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Safety Testing Sandbox

Introduction to Agent Evaluation

Master systematic evaluation of AI agents to ensure they meet production requirements

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Why Evaluation Matters

You've built an AI agent. It works in your demos. It impresses stakeholders. But is it ready for production? Can it handle real users, edge cases, malicious inputs, and scale? Without systematic evaluation, you're deploying blind. Evaluation is how you know your agent actually works—not just in ideal conditions, but in the messy reality of production.

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The Cost of Skipping Evaluation

Launching agents without rigorous evaluation leads to user frustration, security incidents, cost overruns, and reputational damage. Every production failure that could have been caught in evaluation costs 10-100x more to fix post-launch. Evaluation isn't overhead—it's insurance.

Interactive: Explore Evaluation Dimensions

Click each dimension to understand what to measure and why it matters:

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Evaluation is Continuous

Don't evaluate once and forget. Agent performance degrades over time as data distributions shift, APIs change, and user needs evolve. Set up continuous evaluation pipelines that monitor your agent in production and alert you to regressions before users notice.