right? And then on top of that, once you build that, then you can start building standardized automation to say, okay, I, have my metrics, and I have my observability. And then when
[00:11:40] Ameesh Paleja: you have that, you're like, what do I do when there's a problem?
[00:11:42] Ameesh Paleja: Well, I can build automated playbooks. And then once you have your automated playbooks, now you're like, well. I have agent software looking around corners, finding correlated paths that maybe humans wouldn't be observing, but like a machine could look at thousands of variables every second all the time and catch, [00:12:00] things be, you know, while there's smoke and not fire.
[00:12:01] Ameesh Paleja: Um, and so our ability to actually drive, um. Incredible improvements in reductions of our high severity incidences. Our meantime to detection, our meantime to resolution have all improved dramatically. And I, I have to kind of lay it at the feet of just amazing engineers, amazing data folks all working together in concert to create the standardization, the automat automation, and the enterprise platforms that are gonna actually get us to the spot where we feel very comfortable that.
[00:12:31] Ameesh Paleja: We know what's happening in our world. We know we can analyze all the data. We can quickly find out what the problem is and then quickly resolve it. And the best part, Dan, is, is a lot of this is automated, right? Yeah. It used to be that like somebody gets paged at three in the morning and, uh, you know, I, listen, I've carried a pager myself, and I, you know, it's miserable.
[00:12:50] Ameesh Paleja: You're like waking up bleary-eyed, you're looking at logs, you're going on Splunk, you're doing this and that, and you're like, where the hell is the problem? And what if the machine just told you that? [00:13:00] Right. We're at a time where that's actually really possible. Like it's more than possible. It's like it's, it's actually happening right now.
[00:13:06] Ameesh Paleja: And uh, the folks here have just shown a lot of like, thoughtfulness, grit, and innovation to kind of make that happen. And I, it's like a very powerful story for us.
[00:13:16] Dan Lines: thank you for sharing. That's a great example. Um, our customer base at LinearB, so I know a lot of the audience is familiar with MTTR, meantime to, uh, restore recovery change failure rate.
[00:13:28] Dan Lines: These are things that are tracked. These are things that, um, are presented at board meetings. These are things that you might even, I, I don't know at Capital One, but I'm sure there are metrics that you need to show. To someone and, um, SRE teams, that can be a high pressure job. I mean, SRE like you said, you could be woken up in the middle of the night.
[00:13:50] Dan Lines: You could be on not much sleep. The pressure's on to figure out what the heck is going on here. And I would think that automating that, and I'm [00:14:00] sure you're doing stuff with AI and I can figure out, you know, the insights and all of that, probably goes a long way to help those folks. And when you were, uh, thinking of, of that initiative going, uh, from Good to Great.
[00:14:14] Dan Lines: Is it like, should I be thinking, okay, I need all my logs in one place under one technology, or is it like, Hey, I already had it all in one place, but it's more like, let me put some AI on top of this so I can like decipher the insights and I can talk to it like. Could, is there any specifics there? 'cause what I'm trying to get to for the audience is like, how do you like, think about deducing this problem into like steps, uh, to get to standardization?
[00:14:44] Ameesh Paleja: De the decomposition is a tricky problem, right? It's like what you start with stuff's this big with this many people working on it. I would say, you know, one of the first things is really just break down the problem into its kind of, [00:15:00] uh. Foundational pieces and then all the, the steps that you can kind of go up.
[00:15:05] Ameesh Paleja: Right. And so as like a simple example, let's pick on data for a moment.
[00:15:08] Dan Lines: Right? Okay.
[00:15:09] Ameesh Paleja: People are writing log files in different ways. The tools that they use that they write them with are different. How do we, like, how do we consolidate on like, oh, I'm using UTC over here and I'm using, uh, Pacific time over there.
[00:15:20] Ameesh Paleja: And the format, some, some of them are in Parquet, some of 'em are in different formats. Some are using, uh, you know, uh, Apache iceberg format or Delta from Databricks. Like, there's a lot of like, you know, arbitrary uniqueness within the stack and. Even just the destination of where do we put it? Right. Some of it we're storing in log files, some of it we're storing on Yeah.
[00:15:42] Ameesh Paleja: Uh, in databases. And so picking some choices that I think a lot of times these are just six of one and a half a dozen another, and when you have, you know, 14,000 developers working on this stuff, you're bound to get differentiated answers. It's not, there's no bad dogs in this. Right. But it's [00:16:00] like, if nobody's actually declared a standard to say we're all gonna write
[00:16:04] Ameesh Paleja: in this format, in this location. So it sits in the lake. And then we have option value to say, analytics can run over here, AI can run over here, operations can run here, but they're all gonna leverage the same data source. That becomes an incredibly powerful story. And then, you know, it eliminates a lot of variation that just, uh, makes all the automation super painful and, and kind of, uh, it makes the juice not worth the squeeze.
[00:16:30] Ameesh Paleja: Um, and so like. The more you can kind of standardize on some of these simple decisions right up front, the easier it gets when you're going up the stack to, to make some of these, uh, more interesting automation capabilities available.
