Amazon Web Services just dropped three major upgrades to its AI agent building platform that could change how enterprises deploy autonomous AI systems. The company announced AgentCore Policy, Memory, and Evaluations features at re:Invent 2025, addressing the biggest barriers stopping businesses from trusting AI agents with real work.
Amazon Web Services is making a bold bet that AI agents are here to stay, and the company's latest AgentCore updates prove it's dead serious about enterprise adoption. The cloud giant just unveiled three game-changing features at re:Invent 2025 that tackle the biggest fears keeping businesses from deploying autonomous AI systems.
The most significant addition is Policy in AgentCore - a safety mechanism that lets developers set boundaries using plain English rather than complex code. Think of it as training wheels for AI agents operating in the real world. The feature integrates directly with AgentCore Gateway to automatically block any action that violates pre-written controls, creating an automated safety net that enterprise IT teams desperately need.
"Policy allows developers to set access controls to certain internal data or third-party applications like Salesforce or Slack," David Richardson, vice president of AgentCore, told TechCrunch. The practical applications are immediately clear - an AI customer service agent could automatically process refunds up to $100 but must loop in humans for anything larger.
The timing couldn't be better for AWS. While competitors like Microsoft and Google focus on flashy AI demos, Amazon's cloud division is solving the unsexy but crucial problems that actually prevent enterprise deployment. The company's pragmatic approach reflects years of enterprise feedback about AI safety and control mechanisms.
AgentCore Evaluations represents another major leap forward, offering 13 pre-built monitoring systems that track everything from correctness to safety to tool selection accuracy. "That one is really going to help address the biggest fears that people have deploying agents," Richardson explained. "It's a thing that a lot of people want to have but is tedious to build."
The evaluation suite addresses a critical gap in the AI agent ecosystem. While building an AI agent has become relatively straightforward, monitoring its performance and ensuring it doesn't go rogue remains incredibly complex. is essentially providing the enterprise-grade monitoring tools that most companies lack the resources to develop internally.
