I stopped comparing models months ago. My output improved .

Reddit r/AI_Agents News
workflow-design model-selection ai-usage productivity personal-experience

Summary

The author shares that they stopped comparing AI models and focused on workflow design, leading to improved output. They argue that workflow has more leverage than model choice for most practical use cases.

I used to treat model selection like it was the most important decision in my stack. GPT vs Claude. Claude vs Gemini. Benchmarks, context windows, reasoning scores. just jerking my derk to charts and scores, trying to find the best bang for buck model for my stack. Then I got busy and just picked one and stayed with it. Six months later I genuinely can't tell the difference in my results. What changed my output was how I structured the work around the model, not which model I picked. Also i think i kinda treated oh i need to compare the new stuff as an excuse to not work, so now i get more work done. I'm convinced at this point that workflow design has more leverage than model selection for most practical use cases. Has anyone else landed here or do you still see model choice as a meaningful variable? Also there is no perfect stack or ai model, u gotta compromise somewhere
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