BIG INTV: AWS CEO Matt Garman Doesn’t Think AI Should Replace Junior Devs

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0:46From Wired, this is The Big Interview. I'm Katie Drummond. Amazon Web Services, better known as AWS, is back in the spotlight. I'm not talking about the most recent outage that nearly shut down 30 % of the internet. Instead, it's because of the recent announcement from CEO Matt Garmin that's focused on the very AI-centric future of one of the world's largest cloud platforms. Garmin, a one-time AWS intern, is now guiding the company through perhaps its most transformative moment since its founding, introducing new AI systems, new partnerships, and new questions about who and what will dominate the next decade of cloud and artificial intelligence.

1:25In this conversation, we talk about the strategy, the pressure, and the big decisions Garmin has to make shaping the infrastructure that powers, well, almost everything.

1:39All right, I'm ready. Okay, let's do it. Matt Garmin, welcome to The Big Interview. Thank you. Thanks for having me. So we always start these conversations with some very quick questions, like a warm-up. Are you ready? Sure. Go ahead. Okay. He's ready. It's too late now. Okay. Okay. If AWS had a mascot, what would it be? We have a big S3 bucket sometimes that goes around, so we'll call it that. Wait, sorry. What is an S3 bucket? Well, an S3 bucket is like a thing that you store your S3 objects in, but we actually have a large foam, a big bucket that walks around and actually looks like a paint bucket.

2:18So you do have a mascot? Well, S3 has a bucket. It has a mascot. It's probably the closest we have, and I like it. Perfect. What's the most expensive mistake you've ever made? Personally or professionally? Either. That's a good question. I think probably personally, my most expensive mistakes I ever made was playing basketball too long and I tore my Achilles. So that cost me about nine months of being able to walk. So, you know, that was, I probably should have known that into my 30s I was well past basketball playing age, but I lost a little bit of time there. That sounds personally expensive.

2:54Psychologically, that sounds very expensive. Exactly. If you could rename the cloud today, what would you call it? What is it called today? The cloud. Oh, okay. I actually think the cloud is a pretty good name. So I don't know if I would rename it. I would rename, like, we called AWS Amazon Web Services, and now no one knows what web services are. So that I might rename a little bit. But I actually like the name of the cloud, so I'm not sure I would rename it. Maybe Amazon Cloud Services. Yeah, maybe. Maybe. What's the part of your job you would love to outsource to an AI agent? I try to outsource a lot of the parts of my jobs to AI agents if I can.

3:33But I haven't yet figured out how to outsource more of my kind of answering of day-to-day emails yet. And that still, I find, takes up a lot of my time that I haven't yet figured out how to do more efficiently where I get the right information and get the right information out. But if I could figure that out, I think that would be great. But have you – it sounds like you've tried. And I'm curious about this, and I know we're supposed to be doing quick questions, but I was going to ask you a little bit about this later. Yeah. Tell me a bit about sort of how you've tried to incorporate artificial intelligence into your workflow, into sort of your personal professional life.

4:08Yeah, I think there's a number of ways that I've done it. I think in particular for me, though, a lot of the benefits that I get in my job in particular are taking a lot of information inputs and then kind of sharing those out to either the same or other people and kind of connecting a lot of those dots. And for my particular role, I haven't yet found a huge shortcut into kind of being able to do that, particularly with regards to like the medium in which we communicate like email or other places like that, because I find that all of the shortcuts lose some of that nuance. Like there's some summaries and things that work.

4:45There's definitely some tools that allow me to summarize content more quickly or learn new content more quickly, which is I find that to be super useful. But haven't found a huge time win for my role in particular where there's not as much kind of repetitive work or other things like that. And it largely is kind of knowledge that I'm trying to get from a bunch of sources and then consolidate together to send out to others. That's actually very interesting to me and reassuring in a way because I sometimes feel like I should have found a bunch of shortcuts by now, given how artificial intelligence is talked about.

