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.
比如，和誉医药的第二代FGFR小分子抑制剂ABSK061，在降低对FGFR1抑制的同时，保持对FGFR2/3高选择性，理论上安全性更高。在动物模型中，ABSK061的表现优于Infigratinib，目前ABSK061治疗3-12岁ACH儿童患者的2期临床正在进行中。
，这一点在同城约会中也有详细论述
Цены на нефть взлетели до максимума за полгода17:55
Claude Code 将自动分析需求，调用 frontend-design 技能库中的设计模式，生成结构化的代码。
The important thing isn’t which tool you pick. It’s the pattern. Store secrets in a vault, inject at runtime, never write plaintext to disk.