B (3:04)

Yeah, and he doesn't give many interviews and I know this one was a long time in the making, so kudos to you for getting it. It did not disappoint. There are some great nuggets about organizing for innovation that I think our entire audience can learn from.

A (3:17)

Look, Amazon is one of the biggest companies in the world, but I think the lessons from what they're trying to do in terms of becoming a perpetual innovation machine are relevant to any company of any size. So with that, here's my conversation with Amazon CEO Andy Jassy.

C (3:38)

Andy, thank you for joining us.

A (3:40)

I want to jump in.

C (3:41)

You've said that you want Amazon to operate like a startup, like a very large startup. And a lot of CEOs say that. And I'm interested. You know, how do you try to make that happen? You're an enormous company with a lot going on. How do you try to make that work?

D (3:55)

Yeah, well, we talk about. First of all, thanks for having me on. I appreciate it. We talk about wanting to operate like the world's largest startup. And I actually think Amazon already, based on our DNA and the way that we have become a company over the last 30 years, moves very quickly. But when you get larger, there are all sorts of ways that, you know, natural ways that you can get slowed down. And so when we talk about operating like the world's largest startup, we think about a few things. One is, I think in whatever we build, whatever we spend resource on, we have to make sure we're solving a real customer problem. Technology companies in particular fall in love with the technology, but they get to the end and they haven't really solved anything remarkable. And so you have to be. Startups are missionary about trying to solve problems for customers. And that's what we got to make sure we spend our time on. And then we need a lot of builders disproportionately so people that like to invent, people that like to dissect a customer experience and figure out what's wrong with it, even if it's pretty good, and then rebuild it. And then you need owners. If you're going to be a startup, you need people to think about, what would I do if this were my money? What would I do if I Owned all the resources. Hey, I see that I own this piece of the problem. I don't really know if the rest of it's solved. Should I spend my time on it or should I just assume someone's got it? You need people who really feel accountable. It's part of what our effort in trying to flatten our organizations is about is we want the people doing the work to think like owners. And then you really need speed. And I think speed disproportionately matters in every business at every time. You know, in my old job when I was managing the AWS business, I had the privilege of speaking to a lot of CEOs and they would often say to me something like, I don't know if you understand, like we're big. We have security issues, we have compliance issues, we have lots of organizations that have to be involved. We just can't move fast. And I think honestly that speed is a leadership decision. You can decide you want to move fast, but you have to kind of figure out what's slowing you down and knock all those barriers out. And you got to get the whole organization aligned that you are going to move really fast even if you make mistakes. Part of that too, as you're a larger company, as you have more people, is you need to really try to root out bureaucracy, well intended people. As you get bigger, especially as you have a lot of managers, they keep layering in processes and pretty soon you have process upon process upon process that really slows people down so they can't get the real work done, you know. And then I would say the two other things you need if you want to operate with a startup is you got to be scrappy. You can't think about every new project taking 50 to 100 people to do. We started in our cloud computing business, AWS, our storage service. We had 11 people when we or 13 people when we started our compute service, EC2, we had 11 people. You can get going with a small number of people and build something that people actually find resonant and then keep iterating from there. You have to be willing to take risks. And I think that as companies get bigger they often get very risk averse. If you hire achievement oriented type A people, which a lot of companies including ourselves have, they're not used to failing. And so a lot of times when they want to pursue something very different, they worry that they're going to be ostracized if they get it wrong. And, and so they'll play not to lose. And the only way to build something unique and different is to do something different from what people have done. And you have to be willing to take risk and be willing to fail sometimes.

C (7:31)

So there's a lot to unpack there. You know, when you talk about really being customer focused or focusing on an outcome that your customers have, that sounds like it might not necessarily be consistent with taking risks. If you knew exactly what your customers want, you would deliver that. And that's not risky. You know, you're probably trying to skate ahead and figure out what are demands that customers don't even know they have yet, that that's part of the risk taking. So how do you, how do you square those two things?

D (7:58)

Yeah, I think they're actually pretty consistent though. I mean, there's, there's listening to customers, customer actually. If you find the right feedback loops, customers will tell you what's wrong with your product or what's wrong with their experience and they want to change. Oftentimes, customers can tell you the top 10 things in their mind they wish they were different. But if you ask the right why questions on what you're trying to solve, a lot of times customers will tell you what really is bothering them, what's really constraining them, and they can't sometimes tell you exactly how you should fix it. But if you're listening to them and you understand the need, then you can invent on their behalf, which is a lot of what we do, a lot of the invention we do is listening to something customers are really struggling with and they won't tell you how to do it. But we start asking ourselves, why do those constraints have to happen and start to invent on their behalf.

