Less than two months ago, US forces seized Venezuelan leader Nicolás Maduro, Cuba's close ally, and stopped his successor from supplying the country with oil.
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In practice, (and yes, there are always exceptions to be found) BYOB is rarely used to any measurable benefit. The API is substantially more complex than default reads, requiring a separate reader type (ReadableStreamBYOBReader) and other specialized classes (e.g. ReadableStreamBYOBRequest), careful buffer lifecycle management, and understanding of ArrayBuffer detachment semantics. When you pass a buffer to a BYOB read, the buffer becomes detached — transferred to the stream — and you get back a different view over potentially different memory. This transfer-based model is error-prone and confusing:
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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.
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