In this episode of the AWS Developers Podcast, we dive deep into Amazon Bedrock Agent Core Identity with Abram Douglas. Learn how this new service helps developers manage identities and authentication flows for AI agents at scale. Discover the seven core components of Agent Core and understand how the identity service simplifies complex OAuth2 flows and token management. Whether you're building AI agents that need to interact with third-party services like Google Calendar or Slack, this episode explains how Agent Core Identity removes the undifferentiated heavy lifting of identity management, token vaulting, and secure credential handling. Perfect for developers looking to deploy production-ready AI agents with enterprise-grade security.
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Building AI Agents with the Strands SDK
In this episode of the AWS Developers Podcast, we dive deep into Strands Agents, AWS's open-source framework for building AI agents. Our guest Arron Bailiss, Principal Engineer and Tech Lead for Strands, explains how this framework evolved from an internal AWS tool to a developer-friendly, open-source solution. Learn how Strands simplifies AI agent development with just a few lines of code while maintaining production-ready capabilities. Aaron discusses the framework's unique model-driven approach, its support for both MCP and A2A protocols, and how it powers various AWS services including Amazon Q Developer and AWS Glue. Discover how Strands enables multi-agent systems through swarms, supports various deployment options, and get insights into the roadmap including TypeScript support and voice agent capabilities.
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Scaling E-commerce with Serverless: The moonpig.com Story
In this episode, we dive deep into Moonpig's migration journey from an on-premise ASP.NET monolithic application to a fully serverless architecture on AWS. Richard Pearson, Head of Engineering, and Alexis Lowe, Principal Engineer at Moonpig, share their experience transforming a 25-year-old e-commerce platform. They discuss how they tackled the challenges of migrating from SQL Server to DynamoDB, implemented multi-region deployment, and achieved seamless scalability for their peak trading periods. Learn about their "no VPC" policy, their approach to observability, and how they organized their teams to embrace DevOps culture. This episode is particularly relevant for organizations considering a similar journey to serverless architecture or looking to scale their platforms globally.
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Deploying MCP servers on Lambda
Update Oct 25.: After we recorded this episode (July 10th 2025), AWS launched Amazon Bedrock AgentCore (that went in preview on July 16th, 2025) and generally available since Oct. 13rd, 2025. AgentCore is the recommanded solution to deploy your MCP agents on AWS. We keep this episode available as a learning experience but deploying MCP on Lambda is not the recommanded architecture for your production workloads.
In this episode, we dive deep into MCP (Model Context Protocol) servers on AWS Lambda. We explore what MCP is, how it enables AI systems to interact with tools through standardized protocols, and practical implementations on AWS Lambda. The discussion covers authentication mechanisms, deployment strategies, and the future potential of MCP servers as a marketplace for AI capabilities. Whether you're building AI-powered applications or interested in exposing your business capabilities to AI systems, this episode provides valuable insights into the technical aspects and business opportunities of MCP servers.
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When AI meets biology: Using LLM to find natural alternatives to antibiotics
In this episode, we explore how Phagos, a French biotech startup, combines biology, data science, and cloud computing to combat antimicrobial resistance. Their innovative approach uses bacteriophages - natural predators of bacteria - as an alternative to antibiotics. We discuss how they leverage AWS services, including SageMaker and batch processing, to analyze genomic data and train specialized language models that can predict phage-bacteria interactions. Our guests explain how they process terabytes of genetic data, train and deploy AI models, and create user-friendly interfaces for their lab scientists. This fascinating conversation reveals how cloud computing and artificial intelligence are revolutionizing biotechnology and potentially helping solve one of this century's biggest health challenges.
Brasil