Please welcome the Chief Marketing Officer and Vice President of Worldwide Marketing for AWS, Julia White.
Hello and welcome to What's Next with AWS. Thank you so much for joining us here in the room and of course, across the world on the live stream as well. Now it is very clear that we are in the era of AI. And while it's certainly still early, it is and evolving quickly. It's becoming abundantly clear that agents will have a profound effect on how we all work. Now, today, we've got a compelling set of conversations to have on this topic, and of course, several exciting announcements. So without further ado, we're going to go ahead and jump right into it. So to share off the top with his very unique perspective, please join me in welcoming the CEO of AWS, Matt Garman. Welcome, Matt.
Thank you. Thanks for joining us here today. Yeah. Hey, everyone. Good morning.
Awesome. All right. Now back in December, all the way back in December, if you remember that I was looking up and you talked about heading into a world of having a billion agents. So curious. It's been almost six months since then. Like, how do you feel? Do you feel like that's still true? Things changed.
Yeah. I think we are well on the way to there. And in fact, if anything, I think things are moving even faster than we even expected. I think across almost every single industry and every customer I talk to, agents are absolutely exploding and changing the way people do business. So super exciting.
So still on track. A billion or more we are. We'll get there. Exactly. I know one of the things is we've been working with agents more and more, obviously. I think the thing we've seen is that it really fundamentally changes the constraints, right? And so much of business has been about managing constraints. But when agents can run 24 over seven, they can work on behalf, they can work in the background. It changes those constraints. And so I was interested, if you know, how do you think about now, like with that, what becomes possible that wasn't possible before? Just thinking about how to run the business with different kinds of constraints.
Yeah, I think it's a super interesting question to think about what is, was didn't used to be possible. But, but, but now is and, and I think if we look across, even if we just look across kind of AWS what we provide for customers, take something like customer support, where when something goes wrong with a customer environment, the thing that they care the most about is how do we help them fix it as fast as possible. And so previously, and even today, we have large swaths of people and our technical account managers will jump in and help troubleshoot with customers. We've launched things like DevOps Agent, and what it allows us to do is much more rapidly get to the problem that customers are experiencing. We can troubleshoot autonomously. We can actually identify when there's problems ahead of, when customers even recognize it and pinpoint when there's and where the root cause of that problem is, and help them solve problems faster. And so now, as opposed to customers thinking about how do I solve problems when they happen inside of 15 minutes or 30 minutes, it's, it's literally minutes to seconds or even sometimes proactively identifying when there's going to be a problem to self resolve those issues. And now our teams can actually free up their time, as opposed to helping customers troubleshoot problems, to thinking proactively about how can they better architect their systems, how can they lean into new technologies, how can they build new capabilities because they're not spending so much time on, on kind of troubleshooting issues and things like that?
Yeah. You know, in my area, right. I was looking at the average Amazon advertising area and usually like an ad buy would be 100, $200,000, take six months to get the creative. And now with their new agent, I was looking at, actually now comes down to like the point where small businesses have like a 300% growth in small business adoption because now it's so much more capable. Again, those constraints of what used to be hard and expensive are no longer the case anymore.
Yeah, yeah. And we're actually seeing that not just inside of Amazon. We're seeing that across our customers. And so take somebody like WellSpan Health. It's one of the largest hospital systems here in the United States, and they are really pushing the envelope of what's possible with AI and agents. They have agents doing all of the administration that you might expect happens inside of a hospital, things like documentation or monitoring or helping schedule patients or, or doing kind of that routine patient communication. And this is freeing up tons more time so that their staff can actually focus on the thing that hospitals are supposed to do, like take care of patients, have bedside manner, make sure that care is happening in the way that it should, and actually thinking of more ways that they can take care of customers, which is super interesting. And I think it's a, it's a great opportunity. You can also take somebody like in the insurance industry, right, where insurance companies are thinking about the entire end to end workflows of how they can process claims in a much faster way. And so Allianz as an example, one of the largest insurance companies in the entire world is using agents to, to automate that entire process. They think about claims processing, things that used to take, as some of us know, insurance claims often will take 8100 days to go through that process. They've actually reduced that process by 80% by using AI and agents, all built on on AWS, to make sure that auto verification, they can say, well, you're eligible for, they can get rid of fraud, and they've actually been able to lower costs and speed things up for customers.
