Don't Force Your LLM to Write Terse [Q/Kdb] Code: An Information Theory Argument
Published:Oct 13, 2025 12:44
•1 min read
•Hacker News
Analysis
The article likely discusses the limitations of using Large Language Models (LLMs) to generate highly concise code, specifically in the context of the Q/Kdb programming language. It probably argues that forcing LLMs to produce such code might lead to information loss or reduced code quality, drawing on principles from information theory. The Hacker News source suggests a technical audience and a focus on practical implications for developers.
Key Takeaways
- •LLMs may struggle with generating highly terse code due to information loss.
- •Information theory provides a useful framework for analyzing code conciseness.
- •Developers should consider the trade-offs between code brevity and readability when using LLMs.
Reference
“The article's core argument likely revolves around the idea that highly optimized, terse code, while efficient, can obscure the underlying logic and make it harder for LLMs to accurately capture and reproduce the intended functionality. Information theory provides a framework for understanding the trade-off between code conciseness and information content.”