WEEKLY NEWSLETTER
Why Your AI Keeps Failing You (And How to Fix It in 60 Seconds)
© CURRENT YEAR, AI Business Lab. All rights reserved.
Your AI isn’t broken. Your instructions are. And that’s costing you hours of wasted time every single week.
“If I want it done right, I need to do it myself.”
My client Jordan slumped back in his chair, frustration written all over his face. We were on a Zoom call, and he’d just finished explaining why his executive assistant wasn’t working out. Again.
This was his third assistant in less than a year. Same complaints each time: tasks incomplete, details missed, expectations unmet.
I paused before responding. “Jordan, what if the problem isn’t them?”
His expression shifted. “What do you mean?”
“Walk me through exactly what you told your assistant when you delegated that last project.”
He thought for a moment. “I said, ’Handle the client presentation.’”
“That’s it?”
“Well… yeah. She should know what that means.”
There it was. Jordan expected his assistant to read his mind. And sure enough, when we started discussing his struggles with AI tools, I heard the exact same pattern.
“I tried ChatGPT. Gemini. Even Claude. None of them give me what I need.”
“What are you asking them?”
“Things like ’write a proposal’ or ’create a strategy deck.’”
The penny dropped. Jordan’s AI frustration had nothing to do with the technology. He was giving AI the same vague instructions he gave his team—and getting the same disappointing results.
Here’s what I told him: Neither your human teammates nor your AI tools can read your mind. If you want better results, you need better instructions.
The Framework That Changes Everything
You can transform your AI results from generic to game-changing by following a simple framework. Here are the five elements every effective prompt should include.
Element #1: Define the Role
Think about it. When you delegate to your team, you don’t just hand someone a task. You clarify who they need to be for this specific assignment.
“Handle this like you’re our CFO reviewing the budget.” “Approach this as if you’re presenting to a skeptical board.”
AI works the same way. Research shows that assigning a relevant role to AI systems significantly improves output quality by providing domain-specific context and guiding the model’s tone and approach.1 When you tell AI what role to play, you’re giving it a lens through which to interpret your request.
Instead of: “Write an email to my team.” Try: “You’re a CEO addressing your leadership team about a strategic pivot. Write an email explaining the change.”
The difference? Night and day.
Element #2: Provide the Context
Here’s where most people fail. They assume AI knows their situation, their audience, their constraints.
It doesn’t.
A 2025 study on prompt engineering found that users who provide clear, structured, and context-specific prompts experience significantly higher productivity benefits and better quality outcomes than those using vague requests.2 Context is the bridge between what you want and what AI can deliver.
When Jordan said “write a proposal,” AI had no idea:
- Who the proposal was for
- What problem it needed to solve
- What tone would resonate
- What length made sense
Add context: “I need a 2-page proposal for a Fortune 500 CTO explaining how our software reduces security risks. The tone should be confident but not salesy. They’re technically sophisticated and skeptical of vendor claims.”
Now you’re cooking.
Element #3: State the Assignment
This seems obvious, but you’d be surprised how many people bury their actual request in paragraphs of context.
Be direct. Be specific.
Research on AI interaction demonstrates that clarity and specificity in task definition dramatically reduce ambiguity and improve response accuracy—the granularity of your input is directly proportional to the utility of your output.3
Don’t say: “Help me with marketing.” Say: “Create three LinkedIn post headlines (under 100 characters each) for a SaaS product targeting small business owners. Focus on the benefit of saving 5 hours per week.”
The more precise your assignment, the less time you waste editing garbage output.
Element #4: Specify the Output
Here’s where Jordan’s delegation really broke down with his assistant—and with AI.
You have to tell them what done looks like.
“A proposal” could mean anything:
- A 10-slide deck?
- A 5-page document?
- Bullet points in an email?
- A formal PDF with executive summary?
Studies show that specifying output format, structure, and style requirements significantly enhances AI model performance by reducing interpretation errors and aligning results with user expectations.4
Add this to your prompts: “Deliver this as a 3-paragraph email with a subject line and a clear call to action at the end.”
Boom. You just eliminated 3 rounds of revision.
Element #5: Include Examples (Optional)
This is the secret weapon.
If you’ve ever trained someone new, you know that showing is better than telling. AI is no different.
When you provide examples of what good looks like, you’re giving AI a pattern to match. A 2025 analysis found that prompting techniques offering clear structural guidance and relevant examples dramatically outperform vague requests across diverse tasks.5
Try this: “Here’s an example of a headline I love: ’How 3 Small Changes Doubled Our Revenue in 90 Days.’ Create 5 similar headlines for this case study.”
Examples don’t just improve output quality. They cut your iteration time in half.
It’s Not the Tool—It’s the Instruction
Here’s the thing I eventually helped Jordan see: The breakthrough wasn’t switching assistants or trying different AI tools.
It was learning to communicate clearly.
When Jordan started applying this framework to both his human team and his AI tools, everything changed. His assistant went from struggling to stellar. His AI outputs went from generic to genuinely useful.
The five-element framework gave him a mental checklist:
- Have I defined the role?
- Have I provided sufficient context?
- Have I stated the assignment clearly?
- Have I specified what the output should look like?
- Could an example help?
Most of the time, he only needed the first four. But when he wanted something specific—a particular style, a certain format—examples sealed the deal.
Your Turn
Imagine what would happen if every time you delegated to a person or an AI, you got it right the first time. No endless back-and-forth. No disappointment. No wasted hours.
That’s not fantasy. It’s the natural result of clear communication.
The tools—whether human or AI—are ready to deliver. The question is: Are you ready to give them what they need to succeed?
What’s one task you’ve been frustrated with that you could transform by applying this framework today?
Comments
If you have a question about using PromptGenie, click here to send me an email. I read every one. Seriously. Your experiences help me write better content, and sometimes the best insights come from readers like you.
Transforming AI from noise to know-how,
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REFERENCE
- Sander Schulhoff, “Is Role Prompting Effective?” Learn Prompting, accessed January 16, 2026. ↩︎
- “Prompt Engineering and the Effectiveness of Large Language Models in Enhancing Human Productivity,” arXiv, May 10, 2025. ↩︎
- “Effective Prompts for AI: The Essentials,” MIT Sloan Teaching & Learning Technologies, May 30, 2025. ↩︎
- “AI Demystified: What is Prompt Engineering?” Stanford University IT, accessed January 16, 2026. ↩︎
- “Which Prompting Technique Should I Use? An Empirical Investigation of Prompting Techniques for Software Engineering Tasks,” arXiv, June 5, 2025. ↩︎
