Build and deploy scalable AI agents with NVIDIA NeMo, Amazon Bedrock AgentCore, and Strands Agents

Why it matters (2 min)

• This post is co-written with Ranjit Rajan, Abdullahi Olaoye, and Abhishek Sawarkar from NVIDIA.
• AI’s next frontier isn’t merely smarter chat-based assistants, it’s autonomous agents that reason, plan, and execute across entire systems.
• Open receipts to verify and go deeper.

Go deeper (8 min)

Context

This post is co-written with Ranjit Rajan, Abdullahi Olaoye, and Abhishek Sawarkar from NVIDIA. AI’s next frontier isn’t merely smarter chat-based assistants, it’s autonomous agents that reason, plan, and execute across entire systems. But to accomplish this, enterprise developers need to move from prototypes to production-ready AI agents that scale securely. This challenge grows as enterprise problems become more complex, requiring architectures where multiple specialized agents collaborate to accomplish sophisticated tasks. Building AI agents in development differs fundamentally from deploying them at scale. Developers face a chasm between prototype and production, struggling with performance optimization, resource scaling, security implementation, and operational monitoring. Typical approaches leave teams juggling multiple disconnected tools and frameworks, making it difficult to maintain consistency from development through deployment with optimal performance. That’s where the powerful combination of Strands Agents , Amazon Bedrock AgentCore , and NVIDIA NeMo Agent Toolkit shine. You can use these tools together to design sophisticated multi-agent systems, orchestrate them,…

For builders

Builder: read docs/changelog; watch for breaking changes, quotas, and pricing.

Verify

Prefer primary announcements, papers, repos, and changelogs over reposts.

Receipts

1. Build and deploy scalable AI agents with NVIDIA NeMo, Amazon Bedrock AgentCore, and Strands Agents (AWS Machine Learning Blog)