5:22And I haven't either. So maybe both of us one day soon will. From one former AWS intern, that's you, to a future one, what is your best piece of advice? I find that people always overestimate how much of technology has already been invented and kind of think that there's nothing left to do. And what I find is that we continue to be at the early stages of evolution. As long as you're curious and looking and willing to try new technologies, new areas, that we're always at kind of that early stage of what can be invented. And sometimes I run into interns who are like, yeah, you know, when you started AWS, it was small, but now it's a big company, and so there's not the same opportunity.

6:04And I'd say that that's just not true. I think there's just as much, if not more, opportunity than there ever has been. Well, which leads me to my next question, which is, how do people know when you're unimpressed? When I'm unimpressed? Yeah. I largely would tell them. Fair. So direct feedback. Directly. I don't know when to like that. I mean, I think, you know, I think largely, though, it's not about impressing me. I'm more like, you know, I like when people are thoughtful, when they've come up with like the right sets of decisions. It's not that they're like, like particularly like every day, it's not like people are like coming up with something that's super, super novel.

6:43And again, it's not about impressing me, but it is, I like it when people have done the work so that we have all the information, whether it's customer input or data input or sales input or whatever, so that as a group, we can make thoughtful decisions. And so that I like and impressed when people are I've done that work ahead of time so that when we do get together, we can make good decisions and thoughtful decisions as opposed to like being. And I often tell people it's not necessarily the the recommendation that I'm going to be like impressed by. But I want us to have all the information so that as a team, we can move forward and make great decisions.

7:19Last question, because you have a very big job. So what is a hobby you wish you had more time for? I'm assuming it's not basketball based on what we just learned about you. It's not. I've switched to golf. So I caught the bug a couple years ago and quite love playing golf. I don't get to play as much. Well, let me sort of set the stage a little bit. We're here to talk in particular about a bunch of announcements that you recently made around AWS and AI and agentic AI that Wired covered. I'm biased, but I thought we did a great job with that coverage, you know, just very recently. But I also want to learn a little more about you in a professional context.

7:58So tell me and tell all of us about your career journey thus far as now the CEO of AWS. But you've had obviously a very long career at Amazon before that and even sort of prior to that. How did you end up where you are now? Yeah, after – so I'll start at the beginning. I worked for a couple of startups early on in my career. and none of them did particularly well, but I learned a ton from them, which was great. After my second startup, my wife and I both quit our jobs and went to business school, which was a fantastic opportunity. And as part of business school, kind of when I was there, one of the things during my internship that I wanted to try to explore was what entrepreneurship looked like inside of a company, just because my goal was always to go back and do a startup again.

8:47And so as part of that, I looked at a bunch of different companies and I ran across Amazon and actually talked to Andy Jassy. And they were talking about building this technology services capability inside of Amazon. And I thought that's exactly what I wanted to see. I wanted to see what it would like for a successful technology company to build, you know, to try to build something new inside of it. because I just want to see what that motion looked like and how you could learn from experienced entrepreneurs and what was different than at a startup. And so I did my internship for what turned into AWS in 2005 before we launched.

9:27I was fascinated by it. I thought it was an awesome opportunity. And I said, great, I want to come back and work here for a couple of years. And then I would go back and do a startup. And so then I started full-time in 2006, effectively as the product manager for all of AWS. Like there was, you know, it was largely kind of defining all of the services as we launched them. And so I started a couple weeks after S3 launched and before the rest of our services launched and helped launch them and name them and price them and do a bunch of things. And then I kind of kept getting more and more responsibility.

9:59I kind of focused on EC2, which was our compute service, started taking on engineering teams, actually launched our block storage service, kind of wrote the PRFAQ for that. and hired the first engineering team and launched that. And then kind of grew to lead most of our kind of core compute and networking and storage product areas. So all of the product and engineering teams for that. And it was fun. I got to learn a lot along the way. Like I'm not necessarily kind of, or I wasn't originally kind of a deep technology person, but got to learn about hypervisors and kernel engineering and a bunch of these really low-level core technology pieces, which were cool.

