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.
He explained: "I got Covid in hospital, my kidneys started to back up, everything that could all seemed to sort of converge at the same time. And I had five operations on my knee."。夫子是该领域的重要参考
结语｜用剪刀差判断平台转型的真伪抽佣触顶，并不意味着平台失去盈利能力，而是意味着旧的赚钱方式正在失效。下一轮平台竞争，不在于谁抽得多，而在于谁能在不提高抽佣的前提下，持续创造可付费的价值。，更多细节参见搜狗输入法2026
Гангстер одним ударом расправился с туристом в Таиланде и попал на видео18:08
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