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An unparalleled level of interest in generative AI and agentic AI is driving organizations to rethink their data strategy. While there is a need for data foundation constructs such as data pipelines, data architectures, data stores and data governance to evolve, there are business elements that need to stay constant like cost-efficiency and effectively collaborating across data estates.

Struggling to understand the difference between AWS Strands Agents SDK and Amazon Bedrock AgentCore? This is the video for you. Strands Agents SDK Documentation: https://strandsagents.com/ Bedrock AgentCore Documentation: https://docs.aws.amazon.com/bedrock-agentcore/latest/devguide/what-is-bedrock-agentcore.html Sign up for my Newsletter to receive regular AWS updates AND get a FREE PDF that includes 5 AWS Project Ideas: https://beabetterdev.

n this episode of "AWS Show and Tell - GenAI for Financial Advisors: Portfolio Analysis & Client Experience Tools," we explore the art of the possible for integrating Generative AI capabilities into enterprise financial services platforms. Built on a foundation of reusable MCP tools, optimized agentic microservices, and modernized data architectures, this session demonstrates how AWS enables financial advisors to deliver smarter, faster, and more personalized client experiences.

AWS delivers new data center network design that replaces traditional hierarchical "fat tree" networks with a flat network architecture based on random graph theory. The new network design delivers 33% better throughput, 27% lower costs, and 69% fewer routers while reducing the use of power by networking equipment over 40%. Learn more about Future of Cloud Computing: https://go.aws/innovation Subscribe to AWS: https://go.aws/subscribe Create a free AWS account: https://go.

Get an inside look at how Amazon harnesses generative AI to transform developer productivity. Learn how the combination of AWS Bedrock and agentic AI frameworks powers intelligent developer tools that streamline workflows and automate routine tasks. See real-world examples of spec-driven development automation and AI agent integration. Walk away understanding how to implement similar AI-powered development tools to boost productivity and accelerate delivery in your organization.

This session provides a deep dive into Amazon DynamoDB and shares insights into how DynamoDB is architected and how it’s able to deliver the scalability and response times that customers have come to expect. DynamoDB is used by over one million AWS customers, and powers hundreds of applications that exceed half a million requests per second. In this talk we explore the architecture of DynamoDB, and of several specific features.

PostgreSQL performance isn’t magic—it’s engineering. In this code talk, we dive deep into practical tuning techniques to avoid common pitfalls that silently degrade performance by improving an underperforming PostgreSQL database workload. Learn how excessive indexes hurt write throughput, why HOT updates fail, and how vacuum behavior can stall your system.

Your AI response looks right, feels right... but how do you KNOW it's right? 🤔 Amazon Bedrock Guardrails' Automated Reasoning gives you mathematical certainty with up to 99% accuracy to minimize model hallucinations. Perfect for regulated industries! 🏥💰 #generativeAI #AWS #ResponsibleAI #AutomatedReasoning

Discover why memory architecture is the foundation of intelligent AI agents. This session explores how short-term and long-term memory transform stateless chatbots into adaptive, context-aware systems that learn from interactions and deliver measurable business outcomes with implementation examples including Amazon Bedrock AgentCore. - Mark Cliffe, Chief Engineering Officer, Fintua; - Venkatesh Periyathambi, Principal Data SA, AWS.

Robinhood has evolved from a fintech disruptor to an AI-first financial innovator, with virtually everything now built using agentic AI through Amazon Bedrock. In just six months, the company scaled from 500 million to 5 billion tokens daily while cutting AI costs by 80% and reducing development time by half.

Discover how Model Context Protocol (MCP) is transforming the way AI integrates into daily life. 🎲 Use case 1: AI game master for Dungeons & Dragons 📝 Use case 2: Cloud-based personal to-do list controlled via MCP server MCP standardizes how AI tools communicate—making them smarter, more connected, and more practical for everyday scenarios.

Stateless LLMs just aren't enough. It's time to build applications that learn, remember, and evolve. This session dives deep into the architecture of sophisticated agent memory systems. We’ll show you how to move from simple context windows to a unified memory provider that enables true intelligence. You'll learn about different types of memory—episodic, semantic, and procedural—and how MongoDB becomes the single data platform for all of them.