Impact of LLMs on Programming Language Design

The article discusses the impact of Large Language Models (LLMs) on programming language design, particularly Domain-Specific Languages (DSLs).

The author is concerned that LLMs may reduce interest in DSLs since LLMs can generate code for general-purpose languages like Python, often making DSLs redundant.

It highlights issues with LLMs' performance when handling less common programming languages, which are not well-represented in training data.

The article explores possible ways for language design to evolve alongside LLMs, including teaching LLMs about DSLs through translation techniques, integrating informal and formal code writing, and using specification languages to verify LLM-generated code.

The author identifies opportunities for DSLs to collaborate with LLMs to remain relevant and emphasizes the need for innovation to avoid stagnation in programming language diversity.