A (8:47)

So you seem to be in the.

C (8:48)

Middle of what is either rethink in terms of management or maybe culture. So the things I'm aware of, you're rethinking the role of middle management. You've adjusted expectations for how teams are meant to work together. You've got people back in the office, I think all of them, five days a week now. What's behind all of these steps?

D (9:06)

Most companies that have been successful for any period of time have a culture that's been a key part of their success. And that is for sure true with Amazon. And I think we have a really strong culture, but it is not our birthright to keep having a strong culture. You have to, you know, things change, your size of companies change the scope of businesses you're going after, change, the geographical distribution of your people change. And you have to keep working on strengthening the Parts of your culture that you see being stretched if you want to keep being successful culturally. And for us, it comes back to this notion of wanting to operate like the world's largest startup. Historically, Amazon has hired really smart, really ambitious, really motivated people who we have given a lot of responsibility to as owners. And then we let them make the lion's share of the two way door decisions. The two way door decision is one where if you walk through it and you're wrong, you can walk back through it and no harm. A one way door decision is when you walk through that door and you're wrong, it's really hard to walk it back. But the two way to our decisions, which is the overwhelming majority of the decisions we all make, we want to be handled by the people doing the work. But as you get larger, as we have, as we've grown so much the last 10 years, you end up logically with a lot of managers and a lot of layers of managers. And so then you find that you end up with things like there's a pre meeting for the pre meeting for the pre meeting for the decision meeting, or you find that owners don't feel like they they own the decision, can make the recommendation anyway because anymore because that decision is going to be made three levels up. And so that's what we like to try and limit. We really want our owners doing the real work to own the two way to our decisions and to be able to move quickly and autonomously. And that's part of this effort we've taken, which is to increase the ratio of individual contributors to managers by at least 15% across the company, which we have beaten already by the end of the fourth first quarter. But we want to flatten our organizations to move faster and to drive more ownership. The other thing we noticed was that like most companies, people were largely working remote. And when we brought people back to the office three days a week in May of 23, we noticed that a lot of things about how we were inventing and how we were collaborating got better. And if you do a lot of inventing like we do, and our style of invention is often very collaborative, we're in meetings together, we're iterating with one another, that when you're together that invention is stronger. What you find is people riff on top of each other's ideas better if they're together. Turns out sometimes it's actually useful to interrupt each other because you get to a faster spot more quickly, you feel that energy. A lot of our best inventions have been after really Messy wandering meetings when we've been trying to invent something where we haven't quite gotten there and we've resolved ourselves to go have another meeting in a few days, figure it out. And then three people stay behind on a whiteboard and actually map out what it was they couldn't figure out. Or on the way back to their office, they figure it out. Or later in the day, they walk by each other's offices. When you're remote, it just like the meeting ends and you're on to the next jingle and the next meeting, and you just don't find that type of invention together. I also think if you want to teach the culture, it's much harder to see it when you're remote. You have a lot of people who are lurking off camera, or if they're on camera, they look like they're looking at the camera, but they're also working on a spreadsheet. And when you're in a meeting together and you're watching the body language and you're watching people's expressions, you internalize the culture much better. I think also the teaching and the apprenticeship is much better. If you can walk over to somebody or after a meeting, sometimes it's a hard meeting. And I might say, Adi, like, don't be surprised that that was a hard meeting. This is a really difficult topic. And next time when you come back, you know, think about these three things. You just don't end up doing those as much when you're remote. And so we realized that we were much better for customers and for the business if we were together.

C (13:14)

A lot of the data has shown that actually flexibility working from home can increase productivity. You know, the workforce, quote, unquote, wants it. Do you think that data's wrong, or are you saying this is a little bit more intangible, but you feel that this is beneficial for, as you say, for innovation, for customers?

D (13:30)

I would say that I think it's very hard to measure truthfully. We've done a lot of measurement ourself. Our data doesn't suggest what you said. But I also, I mean, how do you measure how well you're inventing? You don't actually know how well you're inventing for probably a few years because it takes a while to get through the invention process and you have to hire a team. Then you got to go build the product, Then you got to get the product in the market, and then you got to see if people respond to it. Oftentimes it takes several iterations. So it's quite Difficult to measure. But I will say I spent a good amount of my own time in product invention meetings. And there is no comparison to being in person Remote a couple of the.