[00:16:42] Dan Lines: that totally makes sense. I wanted to pick your brain on this because, uh, it's similar to either the customers that we've worked with or my own experience.
[00:16:53] Dan Lines: Uh, when I think about standardization, I think you gave actually the same, same example. A lot of the times I think [00:17:00] about quality. You gave an example, like when I think SRE, I think Okay. Like helping us improve quality, make sure there's not outages and like respond quickly and that type of thing. And uh, for the customers that I'm working with, and you probably already have this, but we think about pull request quality.
[00:17:19] Dan Lines: So for example, a pull request gets opened. What are the set of standards across all teams that we at least go through? It could be, Hey, we do an AI code review, but then we have rules that a human needs to review it. In some situations we have test coverage, um, and the reason. For me, when I think about standardization and, and quality, uh, I think they go together ve very well, but they also then lead to efficiency.
[00:17:48] Dan Lines: Like if you're in engineering, you kind of know that there's like a, like, quality can actually make you move faster and all of that. Um, so now they'll put you on the spot. I am gonna, uh, do it. Uh, do [00:18:00] you have. Uh, a standardized like pull request process. Does your team help with that at, at all? And, and what do you think about like, quality and standardization?
[00:18:11] Dan Lines: Do those go together for, for you as well?
[00:18:14] Ameesh Paleja: I love this question and it's, it's such an interesting topic because there's a lot of nuance buried within it. Um, I'll start off by just simply saying like, my, my team owns the developer experience at Capital One. So the full kind of SDLC, uh, pipeline, It's an exciting space and there's a lot of innovation going on, but there's a lot that, you know, we could bring into the system and a lot of variation that spins up.
[00:18:36] Ameesh Paleja: The first and biggest, biggest thing that we did was we consolidated on one built pipeline, right? So instead of having hundreds of Jenkin instances running around, you know, Gradle doing this and that, right? We said, Hey, we're gonna have one pipeline, which we actually call, okay? Totally. One pipeline, Um, we, we, we spent a lot of time and much of the credit of, you know, our, our founder Rich and our, our board members and our, [00:19:00] uh, executive committee, they were all like, bought in. Like when I came into the company, I didn't have to sell anybody on this. They were like, this is important to get standardized on this front.
[00:19:09] Ameesh Paleja: And what we found was from a quality perspective, right, we're able to implement the right tools and the right instrumentation right in the bill pipeline so that as we're moving out, do we have the right images? Do we have, you know, as an example, like do we have ral list images that get rid of a bunch of vulnerabilities that we don't need to have, right?
[00:19:27] Ameesh Paleja: That's, that kind of stuff is like, if you're standardized, it's a lot easier, right? It improves our quality, so we're not running around with our like heads cut out going, oh my God, log for J this, and we have to like, everybody's scrambling for the next month and a half, right? We're like, oh, this one library and everybody picks up the change.
[00:19:43] Ameesh Paleja: We just need to redeploy right? When we think about things like, code reviews and, you know, it's with this size of an organization, you're gonna get uneven code reviews on your prs, right? Okay. You're just like, you're gonna have some junior people looking at it. You're gonna have some very senior [00:20:00] people.
[00:20:00] Ameesh Paleja: You know, we fall into the classic trap of, oh, I submitted. A thousand line PR and I get zero comments and I submit one line PR and I get 500 comments on. Yeah, very Like very typically. '
[00:20:12] Dan Lines: cause who wants to review a thousand line pr? It's gonna be hard to get feedback.
[00:20:16] Ameesh Paleja: Right. And so can we put policies in place?
[00:20:18] Ameesh Paleja: And that's a different type of standardization. Right. And you know, you know, I, I, I kind of look at that and say, what are the best practices that we can teach through policy? What are the best practices that we can enable? Via kind of AI code reviewers, right? Things like, oh, you have too many return, uh, points and dysfunction.
[00:20:36] Ameesh Paleja: It's you gotta, your matic complexity is too high, you know, refactor this, or there's copy and paste code here. That should be a function and just break it down. All of these things are super powerful. They up level the quality of all the code that's being developed. And it gets us to a point where I think is the most important thing is that once you enable these things in the SDLC pipeline.
[00:20:58] Ameesh Paleja: You are on [00:21:00] a path of continuous development, right? At the end of the day, when I, when I speak to our executive committee and our board and our, uh, senior leadership, right, they want to be able to develop, develop and deliver better features faster to, um, our customers. But I think you and I both know that so many times, the defects that you see and the incidents you see are deployment related.
[00:21:25] Ameesh Paleja: Like, I pushed out this nothing broken, and I have to roll it all back. So how do we, how do we minimize the amount of pain that we feel at that time? So, can we have automated testing? How do we Well, you want automated testing. Well, you have to have automated, uh, you know, the, the right frameworks and the right tools, and those have to be consistent so that people can build on top of them.
