Uncovering LLM Blind Spots in AI Coding: Common Pitfalls and Solutions
Large language models often struggle with coding tasks, failing to stop when encountering obstacles, ignoring black‑box testing principles, and making unnecessary refactors; this article examines those blind spots, offers practical examples, and suggests strategies such as preparatory refactoring, stateless tools, and careful prompting to improve AI‑assisted development.
