AWS has expanded its cloud AI infrastructure with the release of Strands and Amazon Bedrock AgentCore, establishing a streamlined pathway for developing and deploying production-grade autonomous agents. Strands functions as an open-source application framework that manages agent logic, model routing, and tool coordination, while AgentCore provides a managed operational layer on AWS. This infrastructure handles session isolation, scalable runtime environments, observability, and long-term memory without restricting how the agent behaves. To demonstrate the integrated workflow, AWS engineers constructed a subject-matter expert triage system capable of routing queries across mathematics, physics, chemistry, and geography. Rather than relying on rigid keyword classifiers, the agent utilizes foundation models to dynamically interpret ambiguous prompts and apply appropriate subject-specific response templates. The development lifecycle relies on the AgentCore command-line interface to scaffold projects, manage dependencies, and provision infrastructure via AWS CloudFormation. Teams can validate functionality locally before deploying to a managed runtime that supports streaming, HTTP, and standardized agent-to-agent protocols. A core advancement in this architecture is AgentCore Memory, which preserves cross-session user preferences and durable facts. By mapping interaction history to opaque actor identifiers, the system extracts and retrieves contextual data using configurable strategies such as preference tracking and semantic summarization. This eliminates repetitive prompt engineering while maintaining conversation continuity. The runtime automatically provisions IAM roles, enforces authorization policies, and routes telemetry to CloudWatch and X-Ray, ensuring enterprise-grade security. The platform deliberately decouples application logic from deployment infrastructure, allowing organizations to swap foundational models or adjust system instructions without rearchitecting underlying cloud resources. Billing follows standard AWS consumption models, charging exclusively for inference compute, storage, and managed AgentCore services. This modular design enables developers to incrementally adopt capabilities like browser automation or code interpretation as agent responsibilities expand. The combined release significantly reduces the operational friction associated with scaling AI workloads. By abstracting infrastructure complexity and providing native memory and observability integrations, AWS offers a standardized framework for enterprises to transition from experimental prototypes to maintainable, cloud-native agentic systems.