Data Snack - Making the Most of Large Language Models in Scientific Programming

This piece focuses on the use of Large Language Models (LLMs) in coding workflows, though many of the insights are valuable for anyone interested in applying LLMs in scientific research. Whether you're just starting out or already comfortable writing code, LLMs can assist with generating, debugging, and improving code. But using them effectively requires more than just copying suggestions. The content helps unpack how these models work, where they excel, where caution is needed – and why LLMs are fundamentally changing scientific programming across disciplines. It offers a practical look at what LLMs can (and can't) do, how to craft better prompts for coding support, and what it means to use them responsibly in research. Additional snack-sized insights into big AI questions include choosing the right model or feature, and ensuring data security and privacy.