AWS AI Agent Builder: New Capabilities Announced

AWS Enhances AI Agent Platform, Amazon Bedrock AgentCore

Amazon Web Services (AWS) is significantly expanding its AI agent platform, Amazon Bedrock AgentCore, with the goal of simplifying the creation and oversight of AI agents for businesses.

New Features Unveiled at re:Invent

Several new features for AgentCore were revealed by AWS on Tuesday during its annual AWS re:Invent conference. These enhancements focus on managing agent boundaries, improving agent memory, and providing robust agent evaluation tools.

Introducing Policy for Controlled Interactions

A key upgrade is the introduction of Policy within AgentCore. This functionality enables users to define interaction limits for agents using natural language.

These boundaries work in conjunction with AgentCore Gateway, which facilitates connections between AI agents and external tools, to automatically validate each agent's actions and prevent those that breach established controls.

Granular Access Control

Policy allows developers to establish access controls to sensitive internal data or integrate with third-party applications such as Salesforce or Slack.

For example, an AI agent could be authorized to automatically process refunds up to $100, while requests exceeding that amount would require human intervention, as explained by David Richardson, vice president of AgentCore, to TechCrunch.

AgentCore Evaluations for Performance Monitoring

AWS also announced AgentCore Evaluations, a comprehensive suite of 13 pre-configured evaluation systems. These systems monitor critical agent performance indicators, including accuracy, safety, and the effectiveness of tool selection.

This provides developers with a strong foundation for building customized evaluation features.

Addressing Deployment Concerns

“This feature will significantly alleviate the primary concerns associated with deploying agents,” Richardson stated, emphasizing the time-consuming nature of building such evaluation systems from scratch.

AgentCore Memory: Building Agent Understanding

Furthermore, AWS is integrating a memory function into the platform, known as AgentCore Memory. This allows agents to accumulate information about users over time – such as flight details or hotel preferences – and leverage this data to enhance future decision-making.

Continuous Iteration and Future-Proofing

“With these three advancements, we are consistently refining the various layers of AgentCore,” Richardson explained. “This includes secure interaction with existing systems via Policy, increased agent capabilities through AgentCore Memory, and streamlined development iteration.”

The Longevity of AI Agents

Despite some skepticism regarding the long-term viability of AI agents, Richardson believes the tools AgentCore is developing are resilient to market fluctuations and evolving trends.

“The ability to harness the reasoning power of these models, combined with the capacity to execute real-world tasks through tools, represents a sustainable approach,” Richardson noted. “The specific implementation of this approach will undoubtedly evolve, and we are prepared for those changes.”

Stay informed with TechCrunch’s complete coverage of the annual enterprise tech event here.

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