Matt Garman runs AWS, and he says replacing junior workers with AI is one of the dumbest ideas he's ever heard. So, why did his own company cut 30,000 jobs over the past year? That's this week on Platformer.
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Welcome to Platformer. I'm Casey Newton, and today we have the final episode of this first little mini series we've been doing on AI and jobs. But, good news, after a couple weeks away, we're going to be back with a new mini series. So, stay tuned for more on that later. This week on the show, AWS CEO Matt Garman joins us. Matt, I think, has one of the best seats in the world to watch what is happening with AI and work. AWS runs the infrastructure behind much of the AI economy, sells the agents that are starting to do white-collar work, and sits inside a company whose CEO has said he thinks AI will shrink its corporate workforce over time. But, Matt is one of the most outspoken optimist on AI and jobs, and we are going to test that optimism.
First, though, as always, we begin on checking in on recent news about AI and jobs. And that means it's time to bring in Platformer fellow and Gen Z AI correspondent Ella Maru. Ella, how are you this week?
Uh, well, as of like an hour ago, I'm furious.
Because I was researching for the segment I'm about to present to you, and I saw this ad on Corsical, an app that is a personal enemy of mine.
Which said, 'Make TikToks for Coursicle. We're paying $500 a month to make videos about Coursicle, an app that actually helps students. Tap here to apply.'
And first of all, what is Coursicle?
Okay, so Coursicle is a course management software that you use, in particular at Columbia, which used it when I was there. You can use it to plan the courses you're going to sign up for and then sign up for those courses. The thing about it is there are hundreds, thousands of courses you might want to take and the interface for searching them makes absolutely no sense and has been overall negative helpful for finding the course I was looking for. I literally would search three keywords for the title of a course I knew existed and knew no other courses contained those keywords and that course would not show up.
So, I mean that sounds infuriating, but what was it about seeing this ad for making TikToks about them that sort of pushed you over the edge?
Well, also it's like, this is near and dear to my heart because I graduated college a year and a half ago. So in some sense I feel I never left. I still have dreams about finishing my problem sets last minute. And I think to say to college students who are stressed about finding an internship, here's a great opportunity for you. Shill for this platform that is making your life worse on TikTok for
$6,000 a year. That's money for a college student. But is it worth what it does to your soul?
It sounds like the answer is no. Well, shame on Coursicle and shame on TikTok. We'll be interested to see what happens to that company. In the meantime, what have you learned this week about AI and jobs?
Yeah, so there's been some recent reporting, partially from the New York Times, about how colleges are increasingly offering not just CS majors, but majors that are specifically AI majors. In 2021, there were only five schools that offered a major that was called an AI major. Now, a report from Northeastern University's Center for Inclusive Computing says that there are 74 AI-specific degrees in the US. That's a five-year period. In academia, this is lightning speed. You have no idea how fast they're
creating these degree programs.
Yeah, do we assume that it's because there is now just suddenly a lot of demand in the marketplace for pieces of paper that say AI on them that come from top universities?
Yeah, and it's also not just top universities. The percentage of top universities and also the percentage of small private universities and state schools that are starting to offer these degrees is pretty similar. There's demand from students on all sides of higher education for an AI degree. Because AI is very hot right now. And people are like, what will keep me employed? The only thing booming right now, apparently AI.
So what do I get if I earn an AI degree and how is it different than whatever these degrees might have been called before AI became so hot?
Yeah, so I've spent a bunch of time staring at the syllabi of these degrees from Ivy League colleges, from smaller schools, and basically every one of them is a slightly modified CS degree, which honestly, that's correct. If it were not a slightly modified CS degree, I would be mad. Because it wouldn't give you the fundamentals you need to prepare, but it's basically if you're a CS major, you have a certain programming load. This squeezes the programming load slightly while still keeping the conceptual fundamentals, and then adds some math, like linear algebra, stats, optimization that is very useful if you're doing any sort of AI application.
So the idea is basically you can spend less time learning some of the basic writing code by hand skills that we know you don't need anymore, but we will teach you more CS adjacent topics that could be useful to you if you ever need to train a large language model?
