AI Reasoning Workflows – The 6 Skills That Improve Model Output

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I’ve been experimenting with a simple idea: most AI performance problems are not model limitations, but task specification limitations.Over the past months I’ve tested a set of reasoning workflows that significantly improve output quality for both small and large models. They’re not about “prompt tricks” — they’re about structuring a task so the model can reason cleanly.Here are the 6 core skills that consistently make the biggest difference:1. *Decomposition* – splitting a vague task into constraints, context, steps, assumptions. 2. *Constraint stacking* – defining what must be true and what must not happen. 3. *Reasoning path control* – explicit “think aloud but check your assumptions” ste

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Website: dailyaiguide.substack.com/p/ai-reasoning-workflows-t...If