And with that, the keynote session is over. We'll be back shortly with a roundup of everything we learned in the opening session. Thanks for following and remembered to keep tabs on our socials and newsletter for all content from AWS re:Invent across the week.
We've still got a bunch of launches expected here. Garman says he's going to rally through the next few announcements - 25 in 10 minutes.
"Buckle up everybody," he says. We're going to cut to the chase here and distill things into simple bullet points covering key areas, starting with Amazon S3.
• S3 object size limits are getting a big boost, a 10x boost to 50TB
• That's not all though, Amazon S3 Batch Operations are also now 10x faster
• Elsewhere, Amazon S3 Tables are also getting new intelligent tiering to help with cost optimization
• General availability of S3 Vectors
Elsewhere, we have some big database announcements.
• Increased storage capacities for RDS for SQL Server and RDS for Oracle are coming
• Optimized CPUs for RDS for SQL Server
• A big new database savings plan for customers - savings of up to 35%, according to Garman
With faster programming and improved security processes, there's only one part of the equation missing. Deployment of software. With this in mind, the new AWS DevOps Agent helps investigate incidents and proactively work to improve application deployments.
Want to learn more about the new frontier agents from AWS? Check out our coverage and interview on the announcement below.
• AWS says ‘frontier agents’ are here – and they’re going to transform software development
"This agent will help you build applications that are secure from the very beginning," Garman says. "It embeds security expertise upstream and enables you to secure your systems more often."
Security Agent also helps with penetration testing, giving developers teams what was traditionally a laborious process one that's now on-demand. Huge improvements to broader software security here, but also speeding up the development lifecycle.
"We think this will help you move much more quickly," Garman says. The agent is going to help shipping more code, more quickly.
But there's more to software development than just writing code, there are key security considerations at play here. The new AWS Security Agent will help underpin safe, secure software development.
With agentic AI gains over the last year, there's huge potential for developers, Garman says, especially with "frontier agents".
These aren't your bog standard AI agents, they're more intuitive, autonomous, and powerful - for developers, the Kiro autonomous agent could be a game changer.
This AI agent essentially acts like "another member of your team", according to Garman, learning from the processes and practices from the team to continually improve.
Kiro has been a huge success internally at Amazon so far. Last week, the company made the decision to make it the official development tool for teams across the company.
Elsewhere, solutions like Kiro, AWS' AI coding tool, is helping drive developer productivity.
Kiro is one of a growing array of AI coding tools out there on the market in 2025, but Garman says the reception has been huge, with "hundreds of thousands of developers" using the platform globally since launch.
Moving onto developers now, Garman says agents have great potential here to help reduce workloads and speed up operations.
This is where platforms such as AWS Transform come in, helping modernize legacy and mainframe code. Thomson Reuters, for example, is modernizing more than 1.5 million lines of code a month during the process of moving from Windows to Linux.
AWS has been quietly working away building its own range of agents in recent months, Garman says. Amazon Quick, for example, assists users in visualizing and analyzing data or automating workflows.
Employees across the company are using Amazon Quick and recording marked benefits so far.
"Today we already have hundreds of thousands of users inside the company," he says. "Teams are telling us they're completing tasks in one-tenth of the time it used to take."
Amazon is also using agents in customer service roles, with Amazon Connect already being used by a range of major customers such as Toyota, Capital One, or National Australia Bank.
"The Connect business passed the one billion annualized run rate mark," Garman says.
So now that you've secured your agents, how do you track performance? You've invested a lot of money in these shiny new tools, but are they actually delivering a return on investment or even helping customers?
Another new service unveiled today, AgentCore Evaluations, helps enterprises keep track of agent activities and performance based on real-world interactions with customers.
"Evaluations helps developers continuously inspect the quality of their agent based on real world behavior," Garman explains. "Evaluations can help you analyze agent behavior for specific criteria like correctness, helpfulness, harmfulness."
Security is a recurring talking point with agentic AI, Garman says. Identity security-related considerations and guardrails are causing headaches for security teams as agents weave their way through data sources behind the scenes.
"You can't with certainty control what your agent does and does not go," he says. Giving enterprises tools to set clear boundaries for agents is critical.
With that in mind, the company announces Policy in AgentCore, which allows users to set strict rules for agents to help them "stay in bounds".
Garman is running us through an example here involving an agent operating in a customer service capacity. Users can set a limit on the size of refunds issued by an agent. Hoping to chance your luck and get a refund on something over $1,000? That won't work.
AgentCore is a source of immense excitement at AWS, it seems.
"The momentum is really accelerating," Garman says, with enterprise customers flocking to the platform at a rapid pace since its launch earlier this year.
We've officially moved onto agents, one of the "biggest opportunities that are going to change everyone's business," according to Garman. The company has already had moves toward ramping up customer agentic AI adoption.
The Bedrock AgentCore service, launched earlier this year, gives customers access to a range of custom built agents as well as the ability to build and deploy their own.
"AgentCore is truly unique in what it enables for building of agents," he says, adding that flexibility and choice is a key focus of the service.
"You only have to use the building blocks you need. We don't force you as builders to go down a single fixed path."
So, you’re an enterprise and want to build your own AI model - seems simple, right? It’s far from it.
Training from scratch is a time-consuming, expensive process and not a realistic expectation for most enterprises.
Building with open weight models help take the edge off, but you can only go so far Garman says.