I love the, the theme on like, what's possible when the growth, right. Which is great. But I also, you know, we both read the headlines and there's certainly a lot of focus on AI agents and how they're replace jobs and what it means for people in their jobs. And I know that can sound in moments hyperbolic, right? But there's a lot of energy on this topic. So I want to just you to hit it head on. Like, what's your perspective? What do you see?
Yeah, I will say I get that question. And, you know, at least for us, we have software development as an example, people say like, okay, it's great that that AI and AI agents are improving what we can do inside of the software development world. But our software developer jobs going away can tell you we are hiring just as many software developers as we ever had inside of Amazon. And in fact, I see the demand for that really accelerating. I think as we think about where AI really takes off and where agents can help free us from the monotony of the repeatable parts of our task, it's really about leaning into those new things that we can do and thinking about what's possible. And I see many more opportunities for job growth in new areas and for new capabilities, frankly, than than we have before. And I think, you know, look, the jobs will be a little bit different, right? And as an individual, people have to be thinking about, you know, how do you really own the key outcomes? Right? And it may be that it's true that potentially being an expert at like being able to author a Java code snippet is going to be less valuable in the future than it was maybe a couple of years ago. But understanding how to author applications, understanding how to solve customer problems, thinking about technology, and how all the pieces fit together is more valuable than it's ever been. If you're a salesperson, what we're thinking about is how do we use AI and agents to automate a bunch of the pieces where it's like, how do you make sure you, you know, load your opportunities into Salesforce effectively, as opposed to freeing up our salespeople's time to have more time to spend with customers, more time helping customers, more time explaining how customers can get value out of the cloud. And I, and I think so the nature of every job is going to change, but it's not. The jobs are going away. It's just that the high value things we're going to be able to do more of.
Yeah. When I was looking at the U.S. Bureau of Labor Statistics, right, about tech jobs, as you said, and it looks like they're over adding over 300,000 tech jobs and growing at two times the rate of other fields. So to your point, like, and then also I did, I did do a fact check across Amazon. We're on track to hire over 11,000 SDE interns in early career. So I know you get that question.
Yeah, yeah, it's pretty awesome. So exactly. Amazon is hiring 11000 new S3 interns and full time employees this year like that, that that is not jobs going away, right? That's an important area that we're going to continue to invest in.
So now you get the chance at your at your seat to look across all things happening at Amazon and curious, what are you seeing across the company? Because we're obviously an operating company and a tech company and how we're using agents and what it's how it's helping and changing Amazon.
Yeah, well, look, the first one is in software development and I will say like AI and agent core development has completely transformed what is possible in the software development world. It really is just incredible both in, in creating software, in operating software and kind of doing the entire software and thinking about security. That entire software development lifecycle has been completely changed. And, and we see teams who are, you know, previously you would have, you'd have a product out there and you'd get feature requests, you'd get bugs filed and the teams would go, you know, if they were really on top of it, maybe within a couple of weeks they would get a bug filed out. I was talking to the team the other day. They had a bug report, came in via one of their social channels. They looked at it, fixed it, and got it out inside of 20 minutes. Like just like the the latency at which the things are changing is just incredible. And so, you know, I think that that is unbelievable how fast you're able to invent and how fast you're able to go build things. In fact, we're seeing, and it's interesting we say about, you know, is AI taking away jobs? I actually see the exact inverse. In fact, when I talk to companies here in, in the Bay Area, I talk to the teams at Amazon. They actually find that they're able to attract STS. And when the developers are coming to interview for jobs, they want to know, am I going to have access to the absolute latest development tools? Am I going to be able to use Kiro and Claude Code? And in some places they're saying like, what is my token budget as a developer? And am I going to be able to move at the speed that I need? In fact, at Amazon, we try to make sure that those token budgets are largely unlimited so that our developers are unblocked by technology. But I think that that that desire to be able to build fast is, is really pretty awesome.
Yeah. When I think across, you know, whether it's Prime or even one of the things I saw was we overnight took the entire intranet, you know, almost a million, over a million employees. Right? And we just turned it into an authentic first experience. Yep. And it took off. And people are like, so happy and so delighted. And it's like a simple thing, but it changes the employee experience and, you know, the types of scale.
That's right. Very quickly on that front.
