AI 辅助调试:解决 SlickGrid 列宽问题
发布:2026年2月9日 00:32
•1分で読める
•Qiita AI
分析
这篇文章展示了 AI 在调试中的实际应用,演示了如何使用 AI 来诊断和解决前端问题。 该过程强调了向 AI 提供更具体的信息以查明根本原因的迭代方法,从而实现成功的解决方案。 这个真实的例子展示了 AI 在简化开发工作流程方面的强大功能。
关于debugging的新闻、研究和更新。由AI引擎自动整理。
"Instead of telling you how our product is differentiated, I am going to tell you how our viewpoint is differentiated - how we think code review will look in the long-term, and what we're doing today to prepare our customers for that future."
"But if I run Codex for the 3rd time on the plan (5.2 High), it seems to always come up with better strategies to implement a feature or fix a bug, for example."
"This is a rapidly evolving field, showcasing the power of human-AI collaboration."
"Now there's a planner → checker → revise loop. Plans don't execute until they pass verification."
"The first coding question relates parsing data, data transformations, getting statistics about the data. The second (ML) coding involves ML concepts, LLMs, and debugging."
"I switched to Codex 5.2 (High Thinking). It fixed all three bugs in one shot."
"Cursor などの AI Agent が使える IDE だけで、MagicPod の失敗テストについて 原因調査を行うシンプルな方法 を紹介します。"