I'm sure it's happened to you: you write a prompt that works perfectly in one AI... and when you copy it to another, the result is completely different. Vague, overly long, non-technical, or simply irrelevant responses.
And then you think: Aren't all AIs supposed to work the same way?
The short answer is no. The long answer, we'll tell you here.
Why the same prompt doesn't work the same way in all AIs
Although they may appear similar on the outside, Each AI is trained differently, with different objectives and behaviors. Some prioritize creativity, others precision, others synthesis or the search for sources.
This means that:
- They interpret the context differently
- They respond with different levels of detail
- They follow (or ignore) certain instructions
So reusing a prompt without adapting it is like using the same experimental protocol in completely different contexts. Sometimes it works. Many other times, it doesn't.
What elements of the prompt typically vary between AIs?
When you switch AI, there are parts of the prompt that you absolutely must review:
Level of detail
Some AIs tend to overextend themselves if you don't set clear limits. Others do just the opposite.
Following instructions
Some models follow step-by-step instructions very well, while others need more explicit reminders.
Tone and style
The same prompt can generate a general response in one AI and an overly technical one in another.
Use of context
Some people quickly "forget" the context if you don't reinforce it. Others retain it better throughout the conversation.
How to adapt a prompt according to AI step by step
There's no need to reinvent the prompt from scratch. These settings are usually sufficient:
- Start simple: Try the original prompt as is and see what fails.
- Adjust the level of detail: Add phrases like “be concise”, “use examples” or “limit your answer to X points”.
- Reinforce the context: If you see generic answers, add what you need the information for and in what area.
- Control the format: Specify if you want lists, steps, tables, or continuous text.
- Iterate without fear: Changing just one sentence can greatly improve the result.
Common mistakes when reusing prompts in different IAS
Here are some very common mistakes:
- Copying and pasting prompts without checking
- Assuming that all AIs understand instructions in the same way
- Failure to adapt the technical level
- Asking for too many things at once
- Do not correct the prompt after a bad response.
The key is to remember that The prompt is not universal, It's contextual.
Practical example of adapting the same prompt
- Original Prompt"Summarize this scientific article, highlighting the key points." Result in one AI: too long. Result in another: too superficial.
- Adaptation 1"Summarize this scientific article in 5 points, using clear and technical language."“
- Adaptation 2"Summarize this scientific article, highlighting its objective, methodology, and conclusions, in list format."“
Same idea, but tailored to the behavior of each AI. The content improves without changing the tool.
Learn to adapt prompts
Changing a prompt based on AI isn't pure intuition. It's a skill that is learnedWe observe, adjust, and refine. You can learn to adapt your questions with this. prompt engineering course.
Because in the end, It's not just about what questions you ask., but of who do you ask and how. And mastering that is what makes AI a true ally. And hey, if it's going to be another tool for you, you might as well get to know it well, right?
Biotechnologist and biostatistician specializing in data analysis and artificial intelligence applied to research. Founder of Maxymia, combines science and technology to develop solutions and training in automation for the scientific field.
