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In this code talk, learn how to build agentic AI systems that automate Amazon EKS cluster management, from real-time issue diagnosis to guided remediation. Discover how to create agents that connect with AWS services through Model Context Protocol (MCP) to simplify operational tasks like incident response and debugging. The live coding demo showcases how agentic systems can leverage tribal knowledge within a company to provide contextual troubleshooting assistance and even auto remediation.

Last week we covered the building blocks. This week we put them together. Morgan and Raf tackle the real-world problems that show up the moment you try to make an agent useful: memory that survives a restart, context windows that overflow, models that ignore instructions, and humans that need to stay in the loop. They'll walk through conversation management, session persistence, Agent SOPs for reliability, hooks for human escalation, and steering to keep agents on track.

Follow along as we uncover the powerful forces shaping the future of AI coding. From the emergence of intelligent agents to Model Context Protocol (MCP) servers, we'll explore the latest advancements and real-world use cases that are redefining what's possible for developer productivity and creativity. By the end, you'll feel empowered to embrace the magic of AI, no matter how daunting the technology may seem. Learn More: More AWS events: https://go.

Learn how to build scalable, autonomous AI workflows using the Agent-to-Agent (A2A) protocol and Model Context Protocol (MCP). This session demonstrates how to design specialized agents that dynamically discover each other's capabilities and collaborate on complex tasks across platforms and implementations. Using MCP for standardized context integration, you'll build horizontally scalable, serverless agents with AWS Lambda, Amazon Bedrock, and Momento Cache.

Want to learn the best way to test your GenAI applications as you build? Drop a 🚗 emoji in the comments! Join Steph Gooch and Ryan French as they look at the project with BMW that kicked off this idea and the tool that the PACE team made to speed up your testing! They look at why testing you GeAI Application is important, what tests to use and demo the GenAI toolkit https://github.com/awslabs/generative-ai-toolkit?trk=f90004aa-b866-47ba-9668-94b16f71e694&sc_channel=sm

Many organizations deploy Amazon EC2 instances without fully leveraging available optimization opportunities. EC2 offers over 850 instance types across six categories: general purpose, compute optimized, memory optimized, storage optimized, accelerated computing, and high-performance computing. Most instances run on the AWS Nitro System, which delivers enhanced performance through dedicated hardware for compute, storage, and networking functions.

AWS's biggest customers rely on Terraform as their front door to the cloud. In this session, HashiCorp reveals how Kiro has dramatically accelerated their Terraform Provider development workflow. Learn the practical tips and best practices their team discovered while implementing Kiro. Discover how this collaboration is helping deliver cutting-edge AWS capabilities to Terraform users faster than ever before. Learn more: More AWS events: https://go.

See how Amazon Bio Discovery simplifies the entire antibody discovery workflow in this complete product walkthrough. Amazon Bio Discovery is a unified lab-in-the-loop application that puts AI-powered antibody design directly in the hands of bench scientists—no coding required.

For more details on this topic, visit the AWS Knowledge Center on AWS re:Post and read the full article associated with this video: https://repost.aws/knowledge-center/share-ami-account The AWS Knowledge Center contains trusted, expert-reviewed answers to frequently asked questions across AWS services — including EC2, S3, IAM, Lambda, Bedrock, and more.

In this episode of "The AWS Pulse" with Ali Maaz from AWS's Developer Experience team, who leads strategy behind Amazon Q Developer and Kiro, we'll discuss how these AI coding tools are changing software development, why AWS built them differently and tackle the tough questions about security and pricing controversies that have sparked debate in the community. This is a straight conversation about what works, what doesn't and where AI-assisted coding is headed.

Amazon Aurora DSQL is a serverless, distributed SQL database that uses decades of Amazon innovation and operational excellence. Join this session to dive into the design and key innovative technologies that make Aurora DSQL the ideal choice for new applications and applications which require the highest level of resilience. Learn how active-active architecture in Aurora DSQL delivers single- and multi-Region resiliency and virtually unlimited scale. Learn more: More AWS events: https://go.

Join this session to explore advanced networking and observability capabilities in Amazon EKS, from securing multi-tenant environments to gaining deep visibility into cluster traffic patterns. We'll share comprehensive strategies for implementing layered network security controls at both infrastructure and application layers which enable granular traffic observability and optimize network performance across distributed workloads.