10:42And it was super interesting for me to learn. And it's just such a fascinating space. And as AWS grew really rapidly, we grew along with it, and we grew the team pretty significantly. We were fortunate enough to work with some of the best technology people in the world as we built the service, and a bunch of services, and as the business grew. And then, I can't remember the exact time, It was after about 12 or 13 years. So it would have been like 2019, something like that. Andy Jassy asked me, yeah, he called me in his office one day and asked if I would lead sales and marketing. And I literally had nothing, I didn't know anything about sales and marketing.

11:24In fact, I was like, kind of like looking around, like if he was talking to someone else. But it was a great opportunity to kind of learn that space. And it was a unique opportunity, right? I was basically handed one of the world's two or three biggest enterprise sales and marketing organizations, having never done any of those jobs before. So I think Amazon's a bit unique in that we kind of trust people where you're smart, you know how to operate, you know the business, you don't necessarily have to know the exact thing that you're going into. And the team was gracious and helped me learn that.

11:58And that was a great opportunity to get to learn how to how to run a field organization at scale and really get to spend a ton more time with customers, which was awesome. Really understand the nuances of what a startup customer really was looking for versus enterprise versus the governments and then kind of the various different industries they worked for. And then took over as CEO kind of was spent two years ago, a year and a half ago. So I've spent almost 20 years here at Amazon, all on AWS. And how big is the organization by employee size that you now run? I don't know the exact numbers, but it's in the hundreds of thousands.

12:42Hundreds of thousands. And a lot of that is, we have large data centers where we run very large operational organizations. We have data centers all around the world and pieces like that. And I mean, I run a team at Wired. It's sort of in the low 100s. And I love management. And that sort of for me was always, it was clear fairly early in my career that that is sort of where I wanted to go. Was that always clear for you? Sort of the idea that, yes, taking on sort of larger and larger pieces of this enterprise is what I feel like I am sort of meant to do, what I want to be doing? Yes. I mean, I like it.

13:19And I think that I'm reasonably good at it, I guess. So I guess I took on more. We'll ask some of your employees, some of your hundreds of thousands. I guess that's not for me to say. But I liked it. And the more I did it, the more, you know, it was a ton of learning. What I really love is when I get to take on roles where I get to learn more and get to stretch myself. And frankly, I love building and love having an impact on what the business is doing and what our customers are doing. and, you know, scaling beyond yourself, it's hard because you can't do all of the, you know, you don't get some of the joy of like actually physically kind of getting to build the thing or deliver the thing yourself.

13:57Or like write this. You didn't write the story in my case. Yeah, that's right. But you can write a lot more stories, right? In that case. And you kind of learn to do that through others, which is also an interesting and useful skill. And then you learn how to communicate to teams you know, first through direct management, then through layers of management, then through, you know, through, you know, mediums like talking and things like, you know, all company meetings or other kind of mechanisms like that where you have tens of thousands of customers or employees that you might be talking to. And so you got to think about how do you build mechanisms?

14:34And this is one of the things that I enjoy learning, which is how do you think about building mechanisms that allow you to help those individual contributors make some of the right kinds of decisions and the strategy that you're trying to drive for the team or the business or the company. And, you know, I've quite enjoyed kind of learning how to leverage some of those mechanisms at different scale. And that's been fun to do too. Because you just talked about sort of going from managing people to managing managers. Yeah. I swear I'm asking for a friend. But do you have any sort of particular mechanisms that you have picked up in those 20 years that stand out to you as particularly effective strategies?

15:16Because I will say there is something very specifically different about managing someone who then manages people who then manage teams of people. It's like it has the potential to be a very unproductive game of telephone. And I'm curious about the mechanisms that you employ to make it much more effective than that. Yeah. I mean, look, everybody has their own way of doing this. I think for, I mean, so you a little bit have to find what works. And I do think that as your team and your organization gets larger, you have to change some of those things. And I think that's one of the common pitfalls that I see people fall into is that they will assume that the thing that worked great when they were a line manager, managing a team of six to 10 people, will work the same as when they're managing a team of 100 people.

