Many developers swing between seeing AI coding assistants as all-powerful or hopelessly unreliable. In practice these tools excel at small, well-specified tasks and struggle with vague, complex ones. The way to get consistent quality is a three-step loop: decompose features into verifiable units, run tests before merging anything, and keep humans in charge of architecture and safety-critical decisions. This article is compiled from publicly available industry information and engineering practice.
AI programming