a16z的报告里举了几个例子，把这个问题讲得很具体。投行分析师用Hebbia，几百份公开文件自动分析完，财务模型直接生成，以前要熬几个通宵做的事情，现在可以去睡觉了。医生用Abridge，它能实时记录医患对话，自动整理病历和后续跟进事项，医生看诊时不用再一边问话一边盯着屏幕敲字。还有做财务对账的Basis，跨系统自动核对试算表，原本需要人工反复比对的工作变成几分钟的事。
There’s a secondary pro and con to this pipeline: since the code is compiled, it avoids having to specify as many dependencies in Python itself; in this package’s case, Pillow for image manipulation in Python is optional and the Python package won’t break if Pillow changes its API. The con is that compiling the Rust code into Python wheels is difficult to automate especially for multiple OS targets: fortunately, GitHub provides runner VMs for this pipeline and a little bit of back-and-forth with Opus 4.5 created a GitHub Workflow which runs the build for all target OSes on publish, so there’s no extra effort needed on my end.
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This has been a glorious year for bookworms. The quantity and quality of Stuff Your Kindle Days has been unprecedented, and the schedule is showing no signs of slowing down. We've got two events on the calendar for this week, but for now, the focus is firmly on the Sapphic Shelf Explosion.