Choosing an AI Coding Assistant: From "Who's the Strongest" to a Quantifiable Evaluation

Every AI coding tool comparison ends in an uninformative “it depends.” That is not because the industry lacks benchmarks. The real problem is that “which tool is strongest” is not an answerable question. Model capability, interaction modality and context engineering are three independent variables, and maxing out any one of them does not automatically improve end-to-end efficiency. This article reframes the choice as a measurable engineering problem: break tasks into four tiers, evaluate tools along five dimensions, build a small reproducible benchmark from your own Git history in two weeks, model effective delivery cost instead of token prices, and roll out in phases with the governance rules that team-scale adoption requires.