提出带时间戳的调试日志与排查流程解决 Agent 查 Bug 难

On 2026-11-13 at 11:36, Juejin published the article "What to Do When Agents Cannot Find Bugs: Timestamped Debug Logs and a Troubleshooting Workflow." The piece addresses a recurring pain point in which AI Agents struggle to locate bugs in code on their own. Its core argument is that agents usually fail because they lack access to the actual runtime scene, and that this gap can be filled with a structured logging approach.

The proposed solution is a three-part logging set that combines millisecond-level timestamps, trace_id, and data snapshots, so that the key events of an Agent run can be reconstructed after the fact. Building on that log format, the article lays out a fixed, repeatable order for reading logs during troubleshooting, rather than leaving the review process unstructured. It also ships a ready-to-run instrumentation template, which is meant to let readers adopt the same logging scheme and debugging workflow in their own codebases without building the setup from scratch.

At this point, the available coverage only records the article that introduced the idea. There is no further reporting on real-world adoption of the logging set or the workflow, and no published disagreement among different parties about the approach.