Ai-Tools

Most people who use more than one frontier model eventually learn that models have different task strengths. One model is better for fast edits. Another is better for long-form reasoning. Another is better for exhaustive review. That part is not especially surprising anymore.

What I wanted to test was more specific: whether those differences could be described as personality. Not personality in the human sense, but a repeatable instinct that shows up across tasks. If that instinct can be named, tested, and connected to failure modes, then model selection becomes less vibes-based.

Give three frontier models the same prompt, and you’ll get three distinct interpretations of what “good” means. I discovered this gradually, over months of working with AI coding assistants on real projects.

Early on, I’d occasionally switch models mid-task, sometimes because I was curious and sometimes because I wanted a second opinion on a tricky problem. I’d notice changes in the outputs, but I couldn’t pin down what was driving them. Was it my prompt? The task itself? The model? Some combination of all three? The variables were tangled together, and I wasn’t being rigorous enough to isolate them.