[00:21:45] Ameesh Paleja: And you have the environments. How do you standardize your environments and automate those environments, right? All of these things lead to a, a spot where we're actually doing CICD properly. That creates this ecosystem, and I'm, I'm very proud of, of the [00:22:00] folks here, that we've been able to increase our, number of changes mm-hmm.
[00:22:07] Ameesh Paleja: Pretty dramatically while decreasing the number of defects going out to production because we've implemented all these quality tests and in, uh, systems and tools right up front and. Dan, the, the biggest thing I would say, the biggest kind of unlock was shifting as much left as we possibly could. So wherever we could kind of help the developer on the inner loop on the, in the IDE or you know, where before they even get to the point where they have to run this test.
[00:22:33] Ameesh Paleja: Like how much can they do on their own quickly and efficiently on their laptop when they're, you know, sitting in the airplane or wherever they're working, right. Give 'em as much power as we possibly can to debug as much, and then when it goes through the whole pipeline. We're doing all the kind of last validations, the checks and the, the, the, you know, the standardized tooling against it to make sure that we're pushing out great quality code that's been validated lots of different [00:23:00] ways.
[00:23:00] Dan Lines: Yeah, like, uh, and again, like you're in a situa, it sounded like you had the mandate of, Hey, let's build features faster, which I think mo most engineering leaders, uh, get that mandate, but we cannot reduce quality and we're probably in this regulated world and we can't get anything wrong. So that's kind of a tough challenge.
[00:23:19] Dan Lines: Now, what you had going for you, it sounds like, is the business was already behind you on standardization. Like you didn't have to prove, uh, why it's important, uh, for someone listening that wants more standardization. You might not know ' cause you didn't have to do it here, but you might. Uh, if I had to prove to my business, like why a standard, let's take the build pipeline.
[00:23:43] Dan Lines: Because everyone likes that whole, let's say, uh, pipeline from, hey, uh, developers are starting to code and they're probably using stuff like copilot cursor or like things like that. all the way to deploy. If you had to convince the business, why standardizing certain pieces of that [00:24:00] pipeline were important, like how would you like, make a pitch to your CEO or whatever.
[00:24:06] Ameesh Paleja: this is, this is a fantastic question. I, what I would say is, is that having multiple teams running their own pipelines is basically you're repeating CapEx cost over and over again.
[00:24:17] Dan Lines: Yeah.
[00:24:18] Ameesh Paleja: So like, why do that? If you have everybody building V one, let's say you have 10 teams building V one of this, and, and the minimum investment that you have to put is at least, let's say five engineers against it.
[00:24:30] Ameesh Paleja: All of a sudden you have 50 engineers working on V one of the software, but you have 10 different versions of V one. Why not just have. You know, 10 people working on v five of this, of this thing, right? Where it provides all of these kind of well-managed capabilities that reduce your defect rate, that add all the linters and the static code analysis, the dynamic code analysis, the security analysis of all the things that are causing you problems downstream, and you run the engine cost or keeping the lights on cost, right?
[00:24:58] Ameesh Paleja: Because every team also [00:25:00] has that. They, they have to, like, how do I keep, just keep the, keep the, the, the machine running all the time. So I look at it in two ways. As one, we're just being inefficient because people are doing the same work multiple times within the same company. That doesn't make a lot of sense.
[00:25:13] Ameesh Paleja: And with just a small amount of incremental tax, you can actually create a multi-tenant platform that provides a lot of value, but more importantly, you end up on the other side of that, that you daily operational costs. You know, if I, if I have a hundred engineers or a thousand engineers working on it, I'm saying 20% of that time is just fixing bugs and maintenance.
[00:25:35] Ameesh Paleja: Updating this library and, uh,
[00:25:36] Dan Lines: yeah.
[00:25:37] Ameesh Paleja: You know, changing this, that's not very exciting work. And so getting, getting leadership bought on to it is like, I'm gonna reduce my run the engine costs down. Getting engineers bought into it is, I'm gonna take this boring work off of your plate. Right? Like, I, yeah, because that took do cool stuff.
[00:25:57] Ameesh Paleja: Rather than like, I'm upgrading from [00:26:00] Spring Boot version X to Y. Like, look, I'm an engineer. I, you know, I like. That's not exciting. Uh, like I can't imagine anybody on your listenership. This is like, I'm really excited to upgrade to this version of Python. Like that's not a thing. But
[00:26:13] Dan Lines: I love the answer.
[00:26:14] Dan Lines: 'cause you, you, you said three things. I wanna summarize it. First of all, the business talks money. You came in and said, I'm gonna reduce costs. That was your first point. At the end of the day, the second thing. That I think your business understands, but most enterprises is I'm also going to increase quality while I do that, so I'm gonna save you money.
[00:26:38] Dan Lines: I'm gonna make the quality better. Two things, and then, and this is where I think we, we should take the convo next. You said, I'm also gonna make developers happier. I'm also gonna, now, if I could do those three things for you through standardization, would you wanna do this? I think most of the time a smart CEO or the board, whoever you're trying to convince, is gonna say yes.
