A three-case acceptance test for multi-turn AI agent tasks

On October 27, 2026, an author writing under the name Xiaohu, who describes himself as holding a bachelor's and a master's degree in computer science from Zhejiang University, published an article titled "How to Acceptance-Test an AI Agent on Cross-Turn Tasks: 3 Test Cases" on Juejin. According to the article, Ant Group's Lingguang 2.0 has opened a limited internal beta, with a full rollout planned for October 2026, and its official positioning has shifted from a "chat companion plus app builder" to a "personal agent with long-term memory that can proactively drive tasks forward." The piece also mentions Tencent LightVela, Alibaba's Qwen Go!

, ByteDance Doubao Spell, and Meta Muse as competing for the same position in this space. The author, who describes running AI training and enterprise efficiency advisory work, says that many solo-business owners fill their phones with tools such as Doubao and Tencent Yuanbao yet still have to copy and paste back and forth among five admin dashboards every morning, which frames the problem the article tries to address. Rather than evaluating products on launch-event messaging, the article offers a reproducible acceptance method: split a single cross-turn, cross-tool office task into three questions, hand them sequentially to any candidate agent, and observe whether the system behaves like an accountable assistant or merely a chat window with a new skin. The author states that readers will take away three things: three test cases that can be copied directly, a selection-judgment table for choosing within a walled ecosystem, and a reusable task-delegation brief template. As of now this is the only available report on the proposal, the method has not been independently verified by any other source, and the full content of the three test cases is not given in the material.