Amazon Bedrock AgentCore: AWS's Answer to AI Agents

The AI landscape is shifting from simple chatbots to sophisticated agents that can reason, plan, and take action across your enterprise systems. But if you've tried to move an AI agent from prototype to production, you've likely hit the same wall everyone else has: infrastructure complexity, security concerns, scaling challenges, and the nightmare of integrating multiple tools and data sources.

Enter Amazon Bedrock AgentCore, AWS's newly announced platform (currently in preview) that aims to solve the production deployment challenge for AI agents. Here's what you need to know.

What Is Amazon Bedrock AgentCore?

Amazon Bedrock AgentCore is an agentic platform designed to build, deploy, and operate highly capable agents securely at scale, enabling agents to take actions across tools and data while running securely with low-latency and extended runtimes. Think of it as the enterprise-grade infrastructure layer you need to move AI agents from experimental code to mission-critical applications.

The key difference between AgentCore and other solutions? It's both framework-agnostic and model-agnostic, working seamlessly with popular frameworks like Strands Agents, CrewAI, LangGraph, and LlamaIndex, while supporting any Large Language Model. You're not locked into a single ecosystem or forced to rewrite code when better models emerge.

The Core Components

AgentCore Runtime

A secure, serverless runtime that empowers organizations to deploy and scale both AI agents and tools, regardless of framework, protocol, or model choice. The runtime provides complete session isolation using dedicated microVMs for each user session, critical for agents handling sensitive operations. It also offers industry-leading extended runtime support because agents can run for up to eight hours for complex asynchronous workloads.

AgentCore Gateway

Here's where things get practical. The Gateway automatically converts APIs, Lambda functions, and existing services into MCP-compatible tools so developers can quickly make these essential capabilities available to agents without managing integrations. No more months of custom integration work—your existing tools become agent-ready with minimal code.

AgentCore Memory

Memory eliminates complex memory infrastructure management while providing full control over what the AI agent remembers, with support for both short-term memory for multi-turn conversations and long-term memory that can be shared across agents and sessions. This is crucial for building agents that actually remember context and improve over time.

AgentCore Identity

A secure, scalable agent identity and access management capability that's compatible with existing identity providers like Okta, Entra, and Amazon Cognito, eliminating needs for user migration or rebuilding authentication flows. Your agents can securely access AWS resources and third-party services with just-enough permissions.

AgentCore Observability

You can't operate what you can't observe. Observability helps developers trace, debug, and monitor agent performance through unified operational dashboards. Full visibility into agent behavior, integrated with CloudWatch for centralized monitoring.

Built-in Tools

AgentCore provides two powerful built-in capabilities: a Code Interpreter tool that enables agents to write and execute code securely, and a Browser Tool that allows agents to navigate websites and complete complex web-based tasks within a fully managed, secure sandbox environment.

Why This Matters for Enterprise

Organizations need an agentic architecture that embraces flexibility and openness rather than rigid frameworks or singular models, building systems that can incorporate new models as they emerge, connect to proprietary data sources, and seamlessly integrate with existing tools.

Companies like Thomson Reuters are already seeing the impact. They're exploring AgentCore because of its potential to accelerate how they build and deploy agentic workflows, compressing timelines from months to weeks, while reducing engineers' cognitive load by abstracting away infrastructure complexity^[1].

Epsilon, a major player in marketing technology, has used AgentCore to revolutionize campaign automation, reducing campaign setup time by 30%, increasing personalization by 20%, and saving teams 8 hours weekly^[2].

AgentCore vs. Bedrock Agents: What's the Difference?

If you're already familiar with Amazon Bedrock Agents, you might be wondering where AgentCore fits. Bedrock Agents is a fully managed service that allows you to build and configure autonomous agents without managing infrastructure or writing custom code, using a configuration-based approach. It's perfect for teams who want to build agents quickly without deep technical expertise.

AgentCore, conversely, is designed for scenarios requiring custom frameworks or more flexibility in agent architecture, providing infrastructure services for deploying and operating agents built with any framework. If you're building complex, multi-agent systems or need fine-grained control, AgentCore is your tool.

Getting Started

The barrier to entry is surprisingly low. Developers can test agents locally, launch to the cloud with one command using the AgentCore starter toolkit, and monitor everything through CloudWatch. The workflow is designed for teams that want to move from prototype to production quickly while staying inside the AWS ecosystem.

You'll need:

• An AWS account with proper credentials
• Python 3.10 or later
• Model access enabled in Amazon Bedrock (for example, Claude Sonnet 4)
• Your preferred agent framework installed

From there, you write your agent code as you normally would, use the AgentCore CLI toolkit to deploy, and you're running at scale.

The Bottom Line

AI agents are moving from experimental novelty to business necessity. But the gap between "cool demo" and "trusted production system" has been massive. AgentCore is AWS's bet on solving that gap by providing enterprise-grade infrastructure that works with the tools and frameworks developers already use.

AgentCore helps eliminate the trade-off between open source flexibility and enterprise-grade security and reliability, allowing organizations to focus on creating business value rather than building security and operational foundations from scratch.

For enterprises looking to deploy AI agents at scale, whether for customer service automation, data analysis, content creation, or process optimization, AgentCore provides a compelling path forward. The framework-agnostic approach means you can start building today without fear of lock-in or obsolescence as the AI landscape continues to evolve.

Currently in preview, AgentCore represents AWS's vision for the future of agentic AI: flexible, secure, scalable, and production-ready. If you're considering moving beyond AI experiments into real-world deployment, it's worth a serious look.

Sources:

1. https://www.constellationr.com/blog-news/insights/amazon-bedrock-agentcore-generally-available
2. https://www.aboutamazon.com/news/aws/aws-summit-agentic-ai-innovations-2025

Interested in exploring how AI agents could transform your business processes? Metal Toad's team can help you evaluate, architect, and deploy agent-based solutions that drive real business value. Get in touch to start the conversation.