[00:26:58] Dan Lines: Ameesh, uh, [00:27:00] please do that for us. And you're gonna say, no problem. Thanks. I got the buy-in. I'm gonna do do it for you. Now, you, uh, again, talked about the, the build pipeline and I think developers, let's talk about the developers and, and experience and standardization. I opened up a bit, uh, by saying, sometimes I've seen developers push back against standardization.
[00:27:22] Dan Lines: Hey, you're gonna make me use a certain tool. You're gonna make me do this or make me do that, but. I've also seen developers get bought in to standardization if certain things happen for them. how do you think, and, and you can stay in the build pipeline if you want to, you could take it anywhere, but like, how do you identify these areas?
[00:27:44] Dan Lines: Hey, we should standardize this, and I also think that developers will like it. Like you need both of those to probably go together. Like how, how do you identify that and like, what's your thoughts on that?
[00:27:56] Ameesh Paleja: I think that, that, that's a, it's, it's a two part answer. [00:28:00] One is what is causing the pain in the, in the, in the enterprise.
[00:28:04] Ameesh Paleja: Like if I look at my, you know, keeping the lights on or run the engine across, and I try to break that down and say, where are we spending most of our time? If you said, oh, it's on, you know, uh, uh, you know, vulnerability, patching as an example, right. Stuff that we have to do, but it's not exactly exciting.
[00:28:22] Ameesh Paleja: And we spend, I don't know, 10% of our time doing that. Like
[00:28:25] Dan Lines: yeah,
[00:28:26] Ameesh Paleja: I would say, Hey, there's a big opportunity here from a cost savings perspective that we wanna do. And then the other side is, you know, that developer happiness and excitement. Um, I want our engineers to feel empowered to work on things that require creative judgment.
[00:28:43] Ameesh Paleja: In this time and age, I mean, like, look, I'm sure you've had everybody talk about ai, uh, over and over again. The reality is, is that the world changes every six weeks, eight weeks. Like there's something new that comes out. You know, yesterday it was Cursor. Today, it's, you know, cloud code. The next day it'll be Codex.
[00:28:59] Ameesh Paleja: I like, [00:29:00] you know, you, it's hard to keep up. But the reality is, is that I want our engineers to be empowered to work on the things that get them excited. Part of the way I could figure that out is just actually talking to them. Right. I'm, I'm one of them. Like, I feel like I, you know, I, I, I'm one of the guys in the, in the trenches with you, right?
[00:29:21] Ameesh Paleja: And I wanted to understand deeply like what people care about, where they wanna spend their time, what's getting them excited and being able to unlock the right tooling and capabilities again in a well-managed way is important because it keeps their kind of intellectual interest. You know, moving forward in the right direction.
[00:29:40] Ameesh Paleja: So look, one of my biggest goals is how do I create an incredibly powerful and happy community of engineers that are focused on creative problem solving and not mundane, uh, mundane work, How can I get, how can I get the BS work off of their plate is really the biggest thing. I, I, I can sell engineers on
[00:29:59] Dan Lines: that [00:30:00] May, I mean, iden.
[00:30:01] Dan Lines: Okay. I agree. Identifying that be, I think all of this actually. Now that I think about it fits together. But let me give a try to, to see, see if it all works together. So identifying BS work. So the opposite of BS work is I'm solving a complex problem that maybe only I could solve. It's never been solved before.
[00:30:24] Dan Lines: The business is asking me to do it. So it's valued. And the bs, uh, side, I think for, at least for me as an engineer, but maybe for most is like kind of those things. I, I'm actually gonna go back to quality and some of, like, I never, for example, I didn't love reviewing code. I didn't love doing security updates.
[00:30:46] Dan Lines: I. Um, depend upon, opened up a PR and it's like a patch and it's totally fine. I didn't like get distracted. There's almost this like ecosystem thing of that surrounds my innovation that kind of wastes my [00:31:00] time. And a lot of that could be automated. And if you're able to standardize and then automate that for me, the stuff that's not my core, core work in the, I would be happier.
[00:31:13] Dan Lines: And, uh, I was wondering if you're able to say, you talked about like the build build pipeline. We talked about the SRE side, but if I was moving more left, was there anything that you were tr trying to go from, like good to elite in terms of the developer experience that, that you all identified, Hey, if we focus in this area of the SDLC, I think we can get that standardization plus the happiness boost?
[00:31:39] Ameesh Paleja: I think, uh. We're getting into a little bit of the, the secret sauce here, but what I would say is, is that the, um, the focus on automating everything except the creative problem solving. Is like the kind of principle thinking around this, right? And so as you think about everything from front end development all the way to [00:32:00] backend development and everything in between performance, testing, I've been testing itself is an enormous task, right?
[00:32:08] Ameesh Paleja: When you think about like, I need to build my unit test, I need to build my integration test. Yeah. This is an area where holy cow, you have the right, uh, standardization. You have the right standard infrastructure. The right standard tooling. You know, even adoption of things like, um, as an example, I'll give you like OTel, right?
