Amazon Web Services’ annual tech conference AWS re:Invent has wrapped up another day with a deluge of product news and keynotes — plus the obligatory customer success stories.
The unsurprising theme is AI for the enterprise. This year it’s all about upgrades that give customers greater control to customize AI agents, including one that AWS claims can learn from you and then work independently for days.
AWS re:Invent 2025, which runs through December 5, started with a keynote from AWS CEO Matt Garman, who leaned into the idea that AI agents can unlock the “true value” of AI.
“AI assistants are starting to give way to AI agents that can perform tasks and automate on your behalf,” he said during the December 2 keynote. “This is where we’re starting to see material business returns from your AI investments.”
On December 3, the conference pressed on with its AI agents messaging, as well as deeper dives into customer stories. Swami Sivasubramanian, vice president of Agentic AI at AWS, gave one of the keynote talks. To say he was bullish is perhaps understating the vibe.
“We are living in times of great change,” Sivasubramanian said during the talk. “For the first time in history, we can describe what we want to accomplish in natural language, and agents generate the plan. They write the code, call the necessary tools, and execute the complete solution. Agents give you the freedom to build without limits, accelerating how quickly you can go from idea to impact in a big way.”
While AI agent news promises to be a persistent presence throughout AWS re:Invent 2025, there were other announcements, too. Here is a roundup of the ones that got our attention. TechCrunch will update this article, with the newest insights at the top, through the end of AWS re:Invent. Be sure to check back.
Doubling down on LLMs
AWS announced more tools for enterprise customers to create their own models. Specifically, AWS said it is adding new capabilities for both Amazon Bedrock and Amazon SageMaker AI to make building custom LLMs easier.
For instance, AWS is bringing serverless model customization to SageMaker, which allows developers to start building a model without needing to think about compute resources or infrastructure. The serverless model customization can be accessed through either a self-guided path or by prompting an AI agent.
AWS also announced Reinforcement Fine Tuning in Bedrock, which allows developers to choose a preset workflow or reward system and have Bedrock run their customization process automatically from start to finish.
Andy Jassy shares some numbers
Amazon CEO Andy Jassy took to social media platform X to expound on AWS chief Matt Garman’s keynote speech. The message: The current generation of its Nvidia-competitor AI chip Trainium2 is already bringing in loads of cash.
His comments were tied to the reveal of its next-generation chip, Trainium3, and meant to forecast a promising revenue future for the product.
Database savings arrives
Tucked among the dozens of announcements is one item that is already getting cheers: Discounts.
Specifically, AWS said it was launching Database Savings Plans, which help customers reduce database costs by up to 35% when they commit to a consistent amount of usage ($/hour) over a one-year term. The company said the savings will automatically apply each hour to eligible usage across supported database services, and any additional usage beyond the commitment is billed at on-demand rates.
Corey Quinn, chief cloud economist at Duckbill, summed it up well in his blog post, “Six years of complaining finally pays off.”
Can’t get a better deal than free, Amazon hopes
Is there any way for another AI coding tool to win the hearts of startup founders? Amazon hopes a year’s worth of credits, for free, will do the trick for its offering, Kiro. The company will be giving away credits to Kiro Pro+ to qualified startups that apply for the deal before the end of the month. However, only early-stage startups in certain countries are eligible.
An AI training chip and Nvidia compatibility
AWS introduced a new version of its AI training chip called Trainium3 along with an AI system called UltraServer that runs it. The TL;DR: This upgraded chip comes with some impressive specs, including a promise of up to 4x performance gains for both AI training and inference while lowering energy use by 40%.
AWS also provided a teaser. The company already has Trainium4 in development, which will be able to work with Nvidia’s chips.
Expanded AgentCore capabilities
AWS announced new features in its AgentCore AI agent building platform. One feature of note is Policy in AgentCore, which gives developers the ability to more easily set boundaries for AI agents.
AWS also announced that agents will now be able to log and remember things about their users. Plus it announced that it will help its customers evaluate agents through 13 prebuilt evaluation systems.
A nonstop AI agent worker bee
AWS announced three new AI agents (there is that term again) called “Frontier agents,” including one called “Kiro autonomous agent” that writes code and is designed to learn how a team likes to work so it can operate largely on its own for hours or days.
Another of these new agents handles security processes like code reviews, and the third does DevOps tasks such as preventing incidents when pushing new code live. Preview versions of the agents are available now.
New Nova models and services
AWS is rolling out four new AI models within its Nova AI model family — three of which are text generating and one that can create text and images.
The company also announced a new service called Nova Forge that allows AWS cloud customers to access pre-trained, mid-trained, or post-trained models that they can then top off by training on their own proprietary data. AWS’s big pitch is flexibility and customization.
Lyft’s argument for AI agents
The ride-hailing company was among many AWS customers that piped up during the event to share their success stories and evidence of how products affected their business. Lyft is using Anthropic’s Claude model via Amazon Bedrock to create an AI agent that handles driver and rider questions and issues.
The company said this AI agent has reduced average resolution time by 87%. Lyft also said it has seen a 70% increase in driver usage of the AI agent this year.
An AI Factory for the private data center
Amazon also announced “AI Factories” that allow big corporations and governments to run AWS AI systems in their own data centers.
The system was designed in partnership with Nvidia and includes both Nvidia’s tech and AWS’s. While companies that use it can stock it with Nvidia GPUs, they can also opt for Amazon’s newest homegrown AI chip, the Trainium3. The system is Amazon’s way of addressing data sovereignty, or the need of governments and many companies to control their data and not share it, even to use AI.
Check out the latest reveals on everything from agentic AI and cloud infrastructure to security and much more from the flagship Amazon Web Services event in Las Vegas. This video is brought to you in partnership with AWS.