“You just don’t have a great way to get a great frontier model,” he says. AWS wants to solve that.
Amazon Nova Forge is a new service that “introduces the concept of open training models”. Essentially, you can build your own frontier AI model by combining internal enterprise data with AWS open weight models picking up the slack.
“We’ve already been working with a few customers to test out Nova Forge,” Garman says. This includes Reddit, which has built its own frontier model using the service.
“We think this idea of open training models is going to completely transform what companies can invent with AI,” Garman adds.
AWS has its own in-house models, the Nova range, which is getting a big update with the Nova 2 series.
“Nova has grown to be used by tens of thousands of customers today,” he says.
This includes three separate models - Lite for cost-effective reasoning, Pro, the “most intelligent” model for complex workloads, and Sonic, a multi-modal option. Amazon Nova 2 Omni is also coming soon, Garman reveals. This is a multimodal option which excels in reasoning and image generation, perfect for marketers and creatives.
Nova 2 Pro is a key focus here, particularly given its use in underpinning agents, according to Garman. I get the feeling we’re building towards a big agentic AI announcement.
Infrastructure is only one part of the story, Garman says as we move onto explore inference, another key focus for the company through its Bedrock service.
More than 100,000 customers are using Bedrock, according to Garman. But it’s the “volume of the usage that’s astounding”, he says.
“We now have more than 50 customers who’ve processed more than 1 trillion tokens through Bedrock. Incredible scale and momentum.”
So how does Bedrock work? It’s essentially a marketplace for in-house and third-party AI models, with customers able to pick and choose based on their own needs.
“We never believed there was going to be one model to rule them all,” Garman says, and Bedrock certainly shows that. It’s doubled the amount of models hosted on the service in the last year, underlining the varied demand from enterprise customers.
And with that we’ve got another big announcement for Bedrock with four new open weight models, including Nvidia's Nemotron and Google Gemma.
Mistral Large 3 and Ministral 3 are also coming to Bedrock Garman reveals.
AWS is well along on Trainium4 development, Garman reveals. This upcoming range will offer six-times performance, four-times memory bandwidth and 2x memory capacity compared to Trainium3. Huge performance gains that customers can expect to see next year.
And we have another big product announcement today - Trainium3 UltraServers general availability.
"Trainium3 offer the industry's best price performance for large scale AI," Garman says. Big performance gains here.
4.4x more compute, 3.9 times more memory bandwidth. With UltraServers, customers have 144 Trainium3 chips at their disposal - that's 362 PFLOPS and 706 TB/s bandwidth.
We’ve moved onto Trainium now, with Garman touting its potential for inference - a big talking point we expected to see here at re:Invent with the focus on Google’s TPUs growing and the company's recent deal with Anthropic.
“We’ve deployed over one million Trainium chips to date,” he says. And AWS isn’t stopping there. “We’re selling those as fast as we can make them.”
Anthropic is also using Trainium chips for AI training and inference through Project Ranier.
And with that we have our first big announcement here at re:Invent, the launch of AWS AI Factories.
“With this launch, we’re enabling customers to deploy dedicated AI infrastructure for AWS in their own data centers for exclusive use for them," Garman says.
“We give them access to leading AWS infrastructure and servers, including the very latest Trainium and UltraServers.”
So what do businesses need to drive agentic AI adoption? This will be a multi-pronged approach, according to Garman. Starting from the foundational infrastructure level through to data storage and the tools and solutions needed to build and deploy agents.
Of course, AWS has been focusing heavily on all these fronts.
"You have to have a highly scalable and secure cloud that deliver the absolute best performance for your workloads."
"None of what we do at AWS happens without builders, and specifically developers."
"AWS has always been passionate about developers," he adds. This is a key tenet of the company, and with developers fueling the company's sharp AI focus they've never been more important.
Developers face significant challenges, however. They're spending too much time dealing with bottlenecks. Freeing up time for developers is the key to building successful products, Garman notes.
Naturally, AI is helping solve this problem, and with the advent of AI agents the potential here is huge.
"This change is going to have as much impact on your business as much as the internet or the cloud," he says.
Infrastructure expansion continues at pace, Garman says. In the last year alone the company has added 3.8 gigawatts of data center capacity, more than any other company on earth.
Networking infrastructure is also expanding rapidly, he adds.
Matt Garman has taken to the stage, hailing the company significant growth over the last year.
"Amazon Bedrock is now powering AI inference for more than 100,000 companies around the world," he says, giving a shout-out to the AgentCore service launched earlier this year. Huge growth within just a few months and thousands of companies flocking to the agentic AI service.
We're just a couple of minutes out from Matt Garman's keynote now and the excitement is building. A packed conference hall here.
It wouldn't be a tech conference without some music absolutely blasting out at 7.30am. The keynote theater is filling up now with a torrent of people making their way through the Venetian Hotel.
While most of the big announcements from AWS are yet to be revealed this morning, we have had some big updates rolled out for the company's Transform service. First announced earlier this year, AWS has doubled down on the IT modernization platform with an array of new agentic AI capabilities.
As part of the move, enterprises will be given access to powerful new AI features aimed at supercharging legacy code modernization spanning a range of programming languages, with additional tools for mainframe modernization also announced.
You can read more about the latest update to AWS Transform in our coverage below.
• https://www.itpro.com/technology/artificial-intelligence/aws-targets-it-modernization-gains-with-new-agentic-ai-features-in-transform