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Net international migration to the U.S. peaked at 2.7 million new entries in 2024, but has since sharply declined. It fell to 1.3 million last summer, according to January Census data, and then turned net negative, according to research from Brookings, meaning more people are leaving the U.S. than coming in. The private sector has weighed in, too, with Goldman Sachs economists reporting last week that immigration policies put in place over the past year have resulted in an 80% decline in net migration relative to the historical average.
In the months since, I continued my real-life work as a Data Scientist while keeping up-to-date on the latest LLMs popping up on OpenRouter. In August, Google announced the release of their Nano Banana generative image AI with a corresponding API that’s difficult to use, so I open-sourced the gemimg Python package that serves as an API wrapper. It’s not a thrilling project: there’s little room or need for creative implementation and my satisfaction with it was the net present value with what it enabled rather than writing the tool itself. Therefore as an experiment, I plopped the feature-complete code into various up-and-coming LLMs on OpenRouter and prompted the models to identify and fix any issues with the Python code: if it failed, it’s a good test for the current capabilities of LLMs, if it succeeded, then it’s a software quality increase for potential users of the package and I have no moral objection to it. The LLMs actually were helpful: in addition to adding good function docstrings and type hints, it identified more Pythonic implementations of various code blocks.
Publication date: 28 February 2026