Yeah, or train a small neural network. The vast majority of people employed as machine learning engineers are not training frontier large language models.
Well, so tell us as somebody who took your share of computer science classes in school, how are you feeling about CS these days in general?
Yeah. So unfortunately, if you're looking to AI-proof yourself, there's not a totally airtight case to be made for CS. Some of the best econ literature so far, especially this study from Stanford called Canaries in a Coal Mine, indicates there's some sort of economic displacement effect from AI. It shows that young person hiring in CS is worse compared to a lot of other fields. For that particular study, they compared the decline in CS and the decline in something like communications, which is also pretty AI exposed, and CS was doing the worst. But I will say the evidence keeps shifting back and forth. Every two months I find a new econ paper that changes my mind. One reason for hope, perhaps cope for me and my brethren, is this paper from some people at the London School of Economics that I liked a lot. It came out last month. It does something kind of complicated, but basically it tries to isolate the effect of underemployment in AI exposed professions and just people who are working from home in general. It does this by isolating the times at which both of these things became relevant. Basically what they find is the correlation between exposure in work from home and AI exposed stuff is 0.77, where the highest correlation you can have is one. That's for any social science research, that's really high. And then also when they try to isolate those variables, work from home is a bigger explainer.
I see. Well, land that point for me a little hard. What does it mean that these two things are so correlated? I get what you're saying. It's sort of harder to understand what AI exposure is, but elaborate a bit.
Yeah, so there are obvious theoretical arguments why CS majors can get replaced because AI can write code. But at the same time, on a macro perspective, the current data doesn't sufficiently distinguish between several effects of work from home. One, companies hiring a lot of people during the pandemic, tech companies when they had comparative booms. Two, it's just harder to train young people remotely. So it becomes more expensive to hire them in general in a non-CS specific way. That hypothesis is pretty strong and explains a lot of what you're seeing even when you're a CS major and you're like, 'Nobody wants me to write code anymore.'
Right. Right. Okay, so that is interesting and is maybe a reason why if you're entering college this fall you may want to consider getting one of these AI degrees after all.
Yeah, it's at least an update against no hope for AI degrees. Another piece of cope I would like to share, or potentially hope, is on a more conceptual level, as AI gets better at a lot of tasks including programming, including machine learning engineering even, which is a very specific AI skill that is hard to train people to do. AI is getting better at that. At the same time, we don't trust AIs. We've never trusted AIs. They often do weird stuff that's hard for us to predict. A lot of the time, there is still demand for expertise of people auditing AIs, people criticizing impacts of AI, people studying the effect AI is having on society, which I try to think of as my niche. In these fields, there clearly are not enough people who understand CS and AI. I cover AI policy a lot. The number of AI policy white papers I've read where I'm like, 'God, I really do wish someone on your team knew stuff about this,' is very high. I also know people with tech degrees who have moved specifically into policy where they find there's really high demand for their skills. So I think that general category, there's something real here that feels robust.
Yeah. All right. Well, fascinating as always. And as it so happens, my conversation today with the CEO of AWS does include some conversation about the young CS graduates of the world and what lies in store for them. So, thank you to Ella. After the break, my conversation with Matt Garman.
