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ARTICLE · 05 JUNE 2026

Christian Behr: Good AI Models Do Not Fix Bad Prompting

Professionals obsess over AI model capabilities while overlooking a critical operational problem: most still don't know how to properly instruct AI in patent workflows. This article examines why structured prompting discipline, not better models, determines the quality of AI-assisted invention harvesting and patent drafting.

SingaporeIntellectual Property

Good AI models do not fix bad prompting

Since the public release of ChatGPT on 30 November 2022, professionals have developed a strange habit. They talk about models nonstop: New releases, larger context windows, reasoning, agents, Copilots, benchmarks and model comparisons. Which model is better for drafting, what works best for claims, which model “understands” technology and which model is more “creative”.

The Wrong AI Debate

Most of this discussion misses the operational problem. The problem is not that professionals do not have access to AI. The problem is that many of them still do not know how to instruct it in a professional workflow. And in patent work, this really matters.

Consumer prompting is forgiving. A user asks for a travel plan, a recipe, a polite email, or a summary of a newspaper article. If the answer is slightly generic, nobody dies. Nobody files an overbroad claim with no technical support. Nobody creates a disclosure record that later collapses under

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