[00:32:25] Dan Lines: Mm-hmm.
[00:32:25] Ameesh Paleja: We, we wanted to adopt OTel across the entire enterprise. And you can imagine, you know, the last 10 years, you know, capital One has been building instrumentation all across, you know, in telemetry, all across, um, the, the company all in different ways with different vendors and different this and that.
[00:32:42] Ameesh Paleja: We just, you know, plugged in, uh, you know, some, uh, AI capabilities in Windsurf and we just said, Hey, everybody, you know, just submit PRS to everybody. And lo and behold, what would've taken hundreds of thousands of hours now took a thousand hours to get done, kind of thing, right? Yes. So there's some [00:33:00] really powerful opportunities, and I don't, I feel like smart engineers, I don't have to go and tell them like, Hey, you didn't, you didn't have to do all this like, hard, like, busy work.
[00:33:10] Ameesh Paleja: Right. Aren't you happy that we standardized to, to get this off of your plate so you can work on the cool problems? Right. That's the stuff that like, I think gets people excited and bought in. Um, and I, I would say the one last thing I'll just add on this is I try to find the hardest skeptics in the company.
[00:33:26] Ameesh Paleja: You know, my, my most curmudgeony uh, and you have consumer engineers and if I can get them bought in, I feel like I've solved
[00:33:32] Ameesh video: that,
[00:33:32] Dan Lines: then you know you're on track. Yeah,
[00:33:34] Ameesh Paleja: yeah, yeah. They'll be my salespeople, uh, for me. So.
[00:33:38] Dan Lines: Thanks for getting into the details. 'cause uh, that's the thing that our audience, I think really appreciates and you're doing a, a really great job of that.
[00:33:46] Dan Lines: I am gonna take us a little bit higher level now. Okay. So I'm gonna ask you, a, a question here. How does Capital One, define what an enterprise platform is. I mean, you're [00:34:00] either building an enterprise platform or you're supplying these enterprise, uh, platforms. Like what are the essential components and why are these platforms so critical, uh, to your overall technology transformation and like your business strategy and all of that.
[00:34:17] Ameesh Paleja: I think the, the simple way to put it, I mean, I, I would, I would hazard guess like, kind of the textbook definition
[00:34:22] Ameesh Paleja: is
[00:34:23] Ameesh Paleja: kind of like a set of tools, capabilities, APIs, software, uh, services that are common, that are reusable. I would say Capital One adds multi-tenancy on top of that and you know, well managed, operationally managed, right.
[00:34:40] Ameesh Paleja: There's a lot of kind of attributes of an inter, a great enterprise platform. And you don't have to have all of these, but I would say they're pretty good foundational pieces to say if I build this, many people can use it. It's reusable in lots of different scenarios. It's well managed and well governed.
[00:34:57] Ameesh Paleja: You know, we are also very mindful of our cost [00:35:00] infrastructure and tagging and all, all the kinds of thing like resiliency. Right. Uh, you know, especially, you know, you've, you've said, uh, you know, we're a well-regulated industry. We're dealing with people's money. Like of course, like
[00:35:11] Dan Lines: yeah,
[00:35:11] Ameesh Paleja: I don't wanna have to say like, oh, are you in, are you in three AZs?
[00:35:14] Ameesh Paleja: Oh no, you're only in one AZ in in one region. Like, no, we want everything in multiple regions, multiple AZs. We want this, we want that. So when you can combine all these efforts of the kind of well-managed, reusable components that enable everybody to go faster, that's the thing that, uh, I would characterize as a great enterprise platform.
[00:35:33] Ameesh Paleja: And as I said, it can be. All the way down to kind of just standards, like API standards to STKs to actual full-blown services. It doesn't, like, you shouldn't necessarily pigeonhole yourself into like, it's only, you know, a, a, a service that you're running or something like that.
[00:35:49] Dan Lines: Yeah. I mean, with a company your, your size and maybe the amount of like, I don't know, platforms that you're delivering to your developers.
[00:35:59] Dan Lines: Um, [00:36:00] I know for our listeners or like our customer base, we use a lot of data to decide where in the software dev, delivery process. Are there bottlenecks? And then we kind of back it up with like surveys. Okay, let's go ask the developers to also see, you know, is that legit of what the data's saying? And then maybe they'd say, okay, because we're seeing a bottleneck in the coding
[00:36:25] Dan Lines: process from, you know, the first commit to opening the pr. We feel maybe, and I'm making this up, we feel that we need to bring in some, a more AI tooling. 'cause we might be fall falling behind there with all of the things that you could do, which is probably a lot. How would you even like, determine your roadmap of what to do, uh, next?
[00:36:48] Ameesh Paleja: I mean, look, this is, this is a very tricky question. I don't know if there's a perfect answer, uh, to the case here. Um, I try to kind of balance a couple of different variables. [00:37:00] One is that kind of that developer happiness, right? Yes. What is, what is causing kind of frustration or anxiety or, uh, uh, you know, fear of among people to say like, I can't go faster because I'm nervous about X or Y or z.
