Notes on Using LLMs for Code

Simon Willison discusses his experiences using large language models (LLMs) in software development during a podcast episode titled "Supercharging Developer Productivity with ChatGPT and Claude." He describes two primary modes of LLM usage: exploratory and production. In exploratory mode, he utilizes LLMs for quick prototyping, even in unfamiliar programming languages, by asking for various options and creating prototypes based on those suggestions. In production mode, he treats LLMs like a fast intern, iterating on code by requesting specific functions and making adjustments as needed. Willison emphasizes the efficiency of prototyping, noting that LLMs have significantly increased his productivity in this area. He believes that having a working prototype enhances discussions and decision-making in meetings. The conversation also touches on various topics, including the use of AI for coding while multitasking, analyzing complex documents, the evolution of local AI models, and the importance of effective prompting for better AI performance. Overall, Willison highlights the transformative impact of LLMs on his development process and productivity.

- Willison uses LLMs for both exploratory prototyping and production coding.

- He compares LLMs to a fast intern, allowing for rapid iterations and adjustments.

- Prototyping with LLMs has significantly increased his productivity.

- The podcast covers various AI-related topics, including voice interfaces and data extraction.

- Effective prompting is crucial for maximizing LLM performance.