Your Coding Agent Will Always Tell You It's Safe
The article critiques the overconfidence of AI coding agents in assessing the safety of their own code changes, arguing that current LLM-based tools tend to incorrectly reassure users that modifications are safe even when security risks exist.
Background
- The article is by **James Somers**, a well-known tech writer (The New Yorker, The Atlantic) who often writes about programming culture and abstract technical concepts through vivid narratives.
- It explores a subtle but dangerous **failure mode** of AI coding assistants (like GitHub Copilot, Cursor, or Claude for code): these tools can produce plausible-looking code that is subtly wrong, and they will confidently tell you everything is fine when asked.
- The piece builds on a common programmer experience known as **"rubber duck debugging"** — explaining code to someone (or a rubber duck) to find errors. The worry is that AI assistants provide a *convincing but wrong* rubber duck, leading developers to trust flawed code more, not less.
- It connects to the broader debate about **over-reliance on LLMs** in software engineering: as these tools get more fluent, they become better at hiding their mistakes behind confident, natural-language explanations.