[00:37:13] Ameesh Paleja: Right. So does that mean that I have to improve my testing, I have to improve my tooling, you know, in the SDLC pipeline. Like, I want to be able to measure all of this stuff so that I can have an objective and subjective answer, right? So, like you said, like what does the data say? What do our people say?
[00:37:28] Ameesh Paleja: Yeah, I think it's super important, right? Um, that efficiency, I think is an important part of the puzzle, particularly in today's day and age. Again, the second part is what is gonna create the most business value and impact, right? Part of the reason why I took this job is that I feel like there's, you know, creating platforms for the whole enterprise.
[00:37:49] Ameesh Paleja: You know, my team owns our app and website. We own our next generation ledgers, we own our marketing systems. We own all, all these different pieces. And it's not just, you know, while we're talking to [00:38:00] a developer audience, the stuff that we do not just affects the developers, but it also affects our marketers, our business analysts, our data engineers, our data scientists, right?
[00:38:09] Ameesh Paleja: Where we can find these opportunities. I try to kind of think about where the leverage is, and that could, that could be measured in developer happiness. It could be measured in business impact, it could be measured in customer satisfaction scores. And so I, I work with our product leaders and our business leaders to kind of come up with the right set of, of kind of heuristic functions, kind of the F of X of Y says, this is my priority.
[00:38:36] Ameesh Paleja: I don't know that there's a, like a, a, a slam dunk, like, just do this in this order and you're gonna get it because it really is business dependent. But what I would say is oftentimes the mistake or the anti-pattern here is that they only, people only look at one of those dimensions. Okay.
[00:38:49] Dan Lines: And
[00:38:50] Ameesh Paleja: I think that if you want to be a successful engineering leader, you should be looking at all of those dimensions to help the whole business out.
[00:38:56] Ameesh Paleja: Not just, not just narrowly looking at your [00:39:00] people or your specific area like. We're, we're Scotty from Star Trek, right. Our job is to make everybody work and be happy and excited and, and sometimes that's firefighting and problem solving and sometimes that's looking ahead and saying, you know what? We need to be able to go faster than warp five.
[00:39:15] Ameesh Paleja: We need, you know, we need to go fast, you know, better, faster, stronger. Right? Like, we talk about
[00:39:20] Dan Lines: like the song Well, I, yeah. I think you're absolutely right that it's not one input. So it would be ma, it would be a mistake to just look at one input of data and then be like, okay, I'm gonna ma make all my decisions on this.
[00:39:37] Dan Lines: And the other thing that I see, um, customers doing is they're taking these different data inputs. You opened up our conversation of how much data is being created. They're taking these different data inputs. Okay, let me measure. And benchmark, like our SDLC. Let me see how our developers are doing from like a dsap perspective.
[00:39:59] Dan Lines: Let me also [00:40:00] input like what our business wants to do. I am seeing now this is what we're, uh, we're doing at, at LinearB, that we can put all of this information, uh, through like an MCP into ai and I can ask a bunch of questions, uh, now, which I think is becoming fundamental. Now, I understand that maybe some of the.
[00:40:21] Dan Lines: Larger companies or regular, uh, regulated companies. I don't know if that's a allowed yet, but I do wanna see, uh, tell the audience, like, if you're not doing that, uh, I think it's available to you. And the other thing that I wanna throw at you here is I think Capital, uh, One calls itself a technology company that happens to do banking.
[00:40:46] Dan Lines: So if we're, and, and you have all of this, uh, data, if we put all of that, uh, together. how do you ensure, I know this is a big question. How do you ensure that 14,000 technologists, and [00:41:00] maybe there's others, like not even technologists, like how can you access all of this data and daily use and meet all of your governance, uh, criteria like that is kind of mind boggling to me.
[00:41:13] Dan Lines: Like, what are you doing there?
[00:41:16] Ameesh Paleja: You know, it's, uh, it's a very challenging problem to be totally honest. Uh, but what, what I will say is that we have the commitment of investing the right people in the right tooling and capabilities. So like we have a wonderful, uh, you know, risk organization that's constantly kind of, uh, who watches the watchers, you know, they're like, they're looking at us.
[00:41:37] Ameesh Paleja: They have a, a second line risk organization that's watching them and validating what their concerns are. We're all helping each other in concert to make sure that we're staying well managed. I th this is just like one example of this. So what I would say is, is that at this size and scale investment in the people is incredibly important.
[00:41:56] Ameesh Paleja: Making sure that those people are mission-driven and they have the right tools, [00:42:00] capabilities, and funding to actually do the thing that they're supposed to go do, I think is important. Then once you have that in place, then it's like, okay, well now how do we instrument things correctly? How do we, you know, uh, what's that famous Peter Drucker quote?
[00:42:13] Ameesh Paleja: You know, what is, uh, what is measured is managed, I a hundred percent believe that. Right?
