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Prompting Reasoning Models: Why Old Prompt Tricks Now Backfire

Originally published on AI Tech Connect.

What you need to know For five years, prompt engineering was the art of compensating for models that could not plan. You said "think step by step" because otherwise they would not. You wrote numbered procedures because the model would not decompose the problem itself. You stacked few-shot examples to teach a format, and added "be concise" because verbosity was the default failure mode. Every trick was a workaround for a missing capability — and as of July 2026, the capability is no longer missing. Anthropic's Claude models ship with extended thinking (and, on the newest models, adaptive thinking that decides for itself when to deliberate); OpenAI's GPT-5-family reasoning models, descendants of the o-series, expose a reasoning_effort dial; Google's Gemini models think dynamically by…


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