C (14:09)

Topics that you've hit on, you know, one, how to be perpetually innovative. And how do I think a lot of people who are listening to this would think, yeah, this problem, I can't get anything done because it's just complex. You know, there's layers of, of, of reporting and management. I'm sure that resonates with a lot of people and you've talked about what you're trying to do. But if you had to boil down, you know, sort of advice for a company, maybe a larger company that has these layers, this matrix layer of complexity and wants to get out of it and to have that sense of urgency, what would be some steps?

D (14:42)

Well, first I would say that I don't believe that we have it nailed or perfect yet. I think you have to keep iterating at it. But I think the first step is to want to address it. And it's actually not simple to address because you get used to operating a certain way and then it seems impossible. Like, how can you change the organizational structure to lose a lot of that bureaucracy? And later. So I think the very first thing is the leadership team deciding they want to actually change it and resolving themselves to take action. And then of course it matters organization by organization. But in our case, we really felt like we wanted to have more ownership with our individual contributors and the people doing the actual work. So that's why we've taken this action of trying to flatten and have fewer managers. I think some of it is actually getting visibility into what's actually happening. So when we announced that we were going to take this goal to flatten and to increase the ratio of individual contributors to managers, we started this no bureaucracy email alias where we encouraged anybody in the company that thought they were experiencing bureaucracy to email me at this alias. And we tried to explain there is a difference between process and bureaucracy. Sometimes people just not like a process and they'll say it's bureaucracy. And most companies of any scale need process to scale the right way. But there is really a difference. And the difference is often processes that have been layered in that don't really add any real creative value. And I, you know, I've gotten over a thousand emails at this point, and not all of them are true bureaucracy. And sometimes it's people saying they don't like this manager like this. So it's not a pure bureaucratic examples, but there are plenty and I've read every single one and so have the relevant leaders in my organ. We have changed already 375processes because of these emails, and it's really hard to see some of the red tape deep in your organizations if you have large organizations. But you can knock down a bunch of things if you see them and you've resolved to change it. And it also starts to motivate you to just look for opportunities when you're in meetings to reinforce with teams that you're not going to tolerate bureaucracy. And so I think it starts with a resolve. Then you got to figure out where you think the biggest problems are initially. Then you have to have good feedback loops to see where all the issues are. And then you got to keep working on it.

A (17:06)

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B (17:49)

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C (18:30)

So I want to talk about AI. I know there were some analysts who thought Amazon was relatively slow to sort of, you know, get into AI in a big way. So I guess the first question Are you happy where you are right now?

D (18:41)

I think AI is probably, it's for sure the biggest technology transformation since the cloud. It's probably the biggest technology transformation since the Internet. And so I think it's going to change every experience that we know. You know, we have a very substantial investment in the AI space right now. You know, I think in the early days of people getting excited about generative AI, people forgot that if you really want to pursue AI in earnest, there are three macro layers of that AI stack, all of which are gigantic, all of which we're investing in, but we invested in a bunch of areas that didn't get as much attention early on. But really at that bottom layer of the AI stack is for model builders and what they care about is two things. They care about the compute to do, the training and the inference, which is really the chip. And they care about services. To make it easier to build models. We've built a chip there, our own custom AI called Trainium, that's going to help people save a lot of money relative to what the cost has been to date. And we've built a service called SageMaker, which is really kind of become the standard way for people building their own models to get the data in, to build a model, to experiment and to deploy into production. And so for model builders, I think we've had services there like some of which have been around for a while in SageMaker that maybe aren't as public but have a huge amount of traction. And then chips that I think people are excited about at that middle layer is for people that don't want to have to build their own models. They want to leverage an existing frontier model, they want to customize it with their own data and then they actually want lots of features that make it easier to build a high quality generative AI application. These are things like guardrails, so the model doesn't say things you don't want it to say or rags that you have up to date information or agentic capabilities so you can take a bunch of automated actions in succession. And we've built this service called Bedrock, which has the largest selection of those leading third party frontier models, including our own. But it also has the best collection of features to help you build a high quality generative AI app. And Bedrock is another one of those services that has substantial traction, like really significant traction if you talk to enterprises or smaller companies that also hasn't gotten as much public limelight. But these are services that are part of why we have a multi billion dollar annual revenue run rate in the AI space. And then the top layer really for applications, we're building some applications. We have something called Q, that's the best AI powered coding assistant, but the overwhelming majority of applications are going to be built by companies. You know, we have over a thousand generative AI applications across Amazon that we've built or are building, but most of them will be built by other companies, hopefully on those first two layers of the stack that I was mentioning. So while there was a lot of attention early on on, you know, ChatGPT, which was kind of the only really large scale generative AI application. I think people have slept a little bit on the other layers of the stack where we have big investments and are doing really nicely.