All right. Now, in terms of what we've been building and obviously we've been building with working with the genetic technology for over a year now. And you get to also see what like lots of customers are doing. So yeah, I feel like we kind of have a front row seat. So I want to share with others like what learnings, maybe what mistakes, what, what's just evolved. That's just different now as kind of as the years gone on.
Yeah. Look, that's, it's a good it's a good question. And, and I've been at now AWS for, for almost 20 years. And, and I think there's some super interesting parallels to the world of AI and agents today from actually when we started in AWS and, and so if you think back to, to when the cloud first came around and when AWS first launched, one of the interesting patterns that we would see from customers is they would take the exact same thing they were doing in their on prem data center and try to do the exact same thing in the cloud. And, you know, we'd get questions like, hey, are your EC2 instances? Do they have five nines of availability? We're like, no, you don't need to worry about that. If your instance fails, you just launch another one. You scale horizontally, you think about serverless, you think there's a whole bunch of different things and people kind of had to, to, to change their mentality about how they and, and people would think about, all right, I got to really think about the infrastructure I need for this project. And we would tell them, look, just launch it and run it and see if it works. And if not, you shut it down. And in that mentality had to change about how you think about things. And, and in some ways, you see that today with how people are thinking about AI and agents they're taking, they're like, okay, I have this business process. I'm going to have agents do the exact same thing that the humans do. Like I'm just going to go redo the workflow and, but have an agent do it instead. And it's fine. It kind of works in the same way that moving an on prem thing into the cloud worked, but it doesn't give you that transformational change. And so what I really see is that when teams are thinking differently, when when businesses are thinking about how do these workflows completely change? How does the, how does the, the whole application that I've built change if agents are doing it, does the the data change, are the access patterns change? Does the UI and the interface change all of those things? And so I think that is one of the key things that, that the learnings is that when those customers are really completely changing what is possible, and then they start to really iterate quickly, and then they start to learn and they start to invent new processes. And I think that's where that real opportunity for new businesses, for, for customers, where they're reinventing every application, every workflow out there, it's really having to re:invent that.
Right? And I see that as well. Like it's common to see, and maybe it's a good first step to just infuse agents into what you're doing. But ultimately, that's not where you get that 510 X.
That's right. And we've seen, we've seen it inside of Amazon where we see some development teams that are are, you know, inching along and making changes. But, but we see some that are totally transformational. Take somebody like the Prime Video team as an example. They had a financial system that allowed them to, to pay their various partners when assets and creative was used. And they had to rewrite that to, to, to modernize it. And it was a program that was going to take two years. And if they just kind of redid it and they, they rethought what, what was possible. And they said, how do I remake this system so that it's better for customers? It's better for us. It actually is better for our partners that get paid faster and using agents. How do I not think about just sitting there and rewriting the code, but having agents go rewrite the code and instead of this taking two years, it took closer to two quarters. And they did it with just a handful of people, and they made something that was meaningfully impactful to their business and changed how that whole ecosystem worked. And so you can both do things faster, but you can also kind of change those business processes for the better.
All right. I want to stay on that point. So there's a lot of headlines. There's analyst reports right around what agents mean for SaaS, B2B SaaS applications particularly. And actually we've seen market valuations change based on some of those proclamations. So you obviously have a very unique perspective knowing that so many of the SaaS applications run on AWS. And we also deliver our own solutions too. And so what do you think? Like, where are the headlines, right? Where are they not? Right?
Yeah. Well, first of all, SaaS apocalypse is a fun word. So I get that people like that word, but I think it probably is a little bit overblown, honestly. And what I mean is, I do think that almost every single one of those SaaS applications is going to be rewritten for the AI and agent core world. That's absolutely true. But the incumbent providers today have such a huge advantage. They really do. They have deep domain expertise. If you talk to the folks at Workday, they didn't just like toss out an HR application and then hope it got traction, right? They deeply understand what are those workflows? What are the things that talent agents or talent groups inside of companies are trying to accomplish? And, and they've built a bunch of that knowledge over time. If you think about what goes into really understanding inventory management in a, in a manufacturing setting and how all the supply chains hooked together and what the various codes mean and, and how you think about demand plan. And what a lot of that is, is, is deeply ingrained knowledge inside of these companies. So they have an incumbent advantage and they, they have a large customer set with all of their data. Now, if all of those companies stick their head in the sand and don't go innovate, I 100% agree they're going to be like, they're going to be passed by and someone else is going to build something new. But the good news is, is. And so if that happens, yes, that is their valuations should go down, but they have a really big competitive advantage to actually expand where they are. And I think if you look at some of the leading companies, take somebody like a Salesforce, where I think you saw a couple of weeks ago, they announced a headless version of their offering. It's pretty awesome. They, they realized that in an agentic world, it's not the UI that's differentiating. It's the workflows, it's the data behind it. And they've built a product that's purpose made for the agentic world, where they can actually do more in that and actually make themselves more valuable to customers in that world. And that's a great example of how the incumbents don't have to be legacy. Like they can actually lean forward and be the innovators in that space. And I think that's and it's a huge opportunity.
