Understand agent benchmark before you buy the score.
These guides are intentionally opinionated. They connect public benchmark language to the real question: can your agent complete delegated work safely and repeatably?
Benchmarking Real Work Case 2: Why Good Agent Evaluation Wasn't Enough for Production
A real-world agent evaluation case study: a dialect interview workflow passed a real-data benchmark, then failed in volunteer operations until it was embedded into the existing Feishu workflow.
Benchmarking Real Work - Case 01: How I Built a Voice Agent Benchmark from Real Customer Failures
A real-world voice agent benchmark case study: turn customer failures into repeatable evaluations, improve speaker identification, and uncover sampling bias.
How to Evaluate AI Agent with Benchmark in Practice?
Before spending on evaluation, decide whether the agent's work is worth evaluating, how much to invest, and how to start from real workflow data.
Why AI Agent Benchmark Matters
AI agent benchmark matters because agents are moving into real work. The question is no longer only whether they can do the job, but whether the work can be trusted.