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My guest today is Matt Garman, CEO of Amazon Web Services. Matt's about as close to a lifer as you can get in the cloud business. He joined Amazon as an MBA intern in 2005 before AWS even launched and later became one of the first product managers for EC2, which is the service that started the cloud computing era. He became CEO of Amazon Web Services in June 2024, and today AWS is a roughly $130 billion a year business. And it has big plans. Amazon plans to spend about $200 billion on capital expenditures this year. Most of it, you probably already guessed, on AI infrastructure. So, why did we want to talk to Matt this week? Well, the interview really sits at the intersection of every thread we've pulled on this show so far. It is the primary training partner for Anthropic with up to $25 billion in fresh investment announced in April. It signed compute deals with OpenAI that are now worth up to $100 billion, and OpenAI's models are now on Bedrock, which is the service that Amazon has for serving AI models. Amazon also has begun selling the agents themselves. It has a developer agent called Hero, a security agent, a DevOps agent, and an agentic teammates suite that it calls Quick. All products that are explicitly marketed as doing work that people do today. But, when it comes to the question of will AI take all the jobs, Matt is a very loud optimist. When executives told him that they were replacing junior employees with AI, he called it, quote, 'One of the dumbest things I've ever heard.' He pointed out that junior staff are often some of your cheapest employees, are already AI native, and are a future pipeline of talent. And when he was asked about his predictions about an AI jobs apocalypse last month, he told the Wall Street Journal, quote, 'Everybody's entitled to their opinion, but I don't think that's true.' At the same time, Matt says all of this from inside a company that cut roughly 30,000 corporate jobs since last October, and whose CEO, Andy Jassy, wrote that AI will, quote, 'reduce our total corporate workforce.' And whose internal robotics documents, reported by the New York Times, describe someday automating 75% of the company's operations. So, this is a conversation with somebody who is both the seller of automation and a defender of the workers that it might displace. Last week, Molly Kinder told us that the messy middle is coming, and almost no one is planning for it. This week, we're asking one of the people actually building that middle what he sees coming in the near and the medium term for the rest of us. So, with that, here's my conversation with Matt Garman.
Matt Garman, welcome to Platformer.
Thank you. Appreciate you having me here.
So, you joined Amazon as an MBA intern in 2005 before AWS even launched, when maybe some saw it as a strange side project for a bookstore. 20 years later, it's a $130 billion business. So, it strikes me that you've already lived through a cycle of people initially underestimating something that turned out to be really big. But also maybe people at various times during that transition overestimated how quickly it would happen. So, I wonder as you're looking at the AI landscape, does any of that history rhyme for you, or does this just feel like a totally different moment?
Yeah. No, it's actually a really good analogy and it's exactly that. If you roll back 20 years ago when we were first starting AWS, we had to explain to people what the cloud was and why Amazon was a part of that. It was a completely different shift into how work was going to get done. We had to explain that it used to take six months to get a server and now you could get one in five minutes, and if something fails, you can just shut it down and launch another one. That's not how the world worked. So we'd explain this new way of thinking about building applications where you did it differently. You didn't think about having one big server and a couple of servers that you took really good care of and then slowly scaled, but rather you had this disposable infrastructure that was serverless. You didn't worry about the underlying pieces and focused on software and scaling. I view a lot of what's happening right now similarly. I think there are some differences, too, but in a similar way, I do think AI is going to completely change how people build applications. It's not just doing the exact same things a little faster or cheaper. It's fundamentally changing business processes, workflows, business outcomes, customer outcomes, and what was possible. And it's moving so much faster than that last change. It took people through the first five, ten years, and we grew what we thought was really rapidly, but we looked up five, ten years into AWS and still today the vast majority of workloads still run on prem. Even 20 years later, there's a massive amount of workloads that still run in on-premise environments. I don't think AI is going to take that long to transform businesses. I think that's probably the biggest difference: the speed at which this transition is happening. It's a totally different technology, but it has wide-ranging impacts across many industries. Even slow-moving industries are thinking this is not something they have 20 years to get ready for. This is something they have 20 months to get ready for, maybe that long, maybe not, but it's going to happen much faster.
Why do you think it's happening faster? I imagine some of it is just businesses feeling like there's a lot of competitive pressure to go fast. But is there something else in there that I should think about?
I do actually think these two technology shifts that we've been intimately involved with are quite complementary and compounding of each other. Without the cloud, AI doesn't take off in the same way. If everybody's still running in their own data centers and you had to install the new update to the next model, scale your own GPU capacity, deal with network bottlenecks, that just was never going to happen. But now because of the cloud, enough workloads and data are in a cloud world, and these models are available in a cloud world, that cycle is much faster. So I think those things compound upon each other and have led to it happening at a much faster rate than a previous shift.
Mhm. Well, I was so excited to talk to you because of this unique vantage point you have as the person running AWS. Basically every company experimenting with AI is running through you. You have millions of customers. Every major model is on Bedrock. You can see what the enterprises are actually doing. Sometimes we hear enterprises have run a bunch of early experiments and aren't seeing a huge return on that investment. Other companies seem like they're starting to figure it out. Give us a sense of what you're seeing in that range.