16:02And those same things won't work. And then, you know, I think there's another shift that's like when you don't know the name of everyone in your team or your organization, which I can't unfortunately know today. And usually that breaks somewhere around, you know, 100 to 200 or somewhere in there. you just you'll you'll run into people who are in your team that you don't know or don't know their names and and you just have to think about all of those things differently and where they are it's really hard i think to have you want to give the broadest set of people in your team as possible mental models on how you would make decisions in their place as opposed to what the decision actually is because if you have to like send down edicts all day one it's not as empowering to your team and two like there's chances that whatever you say gets miscommunicated but if you can have and this is actually a lot of the power of culture in a company but also what we think like these mental models which is like if i was going to approach this situation this is how i would think about it um or these are the the ways in which i would make trade-offs or think about kind of decisions then you can empower tens of thousands of people to go make decisions and then you can focus on how do we make sure that we hire smart people and um don't punish them when they make bad decisions but course correct and that's how i've kind of learned at scale where your real leverage points are ensuring that you have those right mechanisms at place, having a mechanism that does allow you to kind of find where things are going well or where they're not.

17:25And when they're not, where you can dive deep into that and really get into the details and understand really at the very core level, like then you kind of switch modes and you're like, now I'm line manager again. I'm understand the very details of exactly what you're doing, get things kind of sorted and then kind of jump back out again and stay at a high level and look at mechanisms to how you can do that. And that's the best way I've found to do it. Well, I appreciate the free management advice. I'm sure many of our listeners do too, so thank you. But I want to now ask you about AWS in a broad context.

17:53I think a lot of people listening, I would describe Wired's audience as sort of curious generalists. Obviously, they're listening to this because they're interested in sort of technology and where it's taking the world. I'm sure all of you listening have some sense of what AWS is. You have some sense of how important it is to what you do every single day. but they probably don't know sort of in brass tacks just how big AWS is and sort of how vital it is in terms of just infrastructure. So I'm hoping, can you explain it to us? Maybe not like we're five, but like we're 21. We just graduated with a humanities degree and we're really trying to understand this thing that you are in charge of.

18:34At a high level, our idea behind AWS hasn't changed in the last 20 years, which is there was a bunch of pieces of technology that was hard and non-differentiating that companies had to do for a long period of time. And that was used to be, they had to build a data center, they had to go find servers, they had to take care of the servers when a disk drive broke, they had to go fix it, they had to set up their networks, etc. There's a whole bunch of work that they had to do before they could ever, you know, write Netflix. That's like a, you know, they could actually like write a cool application that would stream a movie to your end customer or, you know, write Airbnb that would think about logic of how you could connect individuals with people who had rooms that they wanted them to stay in.

19:17Whatever your application was, right? And so our goal was, what if we could do that work for companies so that they didn't have to do that? And so that was the thesis when we started, which is what if it was as simple as somebody could come and make an API call and simply say, great, give me servers, give me storage, give me databases, give me whatever. And we'd provision them for them. And then, you know, through an internet connection, they can have access to that. And so it turns out that was a very powerful idea. And I think we did a good job executing on some of the abstractions that made it really powerful where a lot of companies went and built their applications on there.

19:54And so the companies I mentioned, Netflix and Airbnbs and Pinterest, are all some of these early customers that we had that built their business from the beginning kind of on AWS and the cloud and don't own data centers. You know, they largely just run inside of AWS. Initially, when we first launched the business, we thought this was going to be incredibly compelling for startups and some technology companies, which it was. But as we grew, we found out that enterprises and really large organizations were equally compelled by this value proposition eventually. And we had to build a lot more capabilities for them, whether it was like encryption capabilities or audit logs or abilities to hit particular compliance things or whatever it is.