Agreed. And good to see them moving fast and adapting in that way. All right, now let's get into some of the announcements we're going to talk about today. The first one is something that, honestly, I've literally never seen this much like excitement and energy from the early adopters. And that's our new Amazon Quick desktop experience that will be available in preview today. So very excited about that. No, Matt. I know you've been using it to you've been one of our early adopters, so you have first hand experience. But like what, what makes Amazon Quick this new experience such a game changer in your view?
Yeah, it's, you know, like when I talk to a lot of, I get to speak to a lot of CEOs and leaders of companies. And what they often tell me is, is they love how AI is, is really transforming what they do in the software development side. And they want to get AI in the hands of every single one of their employees, and they want to figure out how their employees can, can unblock themselves to go build small agents to help them with, with everything that they're doing in their daily lives. And Quick is exactly this. And frankly, I've been using, like you said, the desktop application for the last couple of weeks. And I will tell you, it is a complete game changer. It is by far the most effective tool. I've used a lot of AI productivity tools and tested them. This one is by far the biggest game changer for me personally, and it's kind of a if you think about like what we've done with Quick is combine all of your sources of data inside of the enterprise. But then we also saw, and this is a couple of months ago, you saw when OpenClaw came out, the power of having access to a local desktop and being able to operate with your local files and your local email and your local Slack. And, and I think what we've but, but people are worried about security and appropriately so. And I think what we're doing here is combining a bunch of those things together with Quick to give you the best of all of those worlds and, and a really enterprise battle tested, secure solution that I think is going to be game changing for many of our customers. And they'll really want to like spoil some of the news that's coming up. So I'll leave some of that for them. But, but it's something that I am really excited about and I get a ton of value out of.
Yes, absolutely authentic enthusiasm across every role that's worked on it. So on that note, we're going to shift to talk more about Amazon Quick and show it. So thank you, Matt, for your insights and we'll see you again in a little bit.
Awesome. Thanks. Thanks, everyone.
All right. Now our next guest has been helping us find ways to re:invent day to day productivity through agents. So to come tell us more, please welcome Jigar Thakkar, the Vice President of Amazon Quick.
Thank you Julia, it's great to be here. The way we work is not working. Every day you lose hours to work that actually does not need you there. Searching the summarizing the context. Switching Amazon Quick is built to give you all that time back. Today we are launching new technology that will change how work gets done. Your local files, calendar, email, other apps all coming together with Quick and the ability to create intelligent documents that connect with live data, update automatically and serve as interactive dashboards for any business function, whether it's a sales leader's pipeline review, pulling real time Salesforce data, or finance team's monthly close page aggregating ERP, SSL, and other internal systems. Set it up in minutes, and by end of the day, you'll wonder how you ever worked without it. Say you want to set up a meeting with your colleague on a new product launch. Normally, there's a few messages back and forth on Slack to check their schedule, then over to Outlook to send them the invite. Quick handles all of that with a single prompt, Quick knew the project, figured out the time zone, cross checked the calendars, sent the invite, and pinged him on Slack. No tab switching, no back and forth. So how did Quick know all of that? This is the knowledge graph in action. Quick connects to your systems. You already use your email, Slack, your CRM calendar, local documents and files. It pulls knowledge from all of them and builds a living map of your work. Quick connects the dots between people, projects, decisions, and actions. Quick knows you wherever your work happens. Quick knows what's relevant. It brings the most important items from across my channels to my attention. It has highlighted that one of my priority items today is preparing for a customer meeting I have this afternoon. Quick helps me with the prep as well. Quick performs deep research on the company and the industry. It pulls customer examples from our internal systems, graphs, our current roadmap, product roadmap from a file on my machine and layers in the briefing from the account team, the emails and the Slack threads. Using this knowledge, it creates a presentation I can use in my customer meeting. Hours of work done in minutes with Quick. We often need different assets for different tasks and Quick can help with all of it. Say we need this as a document. Or an email that summarizes the brief to the account team. Or a spreadsheet. Quick and build it. Everything you've seen so far is about my day, but I don't work alone. Teams I work with have a critical processes spread across siloed