AgentCore Evaluations: How AWS Built a Framework-Agnostic Eval Layer Using OpenT

In this post, we introduce Amazon Bedrock AgentCore Evaluations, a fully managed service for assessing AI agent performance across the development lifecycle. We walk through how

Multi-agent systems need deeper guarantees than fluent responses: they must select the right tools, respect constraints, and explain their decisions. Learn how to build a

<p><em>How a two-week evaluation design sprint almost ended with us switching tools entirely — and what we learned from not doing that.</em></p> <p>There’s a particular kind of

This post combines learnings from LangChain’s work on evaluating deep agents and Anthropic’s guide to demystifying evals for AI agents into a practical guide. In this post, you

<p>Let me be brutally honest with you.</p> <p>I've seen teams demo AI agents that look incredible — smooth responses, beautiful UI, stakeholders impressed. Then that same team

<p>I still remember the exact moment.</p> <p>It was 11pm. My team had been sprinting for 3 weeks building <br /> a new payments feature. Deadline tomorrow. I handed the final <br

<!-- SC_OFF --><div class="md"><p>I am curious how non-coders are currently using frontier ai models and capabilities. Specifically in technical fields.</p> <p>I am a mechanical

<p>How it works:</p> <p>Request arrives at an OpenAI-compatible endpoint<br /> Classifier detects task type + complexity<br /> Adaptive router picks the highest-scoring model for