How I automate agent evals starter kit for AI agent workflows

Evaluating AI Agents: A Developer's Starter Kit The Problem Developers Face As developers, we’re increasingly integrating AI agents into our workflows, whether for automating tasks, building conversational bots, or creating intelligent systems. But here’s the catch: once you’ve built an AI agent, how do you know it’s actually working as intended? Sure, it might generate responses or complete tasks, but is it doing so reliably, accurately, and in a way that aligns with your goals? Evaluating AI agents is a nuanced challenge that goes beyond simple unit tests or manual spot-checking. The problem gets even trickier when you’re dealing with large language models like OpenAI’s GPT or Anthropic’s Claude. These models are probabilistic, meaning their outputs can vary even with the same input. How do you measure performance across different scenarios? How do you identify edge cases? And how do you ensure your agent is improving over time? Without a structured evaluation process, you’re left gu