AWS re:Invent 2025: Swami Sivasubramanian unveils major advancements in agentic AI
AWS re:Invent 2025's agentic AI keynote introduced episodic memory for Bedrock AgentCore, Amazon Nova Act for managing agent fleets at scale, reinforcement fine-tuning capabilities, and checkpointless training on SageMaker HyperPod to make building trustworthy AI agents faster and easier.
Last week, AWS Vice President of Agentic AI Swami Sivasubramanian headlined re:Invent 2025 with a keynote focused on making AI agents easier to build, scale, and trust.
Key announcements included significant expansions to the Strands Agents SDK, now supporting TypeScript and edge devices to unlock new development possibilities. Amazon Bedrock AgentCore received a major upgrade with episodic memory functionality, enabling agents to understand user behavior and recognize patterns across interactions—making them smarter with every experience.
On the customization front, AWS introduced Reinforcement Fine-tuning in Amazon Bedrock for improved model accuracy, alongside new SageMaker AI tools that slash customization timelines from months to days. The company also announced checkpointless training on SageMaker HyperPod, allowing recovery from faults in minutes across thousands of AI accelerators.
Perhaps most notable was Amazon Nova Act, a new service for building and managing agent fleets that automate production UI workflows at scale. The platform offers end-to-end training for comprehensive agent interactions.
Sivasubramanian emphasized trust as paramount, with AWS implementing automated reasoning algorithms to logically verify agent behavior. Combined with updates to yesterday's Frontier Agents (Kuro, DevOps, and Security), AWS is positioning itself as the platform where agents work alongside humans most effectively.
In case you missed it, you can still revisit Dr. Sivasubramanian's full keynote at the AWS Events YouTube channel:
Ellie Ramirez-Camara is the News Editor at Data Phoenix, where she writes the daily AI newsdesk — covering model releases, research, funding rounds, and policy across the AI and machine-learning industry. She tracks announcements from labs and startups alike and distills them into clear, source-linked reporting for practitioners.
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