C (21:59)

And do you see that maybe as your next big line of business? You know, whereas, you know, the cloud allowed people to do things with data, this will allow, you know, millions potentially of users to develop AI solutions through Amazon. I mean, is that sort of the bet?

D (22:15)

Yeah, I think that if you believe like we do, that every customer experience is going to be reinvented by generative AI, by AI more broadly, it means that there's a lot that's going to be built. I mean, I think every SaaS application is going to be rebuilt with AI. If I think about our, even our retail business, we've built something called Rufus, which is a generative AI power shopping assistant, which, you know, really, I think if you know what you want, there isn't an easier way to get it than on Amazon. But if you don't know what you want, well, you can easily find it on Amazon. People have been doing it for a while. It's still the place where physical stores are interesting to people because you can say to a salesperson, I'm a golfer. And they can say, well, what's your handicap? You say, I'm a 15 handicap. And they can say, do you have a fast swing or a slow swing? They can kind of narrow the scope of what you're looking for and then say, I think you should look at these three things. And then you can say, what's the benefit of this graphite shaft versus this steel shaft? And that's the one thing that you can't do as easily right now online. And that's what Rufus aims to do, is it aims to be that personal shopping assistant where it can make recommendations, it can ask questions to narrow what you want, it can compare products, you can ask any question of any detail and it can answer that. And you know, the sales assistant is not going to move on to another career. They're going to be with you and get more personalized over time. We're running our inventory management that way, you know, on generative AI applications to get the right amount of inventory in the right spot. You know, if you think about buying apparel, one of the things you don't know is does this brand run large or run small? And we've built a foundation model to compare all the brands and which ones run comparably small or large to recommend the right size. We can every part of our retail customer Experience will be reinvented with generative AI, and that's true across all our businesses. And so if you want to be helping other companies build the best possible customer experiences, which we do and which is what AWS does, you have to give them the right building blocks in generative AI, which is what we're doing with things like chips and things like SageMaker and Bedrock and some of the applications we're providing.

C (24:34)

Well, you sound like you're optimistic about all this. I mean, is there a part of you that thinks, oh, if we're not careful, there may be unintended consequences that we should try to prepare for?

D (24:45)

I think there are always possible unintended consequences. I mean, I'm an optimist by nature, and I'm an optimist about this technology. And I also think that you can't stop the progress of technology. You just have to figure out how to use it productively for people, for great customer experiences and societal good. One of the things we all have to watch is that the pace of this transition may be quick and may be quicker than other technology transitions in the past. We have to work hard. I think one of the biggest problems, in my opinion, for sure, in the US it's probably true in other countries, too, is that the quality of education in the country has really suffered over the last 20 to 30 years. I mean, if you look at the data, we are 30 out of 35 developed countries now in efficacy of education. And I mean, I think the number of people are going to be able to be software developers is going to go up exponentially because you're going to have these coding apps that allow you to use natural language to describe what you want to go build. And it's going to be very empowering. But we got to make sure that our education keeps up so that people are successful in this new economy.

A (25:58)

So I want to talk a little.

C (25:58)

Bit about sort of leadership at a higher level. AI is reshaping everything, and I think every CEO is feeling that it's an opportunity, it's a risk, it could be disruptive, it could be a lot of things. And then you have kind of political and geopolitical uncertainty that is probably more than most of us have lived through before. How do you manage through that level of uncertainty? Or what's your advice to people who are wrestling with how in the world do you manage through all this?

D (26:26)

Well, again, I don't pretend to have the perfect answer, but I think the first thing is there are a lot of things happening in the world Right now across the world, in our country. And they can be dizzying and I think just acknowledging that there's a lot going on, but you can't control everything. You can only control things that you can control. And then remembering what matters most. And the thing that we keep telling ourselves inside the company as we look at the different things happening is that at the end of the day, we're here to make customers lives easier and better every day. And you can get distracted by, are there going to be tariffs? How high are the tariffs? Are there not going to be tariffs? What do other countries relationships look like with these countries? You can kind of. But at the end of the day we have a job to do, which is to figure out what customers want and then to go deliver it for them. And so in every one of our businesses there are so many areas where we can be even better for customers and that's what we try to spend our time on. I think it's not easy because well intended, passionate, mission focused people read or hear about things and wonder how it's going to affect them. And sometimes when it does, you have to figure out how you're going to operate. But I think by and large, if you stay focused on the issues, you know, customers care about, you will do right by your customers and there are going to be a lot of ebbs and flows to all the things happening around us.

