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Join Dave Levy, Vice President, Worldwide Public Sector, Healthcare and Life Sciences to explore how AWS delivers the most secure cloud for AI and government workloads. Learn how customers are building agentic AI solutions to accelerate modernization, empower developers, and secure their organizations. Discover how AWS powers global national security and defense missions and drives digital transformation across the public sector. Learn more about AWS events: https://go.

Running user- or AI-generated code at scale? You shouldn’t have to choose between strong isolation and fast start-up speed. Introducing AWS Lambda MicroVMs. A new serverless compute primitive for isolated, stateful code execution at Lambda speed. Isolated Sandboxes: Every session gets its own dedicated sandbox. Firecracker-powered, VM-level isolation. No shared kernel, no shared memory. And no shared state between users.

Everybody's talking about AI agents — but how do you actually build one? In this hands-on tutorial, you'll learn what makes up an AI agent (model, tools, system prompt, and the agentic loop) and then build your own from scratch using the Strands Agents SDK and Python. What you'll build: - A basic agent in 3 lines of code - Custom tools using the @tool decorator - A system prompt to shape agent behavior - An MCP server connection for real-world tool use Resources: Strands Agents: https://go.

Claude Code is an agentic coding tool by Anthropic that helps you build features, fix bugs, and automate development tasks. But some developers can't use it due to data residency, compliance, or billing requirements. With Amazon Bedrock, you can run Claude Code with your data staying entirely within AWS — no data leaving your infrastructure.

🤖 Stop babysitting your coding agents. In this AWS Show & Tell livestream, we demo a fully automated Software Development Lifecycle (SDLC) powered by AI coding assistants running on Amazon Bedrock AgentCore. 🎯 Open an issue → add a label → watch an AI agent explore your codebase, implement the feature, and open a pull request.

Amazon SageMaker AI helps you train, customize, and deploy ML models, including FMs, with fully managed infrastructure, tools, and workflows — and streamline every step of the data lifecycle all in a single place. Learn more about SageMaker AI here: http://go.aws/4gAmAv2 Subscribe to AWS: https://go.aws/subscribe Create a free AWS account: https://go.aws/signup Try AWS for free: https://go.aws/free Connect with an expert: https://go.aws/contact Explore more: https://go.

Start your Cloud Practitioner learning journey in AWS Cloud Quest: https://skillbuilder.aws/learn/FU5WCYVGKY/aws-cloud-quest-cloud-practitioner/JF9TKU68GT The next generation of cloud builders needs to know how to design, not just how to build. AWS Cloud Quest is a role-based learning experience on AWS Skill Builder where you explore customer needs, clarify requirements in AI-powered conversations, choose an AWS solution, and build and validate it in a live AWS environment.

AWS Transform is the first service to leverage specialized AI agents to simplify and accelerate modernization of Windows .NET applications, VMware systems, and mainframes, empowering customers to migrate up to 5x faster. At AWS re:Invent 2025, we launched new capabilities that enable rapid modernization of any code or application, so customers can reduce their legacy tech debt and shift valuable resources toward innovation with AWS Transform.

Everyone's talking about Jev, the new System 1 model that's fast and cheap because it does one forward pass and returns typed decisions instead of generating text. You can't build an agent out of Jev, but you can put Jev inside an agent to catch bad tool calls before they run. That's what I built. Github repo: https://go.aws/4hLedhp Prompt used: Create a single-file teaching demo that uses the actual Strands Interventions API to show how Jev can evaluate a proposed tool call before it runs.

In Formula 1, victories depend on turning millions of data points into winning decisions. Organizations can apply this same precision to unlock value from underutilized data assets. Drawing from F1's model, we present a three-part framework for data excellence: customer-focused decisions, dynamic people- powered strategies, and market-responsive structures. Learn practical approaches to evolve your data strategy into a business advantage in the AI era. Learn more: More AWS events: https://go.

As generative and agentic AI transform business models, leaders must architect new operating models that bridge technology capabilities with business value. This advanced session reveals proven approaches for scaling AI from experiments to enterprise-wide value creation. Learn to shape AI-driven business strategies, design advanced decision systems, and build governance frameworks that accelerate adoption while managing risk.

AI is dramatically accelerating technological evolution, with new architectural primitives emerging monthly. This unprecedented pace transforms the Solutions Architect (SA) role from system designer to change navigator. Learn how SAs deliver value by enabling and de-risking rapid transformation while maintaining architectural stability. Discover strategies for developing new capabilities while preserving foundational expertise.