20:33But now we have customers like Pfizer and JP Morgan and the United States government and the intelligence agencies. That was a big win for us when we kind of convinced the U.S. government that we could build a top secret region and that they could run intelligence workloads inside of AWS. And were you in those meetings? I would have loved to have been a fly on the wall in those meetings. Yeah, yeah. And we walked through some architectural questions that they had. Well, yeah, like, what does it take to convince the United States government that they should run on the back of AWS? I mean. You know, I mean, like, there was a whole RFP process, and there's a lot of work that we did.

21:13But it was also just some whiteboarding where we kind of walked through, like, how would it work, and how would you, you know. And at the end of the day, you know, it's not, the cloud sounds like it's a magical technology, but it is, you know, it's data centers and it's networks and it's servers and other things that we run at very high reliability, at very high security. and we found some forward-leaning technology folks that wanted to figure out how they could get the benefits to the government. Because it turns out, if you find the right person in an organization, even in somewhere that's as large and bureaucratic as the U.S.

21:46government often is, you'll find people who want to lean forward. They want to go faster. They want to deliver value for citizens. And finding that right person and then being able to collaborate with them, their eyes light up just like they do for a startup company. And so today now it's across almost every country and every industry that you think about. NASDAQ trading markets run on AWS. It's financial services companies run on AWS. Hospitals run on AWS. Media entertainment is, whether it's live broadcasting or streaming broadcasting or any of those things, we power a lot of that technology across the board, really.

22:22And so we're excited that we have millions of customers all around the world. And, you know, we've grown the business now to be about$132 billion run rate business. Wow. But it's still growing 20 % year over year on that large of a base.

22:43Now more than ever, technology is a dominating force in our lives. Then there's the threat of AI everywhere. And yet, tech can be inspiring and help level playing fields. I mean, a YouTuber with a self-funded debut movie just dominated the box office. I thought, hey, if you interview me, it'd be good for your publication. And that's not ego. I just have a lot of followers. But it's that stigma. It's like YouTubers, they're not real. Join me, Lizzie O 'Leary, the host of What Next TBD, Slate's podcast focused on technology, power, and the future. Follow What Next TBD now, wherever you get your podcasts.

23:36Just when you thought you were done learning on the job, enter artificial intelligence, right? Which obviously has been around as a technology for a very long time. But we are in this sort of new era and this new sort of challenge for you and your organization, which brings me to this recent keynote at the reInvent conference that you held recently. You also streamed it on Fortnite for the first time, I might add. But you announced some pretty significant changes to AWS, to your mission, to your priorities, and to what you would be offering to your consumers. And I'm hoping you can sort of talk us through that transformation.

24:15If you would describe it as a transformation, maybe you wouldn't. I think technology is always iterating and going through these kind of transformations. So I think for us, staying at the forefront of every technology innovation is incredibly important. And I think there's been almost no technology leap since maybe the cloud and the internet before that. And so we've been investing in AI and AWS and Amazon for the last decade plus, two decades maybe. But definitely with the leap forward from generative AI over the last three years, we've just seen a massive change in what's possible for customers.

24:52And so we've had this vision that it's not just going to be AI is over on one side and then the rest of your business is going to be over on the other side. But basically, AI is going to be built into what everyone does. And in order for that to happen, number one is you have to have all of your data in the cloud world. And then we've built this whole platform of tools that then allow you, once you have that data in the cloud, to deliver differentiated value to your customers. And so some of the things that we launched, and in particular, I'm quite excited about at reInvent, are really around AI agents and the difference between kind of the first generation of AI tools that were really around summarization and content creation, right?

25:30And that we're all quite excited and got a lot of value out of those. But there's only so far that goes. I think the next stage is these agents. And agents, the real value is they can take access to your data, they can still do some of those summarization and content creation, but they can go actually accomplish tasks and they're able to reason. And when you have these agents that can go reason and accomplish tasks on your behalf, All of a sudden, you can kind of force multiply what you're able to do. And we launched a couple of things. One was called Nova Forge, where we allow customers to actually take their data and integrate it in at the early stages of training one of these frontier models, which is called Nova.