Prevent cognitive debt by manually retyping LLM-generated code (ankursethi.com)

A developer shares their ongoing experience with coding assistants, expressing a blend of appreciation and concern over the cognitive debt associated with using large language models (LLMs) for code generation. While LLMs accelerate the coding process by handling tedious tasks, the author emphasizes the importance of understanding the code by manually retyping it instead of solely relying on AI-generated outputs. This method not only helps them build a mental map of the codebase but also aids in identifying potential errors and enhancing the quality of the code. This approach reinforces a significant debate in the AI/ML community regarding the balance between efficiency and understanding. By prioritizing comprehension over speed, the developer warns against a future where programmers could become disconnected from their work, emphasizing the risk of losing foundational knowledge about the software we build. Their solution showcases a personal commitment to maintaining control over their projects and skills, suggesting that manual involvement in code generation can be a valuable learning process amid an increasingly automated landscape.