Meituan starts an Agent evaluation whitepaper series

On October 3, 2026, Meituan's tech team published an introductory explainer on evaluating AI agents, written to build up from the basics. According to the team, the first two chapters cover what evaluation is and how to set up an evaluation system. The second chapter draws on hands-on experience gathered by the Meituan Turing Agent evaluation team, which worked alongside business teams across the company; the team describes that knowledge as something refined over two years of practice.

Later the same morning, the team launched an Agent evaluation whitepaper series of blog posts, pitched as a structured guide to putting evaluation into production. It is aimed at teams that need to build an agent evaluation system, and is split into four parts: an overview, cold start, scaling up, and self-evolution. The post published that day was the first in the series, the overview.

Both items came from the Meituan tech team, posted at 10:26 and 11:10. Beyond that, the sources give no further detail, such as when the remaining parts will appear or which metrics and tooling the evaluation covers. The matter currently stands at the first overview post being out, with the other three parts not yet accounted for.