Amazon's latest announcement at AWS Summit New York 2025 signals a fundamental shift in how we think about AI agents—and it's about to change everything.

Agents are everywhere…but we know there’s been a fundamental problem

AI agents have captivated us for months now. From simple chatbots to complex workflow automators, these autonomous software systems promise to revolutionize how we interact with technology. But there's been a major issue in the industry when I talk to customers: getting AI agents from a sexy demo to production-ready system has been incredibly difficult.

As Swami Sivasubramanian, AWS VP of Agentic AI, put it at the AWS Summit: "Despite all these open source frameworks and protocols, getting agents to production is still too hard, because of the dynamic and autonomous nature of agents and their effects in production."

Well, it’s about ot change…As Amazon Web Services just announced Amazon Bedrock AgentCore, and it's not just another AI tool—it's a complete paradigm shift that addresses every major barrier preventing AI agents from reaching their full potential in enterprise environments.

AWS Bedrock AgentCore - A set of services to deploy and operate highly capable agents securely using any framework and model

What Makes AgentCore Different: The Complete Agent Infrastructure Stack

Traditional AI agent development has been like building a house without proper foundation—developers had to construct everything from scratch, including security, memory management, tool integration, and monitoring. AgentCore changes this by providing what amounts to a complete "agent operating system."

The Seven Pillars of Production-Ready Agents

Based on AWS's presentation materials, AgentCore consists of seven integrated services that solve the core challenges of agent deployment:

*The six key challenges that make getting agents to production difficult - from secure execution to monitoring and compliance*

*The seven core components of Amazon Bedrock AgentCore - everything needed to get agents to production*

1. AgentCore Runtime The foundation layer that provides secure, serverless execution environments with complete session isolation. Think of it as AWS Lambda, but specifically designed for the dynamic, long-running nature of AI agents. It supports workloads up to 8 hours—the longest session runtime in the industry for asynchronous workloads.

AWS AgentCore Runtime - Secure, serverless runtime purpose-built for deploying and scaling dynamic agents

2. AgentCore Memory Perhaps the most crucial component, this service manages both short-term conversational memory and long-term knowledge retention. As shown in AWS's demonstration, agents can now "store and retrieve memories with just a few lines of code," enabling persistent learning across sessions.

*AgentCore Memory capabilities - simplified memory management for both short-term conversations and long-term knowledge persistence*

3. AgentCore Identity Enterprise-grade security that enables seamless integration with existing identity providers like Microsoft Entra ID, Amazon Cognito, and Okta. It securely manages API keys and OAuth credentials while providing appropriate authorization across different systems.

*AgentCore Identity provides secure, centralized access management with integration to existing identity providers and third-party services*

4. AgentCore Code Interpreter A secure sandbox environment where agents can execute JavaScript, TypeScript, and Python code. This enables complex data analysis and workflow automation while maintaining security through VM-level isolation.

*AgentCore Code Interpreter enables secure code execution in isolated sandbox environments with support for multiple programming languages*

5. AgentCore Browser Tool A cloud-based browser runtime that allows agents to interact with web applications. It offers sub-second latency and compute-based session isolation, enabling agents to perform complex web tasks securely.

*AgentCore Browser Tool provides fast, secure web interaction capabilities with VM-level isolation and robust audit features*

6. AgentCore Gateway The integration layer that transforms existing APIs, Lambda functions, and services into agent-compatible tools. It supports the Model Context Protocol (MCP) and provides context-aware semantic search for tool discovery.

*AgentCore Gateway simplifies tool integration by automatically converting existing resources into agent-ready tools with just a few lines of code*

7. AgentCore Observability Real-time monitoring and debugging capabilities with OpenTelemetry compatibility. This addresses one of the biggest pain points in agent development—understanding what your agent is actually doing and why.

*AgentCore Observability provides detailed monitoring and debugging capabilities with OpenTelemetry compatibility for enterprise-grade visibility*

Why This Matters: The End of the "Prototype Trap"

The goal for AWS is to leverage Amazon Bedrock AgentCore and its partner ecosystem to enable enterprises to go from experiments to production with AI agents designed to run mission critical business processes. This addresses what industry experts call the "prototype trap"—the gap between impressive demos and systems that can handle real-world enterprise demands.

As demonstrated in the AWS presentation, getting agents to production requires solving those six critical challenges I mentioned above: secure execution and scaling, memory management, identity controls, tool integration, resource discovery, and comprehensive monitoring. AgentCore addresses each of these systematically.

Framework Agnostic = Industry Transformation

One of AgentCore's most significant features is its framework-agnostic approach. It supports any agent framework including popular open source frameworks like CrewAI, LangChain, LlamaIndex, LangGraph, and AWS's own Strands Agents SDK. This means developers aren't locked into a single ecosystem—they can use their preferred tools while gaining enterprise-grade infrastructure.

Real-World Impact: Early Adopters Are Already Seeing Results

The proof is in the early adoption. Early customers in private beta for Amazon Bedrock Agent Core include Autodesk, Cisco and Workday. These aren't small startups experimenting with AI—they're established enterprises with complex, mission-critical requirements.

Itaú Unibanco, one of Latin America's largest banks, is using AgentCore to support "hyper-personalized, secure digital banking experiences." In healthcare, Innovaccer has built a new protocol—HMCP (Healthcare Model Context Protocol)—on top of AgentCore Gateway, demonstrating how the platform enables industry-specific innovations.

The memory management capabilities shown in Figure 4 are particularly crucial for these use cases, as they enable agents to maintain context across banking sessions or medical consultations while ensuring data privacy and security.

So..what’s the impact? Where will this be seen?

Sivasubramanian noted that agents represent "a shift to service as software", fundamentally changing how software interacts with the world. This isn't just about better chatbots—it's about autonomous systems that can:

Replace entire workflow orchestration systems with intelligent agents that adapt to changing conditions (Personally this is the one I’m most focused on!)
Eliminate manual integration work by automatically discovering and connecting to appropriate tools (Hey..this is why we do AI right?)
Provide self-healing operations through agents that can diagnose and resolve issues independently (Scary but cool?)

Pricing That Scales With Success

AgentCore uses entirely consumption-based pricing with no upfront commitments or minimum fees. The service is free to try until September 16, 2025, allowing organizations to experiment without financial risk.

The pricing model reflects the modular nature of the platform:

Runtime, Browser, and Code Interpreter services are priced per second, based on CPU and memory usage
Gateway charges $0.005 per 1,000 tool API invocations
Memory costs are based on data volume: $0.25 per 1,000 short-term memory events

The Future: What's Next for AI Agents with AWS?

AWS also announced updates to the open source SDK Strands Agents, which "makes it dramatically easier to create AI systems where multiple AI agents work together to solve complex problems". This suggests we're moving toward multi-agent systems where specialized agents collaborate to handle increasingly complex tasks.

The introduction of new listings in AWS Marketplace to help businesses find, buy, and deploy AI agents and tools from leading providers indicates the emergence of an agent ecosystem where organizations can discover and deploy specialized agents for specific use cases.

Conclusion: The Agent Revolution is Finally Here? What do you think?

Amazon Bedrock AgentCore represents more than a new AWS service—it's the infrastructure foundation for the next phase of software evolution. By solving the fundamental challenges of agent development, deployment, and operation, AWS has created the conditions for AI agents to finally fulfill their transformative potential. What do you think? Let us know in the comments below!

Note: Amazon Bedrock AgentCore is currently available in preview in US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Frankfurt). To learn more, visit the AgentCore documentation or try the service free until September 16, 2025.

Amazon Bedrock AgentCore: How AWS Just Solved the AI Agent Production Problem