C (28:00)

Yeah, I mean it was a period and HBR was absolutely part of it, you know, a couple years ago where at places like Davos and again in our pages, you know, good leadership was defined as thinking broadly about stakeholders, thinking about things like sustainability and you know, diversity and long term thinking and all these things.

A (28:20)

Has that changed?

C (28:21)

I mean, you know, the, the, the conversation seems to, or the noise seems to have changed around it. But you know, is the definition of successful 21st century leadership sort of evolving at this moment or you know, what, what is the role of a 21st century?

D (28:36)

I don't know. I mean, at the end of the day, I think, I mean to be, in my opinion, to be a great leader of a significant company, there is no one definition and there are different things happening each time that matter. But at the end of the day, I think you have to deliver great customer experiences for whoever you're trying to serve with successful financial results. You know, I think there have been times over the last few years where maybe one issue or a different issue gets disproportionate attention. And I think the reason that those issues get disproportionate attention is that there's work to be done. We're not in the right spot, in my opinion. We're still not in the right spot in terms of where we need the environment to be. I still think we want more diverse teams. None of that has changed. There are certain times where that takes up more of the conversation than at other times, but it is true, in my opinion, at the end of the day, as a leader, you have to have the right customer experience with the right results to match it, and then all the other pieces are parts of it.

C (29:47)

So, last question, as you said, you've been at Amazon for 28 years. You've been in the CEO role for four. What's your best bit of career advice for the HBR audience?

D (30:00)

First, I would pick something that you're either really passionate about or that you think you're going to be good at and you're convicted you could be good at to work on because we all spend so many of our waking hours working. So you want to work on something you like and that makes you feel good about yourself. Pick things that you're really passionate about that you believe you're going to be good at and want to come to work every day doing. You just can't be terrified of failure, you know. And I think, and by the way, I made mistakes in this area many times. You know, I felt like almost every stage of my career as I got to new audiences who I felt didn't know me or know me well, that every time I got in front of them was like a, pass, fail referendum on my competence. And it's just, it's just not, A, it's not helpful and B, it's not how most people think of you who are working with you. And I would say that almost every most important lesson I learned in my career was from failure, were things that didn't go right. And if you are self reflective and learn from them, it catapults you. And then I think the last thing would be, I think an embarrassing amount of how successful you are is attitude. And I always tell my kids this. I don't think they really believe me, but it is absolutely true in my opinion. I think simple things, things you can control. Do you work hard? Are you reliable? Do you get done what you said you would get done? Do you tell people if there's going to be an issue? Do you want to be part of a team? Are you a can do person versus a naysayer all the time? All those things change how people receive you and how much they want to advocate for you and how much they want to work with you. You. And I think another piece of that is how good a learner you are. What I notice is that at a certain point of people's careers, for a lot of people, they just seem threatened by having to learn again. I don't know if it's because it's a lot of work to feel like you have to keep learning or if it feel you get to a certain point of seniority where you think I shouldn't have to learn, or a sign of weakness that you don't know everything. But if you work in a dynamic environment, which hopefully most people do, the second you stop learning really is the second you're starting to unwind. I think back every six months and there's so much that I've learned and it's, you know, that is really what changes your capacity and what people are going to let you do. And I think your own enjoyment.

C (32:38)

Andy was amazing. Thank you very much for your time for your ideas. This is a great conversation.

D (32:42)

Thanks for having me. Adi. Appreciate it.

A (32:45)

That was Amazon CEO Andy Jassy. And that is it for this episode of HBR IdeaCast. Next week, Allison will take the microphone to speak with Whitney Johnson on what to do when you experience an unexpected career disruption, whether that's due to illness, a layoff or restructuring, or macroeconomic forces beyond our control. We have more than a thousand IdeaCast episodes, plus many more HBR podcasts to help you manage your team, your organization and your career. Find them at hbr.org podcasts or search HBR in Apple Podcasts, Spotify or wherever you listen. Thanks to our team, Senior Producer Mary Dew, Associate Producer Hannah Bates, Audio Product Manager Ian Fox and Senior Production Specialist Rob Eckhart. And thanks to you for listening to HBR IdeaCast. We will be back with a new episode on Tuesday. I'm Adi Ignatius. What does the future hold for business? Ask nine experts and you'll get 10 answers. Can someone invent a crystal ball? Until then, over 42,000 businesses have future proofed their business with NetSuite by Oracle, the number one AI cloud ERP, bringing accounting, financial management, inventory and HR into one fluid platform. Speaking of opportunity, download the CFO's guide to AI and machine learning at netsuite.com IdeaCast. The guide is free to you at netsuite.com Ideacast netsuite.com IdeaCast.