systems, and usually those 1 or 2 people who really know how the process works Quick can help you here too, with a new capability that enables teams to create dedicated collaboration spaces. For example, my finance team was tracking contract reviews across email threads or shared drive and approval system. Nothing connected. They can now use Quick to build a single workspace where the contract, the supporting documents from OneDrive and the approval status all live side by side. What used to require hopping between many systems now happens in one persistent view that stays current, and they're able to share a read only view with their stakeholders. To self-serve, they can submit new contracts and check on status of submissions. No more chasing people down for updates. This took minutes to build and Quick. Let's take a step back. You seen Quick schedule a meeting from a single prompt, prepared a customer briefing across six different systems, and generate artifacts in minutes. That's personal productivity. You have seen Quick bring together siloed systems into a single workspace that keeps an entire team on the same page. That's team productivity. And when everyone across an organization is working this way, that's enterprise productivity. So that's Quick. My team and I are very excited to see what will you do with it.
Thank you, thank you. Jigar. Thank you. Thanks for the demo. Appreciate it. I hope we got a sense of how it works. Now, obviously, we're working in the productivity space for a while with AI. I've been really helpful in a more reactive way, but we're turning the corner to something different. So tell me about what's driving that shift.
So, Julia, there's been an inflection point over the last few years. There have been these siloed bots where they're operating on fragmented old ways of doing things and old apps, and that doesn't work. So what we did was build Quick from the ground up. It knows you. It knows the full context of the people you work with. So you don't have to go to every application. All that context come to you.
And now you talked about that in the very like personalized experience that knows you like how, what is the context? Tell me a little bit more about how that works.
So every time you use Quick, it learns from you. It is collecting the documents, you deal with the project deadlines you have, the people you must interact with, and the escalations from a customer that just showed up. What's happening urgently in an email and Slack. It has all this information and that provides the context it needs to give you very relevant answers.
Got it. All right. What I have to, you know, for all the CIOs or other folks listening, what about the controls, access controls, identity management, privacy, all of that, right? If has it has ability to connect with all those, how do they trust that to work?
Well, yeah. So we have 20 years of heritage of AWS with the standards of quality, performance and. Compliance, security and privacy of all the users, all of that entire stack that Amazon AWS is built on is what Quicksight stands for.
Got it. So it's bringing all of that kind of the robustness of the AWS platform and security kind of the robustness of the AWS platform and security kind of the robustness of the AWS platform and security controls into how Quick is implemented, which is very important. Now, curious what obviously, I know inside the company is very excited about internal, but what are you hearing from our customers who are using Amazon Quick?
We have so many customers who are giving us feedback, and it's been really amazing. From BMW or 3M or Mondelez and Allianz and so many others. And over the last few months, what we're hearing is how they are cutting down production time for so many of these processes by almost 80%. In some examples, we are hearing how they cut down the time it takes to process customer issues more than 50%. So there are so many of these anecdotes and examples we hear. And one of my favorite one is when one of our customers started our desktop app, they said, you know, I've been waiting for something like this and this just feels magical, right?
That's always the best word, right? When technology is great, you know, it has that magical feel. Well, hey, thank you, Jigar, for showing us what Quick looks like and giving a sense of kind of how it works in the backdrop as well. I think, again, the best thing to do is try it. I have to say, trying to describe it is hard, but using it is has that magical feel. So thank you so much for joining us and showing us about Quick.
All right. Now, as we have worked with agents, we become more convinced that it has the capability to transform, obviously, individual productivity, but actually entire business functions. So our next guest is a leader who has been at the very forefront of inventing and operating across several businesses at Amazon for over 20 years. So to share how we're applying agents to new business areas, please welcome Colleen Aubrey.
Good morning. Thanks for joining.
All right. We've got a we're warming up here. All right. Now I just want to start with, you know, you've been worked across for 20 years, the retail business for a long time. And you're one of the founders of Amazon advertising business. And now joining AWS, leading our applied AI solutions area. So I first want to start with what are you and your team do? What is this area about?