[00:42:18] Dan Lines: Me too.
[00:42:19] Ameesh Paleja: And so I, the right instrumentation, I mean, I, LinearB does that, you know, incredibly well across a, a wide variety of tools, right? Whether it's git or Jira or whatever you're looking at that.
[00:42:31] Ameesh Paleja: Work is gritty and it's hard. And it takes some fortitude to have the mindset to say, I'm gonna invest in this now because when I come out the other end, I'm gonna be 10%, 20%, 50% smarter and and faster at my deployments. You have to believe that the outcome is gonna come. And I like, I don't think it's, uh. I think if you look around the industry, the people who have done the investment, that have done the time, they will, they, they've already, they're already [00:43:00] reaping the benefits.
[00:43:00] Ameesh Paleja: And I'm like, yeah, out of Capital One that like we've won little battles and we've been able to say, okay, we took a small bet here. Now let's take a medium sized bet. Now let's take a large size bet. Right? And that results in our ability to create that, that kind of positive flywheel that long-term investments will yield.
[00:43:21] Ameesh Paleja: Long-term value for the company. And that's not just people, it's tools, it's capabilities, it's instrumentation. And it may mean that like in the short term we have to say, I'm not gonna build customer feature X because I'm building developer feature y, but it's gonna help me, you know, put rocket fuel in the tank.
[00:43:40] Dan Lines: Yeah. I, I, I love that. Wow. There's so much to un unpack, but I, I am happy that you kind of, uh, ended that by saying, sometimes you do have to also go back to the business and say, if we invest into our infrastructure or DevEx, or whatever it is, that's [00:44:00] more internal, I can get you that feature. Uh. But it's not only that one feature, it's lots of features that you're gonna ask me for at a later date and an accelerate accelerated rate.
[00:44:14] Dan Lines: Now, because we're in the era of AI and I do think AI is a real thing. I'm seeing it. Our customers are, are seeing it. How do you go about incorporating AI or policies around that when you're in such this like regulated world and you can't make mistakes and you got the the money thing going on, like. How do you, uh, is there anything you could tell our audience of how you approach that or guidelines around it?
[00:44:41] Dan Lines: Is it automation or something different? Like how are you taking that on?
[00:44:45] Ameesh Paleja: Boy, this is, this is a complex question that yes, debate all the time, right? And regardless of whether, you know, uh, you're in a bank or you're, you're, you're working with money or not, like I would, I would say it's important to [00:45:00] be kind of go in eyes wide open, uh, on, on this topic because.
[00:45:04] Ameesh Paleja: It's gonna impact you one way or another, right? Like, so I would say first and foremost, the amount of kind of mutability that's happening on the kind of top of the funnel in terms of cooling and capabilities, right? Like every weekend I'm like, oh, I, I saw this new thing on Codex. I'm gonna go and try it this weekend.
[00:45:21] Ameesh Paleja: By the time I get to it, there's some other announcement that says, oh, actually you should try this other thing. And I'm like, I can't keep up with the amount of change. The power that we have is that we have 14,000 developers that are all intellectually curious, right? They're, they're, they're builders.
[00:45:36] Ameesh Paleja: They're excited about this time. I mean, it's a sea change moment in the industry and candidly, the whole world. So, you know, the, the, the kind of forward progress that I'm trying to, uh, have with the company is can we create environments and sandboxes that are compartmentalized, that have synthetic data, that have like.
[00:45:56] Ameesh Paleja: The information and kind of fake or, or [00:46:00] anonymized information that can be kind of played around with so that we can enable our engineering and product leaders to go and test and play and experiment and explore all these new tools. And once we have that top of the funnel, you're gonna immediately say, yes, this is good for us, or No, this is not good for us.
[00:46:16] Ameesh Paleja: And we kind of separate the wheat from the chaff. And once they have like out of the 50 tools that I was looking at, these are the three that I care about. I want to add rigor there, right? So then, then we say, okay, do they meet our cybersecurity standards? Do they meet our risk standards? You know, is there DLP, you know, if I, if I put, uh, highly sensitive data or PII into the system, is it just gonna get leaked into the models and we're gonna be in trouble?
[00:46:41] Ameesh Paleja: So we have a pretty rigorous process behind the scenes and a great set of people that are kind of not only establishing today's standards, but also continually updating them because, you know, six months ago, MCP wasn't a thing. Today, it's a thing. A2A is, you know, the next thing. And you know, i I, it, it, again, all of this [00:47:00] stuff is changing so fast.
[00:47:00] Ameesh Paleja: So you have to have people dedicated to your craft and possibly updating your policies and, and, uh, standards, but. You don't wanna cut your own legs out from underneath you by trimming the funnel too high and say, well, we have to have a a standards committee doing this, and if it doesn't meet these 50 things right up at the front, then we just can't talk about it.
