Your LLM Doesn't Write Correct Code. It Writes Plausible Code.
Summary
The article argues that LLMs tend to produce plausible but incorrect code and backs this with a benchmark comparing SQLite's correct behavior to a Rust reimplementation that stalls due to two bugs. It analyzes why these errors occur, including debug-path issues and safety-focused design choices, and emphasizes the need for explicit acceptance criteria and rigorous benchmarking when using AI to generate code. It also discusses broader implications for AI-driven development and code review practices.