Once you’ve learned the basics of prompt engineering, it is easy to take it one step further. Clear, specific prompts are a great starting point, but there’s even more power available when you start shaping how the AI thinks, not just what it says. That’s where advanced techniques come in.
Whether you’re writing proposals, generating summaries, or exploring how AI can fit into your workflows, these strategies can help you get sharper, more relevant results, without a lot of trial and error.
Guide the AI with a System Message
One of the easiest ways to get better results is to define the role or behavior of the AI before you give it a task. This is done with something called a system message. It tells the AI how to act, what kind of tone to use, and what style to follow.
For example:
You are a professional business writer. Use a formal tone and structure your answers with bullet points. Avoid casual language.
This type of instruction works best when you’re building reusable prompts or templates for specific business functions. Setting expectations up front helps you get more consistent and intentional results, especially when tone and format really matter.
Be Specific About the Role
In addition to the system message, you can shape the output by telling the model who it is supposed to be at that moment. This is called role prompting, and it adds helpful context about the audience and purpose.
Here’s an example:
Instead of saying, “Summarize this document,” you could say, “You are a communications lead summarizing this internal memo for senior leadership. Include only the essential updates and action items.”
This gives the model a clear perspective to write from, which usually leads to stronger, more focused responses.
Learn How Different Models Respond
As you use AI more often, you’ll notice that not every model handles prompts the same way. Some are more literal. Others are more conversational. Some are better at following complex instructions, while others do better with open-ended brainstorming.
Here’s a quick way to think about it:
- ChatGPT often works best for polished, structured writing and business documentation
- Claude is strong at retaining context and providing thoughtful, longer responses
- Gemini handles reasoning well and gives more flexible outputs
If a prompt isn’t working quite right, try it on a different model. Sometimes just switching tools makes all the difference.
Tailor Prompts to the Task
One of the most common mistakes people make as they get more comfortable with prompt engineering is assuming one prompt fits every situation. In reality, the best prompts are shaped for the task at hand.
Here are a few quick examples:
For summarizing:
“Summarize this meeting in three bullet points so a VP can scan it in under a minute.”
For transforming tone:
“Rewrite this email for a broader, non-technical audience. Keep it friendly and under 150 words.”
For creative brainstorming:
“You are a marketing lead coming up with taglines for a new AI-powered analytics tool. Share five ideas with short notes on why each one works.”
The more you customize the prompt for the outcome you want, the better the results.
Making AI Work for You
Mastering these techniques takes some practice, but once they click, you’ll wonder how you ever worked without them. Whether you’re refining reports, building internal tools, or just trying to get clearer results faster, advanced prompt engineering can make AI feel a lot more like a real teammate. If you’re looking to explore what that could look like inside your business, the team at 7Rivers is here to help.
