Can LLMs Save Niche Programming Languages? Elixir's Strategy

The rise of Large Language Models (LLMs) has sparked concerns among developers about their impact on niche programming languages. This article uses Elixir as a case study to explore how LLMs affect programming languages and how to leverage LLMs to enhance the competitiveness of niche languages. The author argues that LLM biases might lead to a preference for mainstream tech stacks, but by improving the interaction between LLMs and niche languages—such as providing better documentation and LLM-optimized code examples—LLMs can better understand and utilize niche languages. Furthermore, building evaluation datasets for niche languages can improve LLM proficiency, leading to recommendations for niche languages in suitable scenarios. Ultimately, the author suggests that actively embracing and utilizing LLMs, rather than passively resisting them, is key to the survival of niche programming languages in the AI era.