Antonio Rodriguez

Get hands-on implementing secure authentication and access management for AI agents using Amazon Bedrock AgentCore Identity. In this builder's session, you'll practice configuring agent identities, implementing OAuth-based tool access, and setting up secure agent access.

As generative AI agents take on more complex tasks, the need for secure, contextual identity becomes critical. In this chalk talk, dive into Amazon Bedrock AgentCore Identity, the foundational building block that enables secure, auditable, and role-aware execution for AI agents.

Join this chalk talk to uncover how Amazon Bedrock IDE within Amazon SageMaker Unified Studio empowers users to rapidly build, customize, and verify generative AI applications through governed collaboration.

When adopting generative AI, enterprises face unique challenges including scaling, cost management, and resource optimization. This session explores building a robust, enterprise-grade generative AI platform using Amazon Bedrock.

This builders’ session dives into techniques to simplify the creation, evaluation, versioning, and sharing of prompts to help you get the best responses from foundation models for your use case. Learn how to use Amazon Bedrock’s visual builder to author executable flows, enabling rapid prototyping and collaboration.

Foundation model (FM) customizations help you build differentiated generative AI applications using your own data. It’s easy to securely customize models in Amazon Bedrock.

Join this chalk talk to learn how to prepare data for ML in minutes using Amazon SageMaker. SageMaker offers tools to simplify data preparation so that you can label, prepare, and understand your data and engineer model features.

Recommender systems are everywhere. Many successful e-commerce companies leverage personalized recommendations to help their customers discover new products, find the right product when they need it, discover similar products, and more.