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Chapter 12 of the Building AI Agent Harnesses with Strands Agents course. In previous multi-agent chapters, control was either centralized (one parent calls children as tools, Ch 10) or predetermined (a graph defines the execution path, Ch 11). Swarms decentralize both. In a swarm, multiple agents share a workspace or communication channel. Each agent has its own tools, its own prompt, its own specialization.

AWS Graviton-based Amazon EC2 instances provide the best price performance for workloads in Amazon EC2. In this session, dive deep into the AWS Graviton processor and learn about its workload performance, energy efficiency, and software offerings. Learn about common use cases, best practices to optimize your workloads across various applications, customer success stories, and how you can accelerate your AWS Graviton journey. Learn more: More AWS events: https://go.

At Philips, AI is transforming healthcare and driving demand for smarter solutions. To help teams keep pace, Philips collaborated with AWS to leverage AWS Skill Builder, enabling employees to continuously develop AI skills and apply them across the organization. More than 5,000 employees have already used AWS Skill Builder, helping accelerate innovation cycles and deliver solutions faster.

AWS Backup helps over 140,000 customers protect more than 2.9 exabytes of application data across AWS services. It offers policy-based data protection, streamlining backup management, enhancing security controls, and simplifying compliance reporting. In this session, you'll learn how to use AWS Backup, hear what's new, and discover practical implementation strategies.

Discover how to architect scalable, production-ready agentic AI applications on AWS that deliver autonomous, multi-agent solutions for complex business challenges. Many organizations struggle with designing AI agents for real-world complexity, from managing context effectively to ensuring secure, scalable deployments.

Chapter 5 of the Building AI Agent Harnesses with Strands Agents course. Last chapter was about watching the agent work. This chapter is about reaching in and changing what it does. Hooks fire at the same event points as callbacks (before/after tool calls, before/after model calls, cycle boundaries) but they can modify or cancel what's about to happen.

Full Length Video: https://youtu.be/Bo-8p5UsArc An Executive Leader in Data and AI needs to navigate the waters in cultural change, whilst balancing out the value story of the business. Find out from our Site Lead for the Executive Briefing Centre, Keith Inch and the Senior AI Solutions Team Lead, Ahmed Raafat, on what we hear from Executives that come to visit AWS and what they say they need to unlock that value in their organization #AWS #AmazonWebServices #CloudComputing

Join Mercedes-Benz to learn about how they are transforming their global vehicle ordering system by migrating mainframe-based infrastructure to AWS and accelerating modernization with Generative AI. Their approach blends replatforming with AWS GenAI-driven code transformation, enabling AI agents to streamline architecture, development, and testing. This modernization secures business continuity, strengthens security, and boosts agility, resulting in a scalable, future-ready IT landscape.

Scared of the command line? Don't be! In this video, we'll break down the fundamentals of Linux/Unix command line tools that every developer should know. Whether you're working with coding assistants like Kiro or just want to level up your terminal skills, this video covers everything from basic commands to powerful piping techniques. Kiro CLI: https://go.aws/3O1mS48 TLDR: https://go.aws/4tn39uN Sharkdp: https://go.aws/4thAVS4 JQ: https://go.aws/4verdlA Follow AWS Developers! 🆇 X: https://go.

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Mama J is back, and this time it's Containers. AWS Developer Advocate Eric Johnson takes on the classic "but it works on my machine" problem and explains containers with his mom, Mama J, who still hasn't touched a line of code. Watch the full video here → https://go.aws/4vVSgB0

Amazon Bedrock's Project Mantle represents a fundamental reimagining of how we serve generative AI inference at scale. Join AWS engineers as we unveil Mantle's architecture and take you behind the scenes, exploring how we've raised the bar on security, performance, and developer experience.