A year ago I spent an embarrassing amount of time comparing models. GPT vs Claude. Claude vs Gemini. Gemini vs open-source. Context windows, benchmarks, reasoning scores, latency comparisons. I treated model selection like it was the most important decision in the entire stack. Lately I'm starting to think I had it backwards. I've watched teams get incredible results from models that weren't considered "the best," while other teams struggle despite having access to state-of...