I'm telling you that learning sales is hard for an academic entrepreneur like me. We don't like to ask people for their money and it's not like many of us are in well-paying jobs either. But we all understand value.
So, my goal is to make my upcoming Masterclass "The AI-Powered UX Designer: A 3-Hour Masterclass That Lets You Charge 50% More," the most valuable purchase that anyone interested in AI can make. Yes, its primary audience are designers, but we'll deliver AI tools and prompts that anyone can use. And I'm throwing in lots of useful prompts for researchers doing qualitative analysis. This also meant changing the pricing structure. Just one honest price that'll be a fraction of the value we'll deliver. No more underselling myself at a 50% discount. Instead adding a money-back guarantee, a massive prompt pack, and AI ideation workflows. And we are working on even more content to deliver with the Masterclass. After doing all that, I'm excited about running this live Masterclass. And we decided on a hard cutoff at 20 people. We want to best quality for the people that attend, which means, we'll only take a small cohort. And to top it all off, we're running a couple of free webinars to give you a taste of things to come. Enjoy today's article.
It was another afternoon in my university office. I was hunched over my laptop, surrounded by textbooks and empty coffee cups. I could just feel the concerned glances of Twitter influencers that made using AI look easy as I stared at my screen with the vacant expression of someone who has been debugging code for six hours straight.
Another AI response, another letdown. I was frustrated. I was typing crap like “make this paragraph sound better” into the prompt box for what felt like the hundredth time, hoping for this flint and tinder to light the productivity fire everyone was promising. Instead, I received output that read like a first-year student's rushed assignment. No thank you, ChattieG. You tried.
My realization came between my third and fourth skinny Latté. The AI was not the issue - my approach was. I had been treating it like some omniscient academic advisor, throwing vague requests into the void and expecting detailed, perfectly tailored responses. The classic computer science principle of garbage in, garbage out suddenly felt very personal. My imprecise inputs were leading directly to unfocused outputs. It was time to become more structured.
The 10 Rules
So I started treating my prompts like I was writing instructions for an undergrad research assistant. Specific. Clear. Detailed. No room for artistic interpretation. And here are the 10 rules, I recommend to follow for better results:
Recording of our free webinar: The 10 Commandments of AI Prompting
1. Embrace Specificity
If your prompt could apply to a thousand different situations, it’s probably not going to give you a good result. Don’t say: "Review this research paper." Instead, say:
"Review this psychology paper’s methodology section. Focus on the experimental design, participant sampling method, and whether the statistical tests chosen are appropriate for testing the stated hypotheses."
The more precise your input, the better the output.
2. Break Down Complex Tasks Into Steps
Don’t dump a 10-step job on it at once. Break it up.
Start with: “Generate 10 open-ended interview questions about daily productivity habits.”
Then: “Based on these transcripts, identify recurring themes in user frustrations.”
Finally: “Summarize the top 5 pain points users experience with task management apps.”
Micro-prompts = macro clarity.
3. Context Is King
Give the AI a sense of the big picture. Who are you? What are you working on? Why does it matter?
Example:
"I’m a doctoral candidate in educational psychology studying digital literacy interventions. Help me code qualitative data from 30 teacher interviews about technology adoption barriers."
Now your AI has a mental map. Expect better results.
4. Eliminate Ambiguity
Words like “improve,” “enhance,” or “optimize” are death traps. They mean everything and nothing.
Instead of: “Make this better” Try:
"Restructure this literature review to follow APA 7th edition standards with clear topic sentences and logical flow between paragraphs"
Be crystal clear about what you want. Otherwise, you’ll get mush.
5. Set Clear Goals
Always say what you’re trying to accomplish. Instead of just asking for ideas, tell the AI what kind of output you need and why.
"Generate 12 semi-structured interview questions to explore faculty experiences with remote teaching technologies, focusing on pedagogical challenges and institutional support needs."
Let the AI know where the finish line is.
6. Prompt for the Right Audience
The AI isn’t reading your mind. Tell it who you’re prompting for.
Prompt A: “Explain data encryption.”
Prompt B: “Explain data encryption to a high school student who uses Snapchat but doesn’t trust big tech.”
Big difference.
7. Provide Examples
If you want your AI output to sound a certain way or follow a particular structure, show it the way.
“Here’s an example of the tone I like: ‘Think of this as your brain’s inbox. We’re just helping you sort through it.’ Now write a similar line for a focus timer feature.”
Monkey see, monkey do.
8. Embrace the Feedback Loop
Your first prompt won’t be perfect. That’s okay.
Think of AI as a collaborator. Ask. Read. Revise. Ask again.
“That’s close. Now try making it more playful.”
“That’s good. Now shorten it to under 10 words.”
Iteration is how good becomes great.
9. Use Multi-Shot Prompting
Don’t stop at one.
Prompt the AI with a few variations of what you want:
First: Extract themes → Second: Define each theme → Third: Find supporting quotes → Fourth: Create thematic map with relationships.
The AI can compare, contrast, and improve if you feed it multiple data points.
10. Keep It Simple
Big words don’t make you sound smarter. They make your prompt harder to interpret.
"Analyze participant responses for recurring themes related to technology acceptance"
That’s it. No MBA jargon. No academese. Just plain, human talk.
Wrap Up
These rules work because they treat AI as a collaborative partner, not a magic solution. The best human-AI interactions happen when we provide structure, clarity, and context.
Start with one rule per week. Pick a routine task—maybe analyzing survey responses or writing summaries. Apply that week's principle and see your results improve.
Your next breakthrough might be just one well-written prompt away.
P.S.: Curious to explore how we can tackle your research struggles together? I've got three suggestions that could be a great fit: A seven-day email course that teaches you the basics of research methods. Or the recordings of our AI research tools webinar and PhD student fast track webinar.
