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Insights
Practical ideas on AI, project governance, and digital execution. Read, reflect, and put them to work.
4 insights · Newest first

In my recent AI in Project Management articles, I have explored how project managers can use structured prompts to analyze RFPs, develop Project Management Plans, and turn plans into executable work.
But why does prompt structure matter?
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“AI image generation is powerful, but how can we generate images with a consistent style?”
This is actually a common challenge many companies face when using AI image generation.
The longer the Prompt, the more likely the result is to drift away.
The real key is not to make the Prompt longer, but to frame the image generation requirements more precisely.
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Many people think AI gives weak answers because the prompt is not clever enough.
But in practice, the bigger issue is often this: AI does not have enough context.
A prompt tells AI what to do. Context tells AI what situation to base its judgment on.
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Stakeholders often come to PMs with a solution already in mind. At first glance, the requirement looks clear. But there are usually hidden assumptions behind those solutions. This article tells you how PMs can use 3 prompt templates to reveal hidden assumptions before writing specs. Because PMs do not only make requirements clear. A more important part of the PM’s job is to make sure the team is not spending effort on the wrong problem.
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