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Stop Using Your Smartest AI Model for Everything: A Practical Workflow That Saves Time and Tokens
The Mistake I Didn’t Realise I Was Making For a long time, I thought I was being efficient. Whenever I opened my GitHub Copilot, I instinctively selected the most capable model available. It didn’t ma
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Ahmet Özel
AI Engineer. Computer Vision, RAG and LLM agents.
Model selection should be driven by task risk and acceptance criteria, not perceived intelligence alone. A useful routing policy records the task class, latency budget, expected output schema, and fallback. Then the team can compare accepted quality and total retry cost rather than choosing models by anecdote.