Yeah. So I've had the great privilege of working with many of our consumer businesses. And really in that process, learned a lot about how we run businesses at scale at Amazon and how do we go through those different phases of development, from an early idea to finding fit, to actually operating at this, you know, at the scale of, of hundreds of millions of customers and billions of dollars. And so that experience really led me to AWS two years ago, joined the team after working on the ads business for a long time. And for me, there was this opportunity to take what we've learned in our business. And in many cases, we sort of outgrow off the shelf applications, and we end up building our own applications to run our business, usually around scale or complexity, pace of innovation. And so it's really for me, like we've learned a lot doing that. And surely there's an opportunity for us to take that learning, take those capabilities and put them in the hands of AWS customers. And we have this incredible sort of collision of opportunities with AI and this new sort of tool in the toolbox to think about like, what? How would we work now that we have this new capabilities? And so that led to applied AI solutions now.
And I know not just you, but many of your leaders actually came from the operating side of Amazon as well, kind of bringing in that domain expertise of across how Amazon works, right?
Yeah. And so it was important for me, like, you know, I'm sure many of you have seen this as well. It's often the mix of capabilities you have in the organization that brings fresh ideas. And so one of the important factors with me for me was like building a leadership team that have been in the business of being hands on, running at scale, delivering for customers every day, managing the complexity of doing that and the, the emerging sort of adaptability that you need to, to make that happen. And as part of that, you know, and my experience and many of these leaders experience at Amazon, we've had to build our own applications to run. And so for me, this mix of people in the organization is about it's not about SaaS for SaaS at stake. It's about, you know, inventing applications that work in the business and bringing that experience to life, which I think is an important, important thing.
We'll dig in more deeply. But your team is also responsible for Amazon Connect, right, which is our solution for customer experience and contact center. And so those of you not familiar with Amazon Connect, it's a leading enterprise customer experience application, and it's reached over $1 billion in revenue last year. But I think for maybe most important for today's conversation is you are actively taking that what is maybe had been a traditional SaaS application and you're making it an agent first and agentic experience. And so, you know, as Matt and I talked about, this is what all SaaS needs to do. So how are you doing it? What does it look like from the inside?
Yeah. So lucky for me when I joined AWS, actually, you know, Andy and Pasquale had already done started down this path of taking what we had built for our own stores, customer service team and bringing that to life in Amazon Connect. So last year we did 20 million interactions a day. We did a 12 billion of AI minutes and conversations last year alone. And so that products in its ninth year, in March of last year, we introduced what we think of as the next generation of Connect. And the reason why we think of it as next generation is we have introduced AI across the entire customer journey, voice or digital channels into the human experience, like assisting agents as they're working with customers into transcription, sentiment analysis, into the analytics and into outbound communication. And so the for me, the key here is that if you, if you like, put AI in a box and if you like, constrain it in that way, you're really not likely to realize the potential. And it's really when you can carry context across a journey. And we start thinking about now about the horizontal journey of a customer through, as they work with the organization that the power becomes, in my opinion, more real and more transformative. And so here we sort of launched Connect with unlimited AI. And, you know, I think it's sort of it's a journey, but I'm really pleased about the way we're really sort of putting agentic and AI context across the whole experience into really the teams that are coming back and rethinking it.
And I love that you take the whole journey, right? Not just parts of it and rethink of what's possible now with agents in that experience. Now we're taking that agent first approach and marrying it with Amazon's operating and domain experience to build more agentic solutions. So I'd love for you to talk about what we're announcing today.
Yeah, it's sort of a big day for, for my team and for me, like we've been toiling away for a couple of years ago, really challenging ourselves to rethink. And so today we have a few new products to share with you. And where we're going is actually, we are going to expand the Amazon Connect name to be a family of products. And so it's super exciting that the birth of a new family. And so we are unveiling three new agent core solutions Amazon Connect Decisions, Amazon Connect Talent and Amazon Connect Health. And the product that we've come to know and love is Amazon. Amazon Connect will be Amazon Connect Customer. And so this is our, you know, I guess for me, Amazon Connect starts to stand for agentic business solutions and bringing all that domain expertise together with the agent first.
Now let's just start for a second before we jump into each one of those. But what makes these energetic solution versus just kind of AI powered?
