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GPT-5.3 Instant 显著降低幻觉率，意味着 Agent 在自主执行任务时少犯错；「AI 腔」的消退，意味着生成的邮件、文档读起来更贴合真人的阅读习惯。
。17c 一起草官网对此有专业解读
The developer hasn’t made a mistake when these happen, and there’s often little they can do to prevent it. The existence of these errors is not a bug (though failing to handle them can be). These aren’t the programmer’s fault.。关于这个话题，PDF资料提供了深入分析
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Around this time, my coworkers were pushing GitHub Copilot within Visual Studio Code as a coding aid, particularly around then-new Claude Sonnet 4.5. For my data science work, Sonnet 4.5 in Copilot was not helpful and tended to create overly verbose Jupyter Notebooks so I was not impressed. However, in November, Google then released Nano Banana Pro which necessitated an immediate update to gemimg for compatibility with the model. After experimenting with Nano Banana Pro, I discovered that the model can create images with arbitrary grids (e.g. 2x2, 3x2) as an extremely practical workflow, so I quickly wrote a spec to implement support and also slice each subimage out of it to save individually. I knew this workflow is relatively simple-but-tedious to implement using Pillow shenanigans, so I felt safe enough to ask Copilot to Create a grid.py file that implements the Grid class as described in issue #15, and it did just that although with some errors in areas not mentioned in the spec (e.g. mixing row/column order) but they were easily fixed with more specific prompting. Even accounting for handling errors, that’s enough of a material productivity gain to be more optimistic of agent capabilities, but not nearly enough to become an AI hypester.