[00:47:20] Ameesh Paleja: Then nobody wants to explore. So I'm trying to have a balance of how do we enable our builders to explore creatively and, and have fun with it. But then once we get serious about it and we say, okay, these are the tools that we actually care about. Like I care about cursor and, uh, windsurf and claude code, and I want to use these models, and some of them are open source and some are not.
[00:47:42] Ameesh Paleja: Right? That's the place that I want to have more rigor and, and really focus down and, and tap all of our cybersecurity professionals and our risk professionals to come in and, and really. Uh, give it a good, uh, uh, shaking to make sure that our core tenants and our [00:48:00] customer privacy and, and security is really protected.
[00:48:02] Dan Lines: Yeah, I, I love how you explained it. I love that you think about it as a funnel. I think that is the right way to think about it. And what I, I will say, uh, to you, Ameesh and, and everyone listening at one point in the funnel when you, let's say that you pick Windsurf cursor, co-pilot, you say like, okay, these are the ones that, you know, made it down to the bottom five.
[00:48:25] Dan Lines: There's a lot going on now to measure the impact. So you can do things that say like, okay, how does Windsurf affect my cycle time, my PR size, my MTTR, my CFR. I mean, these are the kind of things, uh, that are out there now we're doing that with, with customers. So once you make it down there, you can be a little more data driven.
[00:48:48] Dan Lines: Um, but I think the takeaway for, for the audience is that funnel idea. Let's make sure we're opening it at the top so there's, 'cause they, I mean, there's like a new tool every day here. [00:49:00] Uh, let's make sure that we're getting enough into the funnel, let's make sure that it's secure and then let's see what the impact is.
[00:49:06] Dan Lines: I love thinking of it that way as we come to the end of the conversation. Uh, here, is there any, um, either anecdote or success story or something that, uh, we didn't touch on that I didn't get to ask you about that you, uh, wanted to say?
[00:49:25] Ameesh Paleja: I would say this is that, you know, gi given, given your audience, uh, focus on, on the creative problem solving, oftentimes we get stuck in arguing about,
[00:49:38] Ameesh Paleja: oh, should I use Kafka or Kinesis, or should I use, you know, iceberg or Delta or whatever? Like those conversations are not moving the ball forward. And right now engineers have the ability to get an Ironman suit put around them with all of these AI tools. If you wanna be powerful, if you wanna be creative, you want to be impactful, [00:50:00] focus on the things that matter to your business, that matter to your stakeholders.
[00:50:05] Ameesh Paleja: You can still be incredibly creative without debating whether or not you should rebuild, you know, S3 or something, you know, silly like that. Right? So I would say focus on the, on the creative problem solving because that, that's where you as an engineer can unlock at a tremendous amount of value and impact for your organization.
[00:50:23] Ameesh Paleja: So that would be the best kind of piece of advice or anecdote I would say. And this is such a, such an amazing time to be an engineer. I didn't having to age myself for a second. It is like I used to, you know, when I was at Microsoft, I was futzing around with make files and like, you know, you debug those for hours and hours and now I don't know that anybody would even be able to relate to that example.
[00:50:45] Ameesh Paleja: Uh, I mean, you're chuckling so you've probably done it yourself, but like we're so far beyond dealing with the kind of mundane work that get excited about what you can do, the power that you have in your hands. These tools are incredible. You just don't have to get good at [00:51:00] it. And, and, and if you focus on the right things, you're gonna unlock so much value for your company.
[00:51:05] Ameesh Paleja: And candidly, you're gonna, you're gonna be much happier. So that's, that's what I would, uh, leave you with.
[00:51:10] Dan Lines: Ameesh. Thank you so much for coming on Dev Interrupted, I mean, your experience. And honestly, sometimes I think, okay, some of these enormous. Uh, companies can't have cool stuff going on. There is a lot of cool stuff going on at Capital One.
[00:51:29] Dan Lines: I mean, you are on top of it with developer experience and also, you know, we talked ai. It seems like a really awesome place to work, and I think getting that insight, out into the world, uh, is, is really, really important. Where can our audience go to learn more about the work in Capital One's, uh, innovations?
[00:51:55] Ameesh Paleja: Uh, great, great question. Capital one.com/tech. We have tons of blog [00:52:00] articles, et cetera. And you know, what I would say is coming from, you know, 20 plus years in big tech, uh, this is my first job in finance and working for a bank. We are a technology company, uh, that's wor, you know, working in the banking space.
[00:52:14] Ameesh Paleja: Like we have some great cool innovations coming out. Like we're one of the largest serverless deployments in the world. Um, so there's a lot of cool stuff, a lot of fantastic people, and I appreciate you giving me the time to, uh, expose your audience to it.
[00:52:28] Dan Lines: Awesome. We will, uh, be sure to make sure all of those links are in our show notes to those listening.
[00:52:35] Dan Lines: Uh, join us on LinkedIn to continue the conversation. That's it for this week's Dev Interrupted. See you all next time. And Ameesh thanks again for coming on the show.
[00:52:45] Ameesh Paleja: Thank you for having me, Dan.