Yeah. You know, I think Matt talked a little bit about this when we thought about developing these products. The question is like, now that you we can see the future of what agentic capabilities can do, how do you think about how companies will work? And at the heart of it, we got to this idea of we need to build agentic teammates, and no one needs a difficult teammate. That's not great. Plenty of those. Yeah. So we don't need to do that. So where we need to go is really I need a teammate, which is easy to work with, intuitive. It's trustworthy and agentic team that is always learning. And I need to be able to take this agentic capability and get the transformation in my business, the reinvention of how we work. But without the change management, no one needs to go on a 2 or 3 year change management sort of process. And so we really are challenging ourselves to put agentic capabilities to work in a way that delivers that organization's new ways of working, but also in a very intuitive and easy way that I don't have to really learn something different. And we have developed a new device design philosophy that came with that. What we realized is we dug into this is that great AI with a underwhelming user experience is probably not going to be transformative that we really needed to address both. And so we came up with this, this sort of philosophy, which we call morphism. And I think in the past, in design, in design, you really went with skeuomorphic skeuomorphism, like with Apple, with the leaders here, where you actually looked at the physics of objects and translating that to the digital environment from a desk to a desktop, files to folders, those sorts of things. What we're focused on with Hugh morphism is what is the dynamics of human interaction? If we're building products that are at the heart of which is an agentic teammate, then how should those teammates interact with you? And so it's a journey. You know, we're getting started, but this has really been a key part of how we thought about these products.
So here kind of a mental model of this is what makes it agentic first, it's like a teammate, right? That's a different way to think about it. And then you literally have come up with another design approach for doing these as well.
Yeah, I would say it's work in progress. We're making good progress and you'll see some of it today. But this is like a journey and we've got a lot to unpack. And like every week, you know, Hector and his team are like exploring new interactions. And we're sort of pushing ourselves to think of like, is that really, is that how it happens? Is that awkward? Is that weird? Do I trust that? How do I think about how natural that is? And so it's, it's something that we're working through.
Well, interesting and excited to watch it happen. But let's get into a specific example. And we're going to start with an area that Amazon is quite well known for, which is rapid decision making, but also particularly in the area of supply chain and logistics, obviously from our retail store and your experience and the retail side, you've seen quite a bit of that evolution from the inside. So I want to start with what is it around Amazon's expertise that we're bringing into this domain?
Yeah. So let me start with you. Something we talked about. We've talked about a lot at Amazon for a long time. But speed matters in business and specifically high quality but timely and fast decision making is key to, you know, continually to innovate re:invent and to deliver for customers. And so this is sort of at the heart of, you know, heart of the product here and where we know there's one area that we do this daily, and it's complicated and it's something we spend a lot of time on is around managing demand and supply planning. And so we have decided to start there. We've built a product which we have two teammates here. One is a demand side planner and one is a supply side planner. They sit side by side. And this is not about data processing. It's not about delivering you another pretty dashboard. It's really about getting that high quality decisions at the speed of today's business, moving planners from reactive to strategic decision making, getting to the point where they're actually managing the business versus reacting to the escalations and the external conditions.
Yeah. All right. I'm going to invite Olivia to come out here in a second to show us what Amazon Connect Decisions looks like. But before that, what is it like? What about Amazon's domain expertise in this area specifically that's brought into this experience?
Yeah. So decisions as speed is fundamental to our stores business. And you know, we've been working on this for 30 years, building the capabilities to, you know, source, receive, manage and deliver sort of 400 million SKUs around the world. And we started down that path with like two day delivery, then one day delivery and same day delivery. And now, you know, we're working on 15 minutes. And so this sort of constant building of the expertise and this sort of weaving through, as Andy talks about in his shareholder letter, like not
The straight line of learning through this really helped inform this product. There are a few things that stood out to me. In 2013, we came to holiday season and we couldn't meet delivery promises to customers. This was catastrophic for us. The root cause was last mile capability and the capacity we had there. This led us to building our last mile network, and today you see that into rural areas as well. In 2016, we hit another constraint: middle mile distribution. We couldn't get products into our distribution centers fast enough in order to get them out the other side into the last mile network to get them to a customer's doorstep. So we built that capability. All along the way, we have been building our own foundational models to actually drive this decision making, to extend from sourcing to a customer's doorstep. This foundational model is actually at the heart of Connect Decisions.
