Why ChatGPT Keeps Giving You Generic, Useless Responses (And A Simple Framework That Solves That)

You open ChatGPT, type in what feels like a clear request, and hit enter.

What comes back is… technically an answer. But it’s vague, too fluffy, or completely missing the point of what you actually needed. Now you’re stuck rewording, re-asking, or just giving up and doing it yourself.

One podcast listener recently told me: “I keep trying different prompts I find online, but ChatGPT still feels like it’s guessing what I want.

I waste more time fixing its responses than if I’d just written it myself.”

You’re not alone. This frustration is completely normal, and you’re not doing anything wrong.

Most professionals make the same fundamental mistake that kills their productivity with AI.

The real problem: You’re treating ChatGPT like Google when you should be treating it like a new team member who needs proper onboarding.

This article walks you through a simple, four-part framework that helps you get better, more relevant, more helpful responses – whether you’re writing, planning, analyzing, or problem-solving.

You’ll learn exactly what to include in every ChatGPT request to stop the guesswork and start getting output you can actually use.

The Four-Part Framework That Changes Everything

Before diving into why this works, here’s the complete framework you can start using immediately. Each part plays a specific role in getting better, more useful responses:

1. What are we doing? Start by stating the task or project clearly and directly.

2. Why are we doing it? Give context. Help ChatGPT understand the bigger picture or goal.

3. What does success look like? Describe what a great answer would include—or what you’re hoping to walk away with.

4. Do you have any questions for me? Invite ChatGPT to ask clarifying questions so it can fill in any gaps.

That’s it. Four simple steps that turn ChatGPT from a guessing machine into a thinking partner.

Now let’s look at each part and why it works.

Part 1: What Are We Doing? (Stop Making ChatGPT Guess)

This is where you tell ChatGPT what the actual task is. Not what you hope it figures out—what you’re specifically working on.

Most people skip this step or assume the task is obvious from their prompt. But when you don’t clearly state what you’re trying to do, ChatGPT has to guess. And when it guesses, you get generic, confusing, or completely off-track answers.

Here’s what this sounds like:

“I’m putting together a short overview of our company for a new team member.”
“I need help reviewing a customer transcript and pulling out key insights we could use in training.”
“I’m drafting an email to reconnect with a former client, and I want it to sound friendly and professional.”

What changes: ChatGPT stops guessing and starts focusing. You get targeted responses instead of generic ones that miss the mark entirely.

One clear sentence like this is often enough. You’re setting the stage and helping it focus.

Part 2: Why Are We Doing It? (Give Context That Actually Helps)

This is the part that gives ChatGPT context—and context is what turns a generic response into a useful one.

When you tell it why you’re doing the task, you help it understand your priorities, your goals, and what kind of thinking will be most helpful.

Here are a few examples:

“I’m writing this company overview so I can reuse it in future marketing materials.”
“I’m reviewing this transcript because I want to improve how we train new team members.”
“I’m sending this email to reconnect with a client I haven’t spoken to in a while.”

What changes: ChatGPT starts making smart choices about tone, length, focus, and format because it understands what matters most to you.

It’s a simple addition, but it makes a massive difference. If the first part gives it a map, this part tells it where you’re trying to go.

Part 3: What Does Success Look Like? (Get Output You Can Actually Use)

Once you’ve told ChatGPT what you’re working on and why, the next step is to define what a helpful result would look like.

Not just the topic—but the form it should take and what you’ll do with it.

Are you hoping for a bulleted list? A first draft of an email? A table with comparison points? A short summary with insights? This is where you spell that out.

A few examples:

“Success looks like a table that compares the last three years of data, organized by region.”
“I’d like a short list of clear takeaways I can copy into a presentation.”
“I’m looking for a first-draft response that sounds like it came from a real person, not a bot.”
“Please give me the top three patterns you notice from this data, along with a one-sentence insight for each.”

What changes: You stop getting technically correct answers that don’t actually help you move forward. Instead, you get output formatted exactly how you’ll use it.

This simple step saves you 15 minutes of reformatting and rewriting per task.

Part 4: Do You Have Any Questions for Me? (Turn It Into a Partner)

This is the step that turns ChatGPT from a basic assistant into a thinking partner.

Once you’ve told it what you’re doing, why you’re doing it, and what success looks like, finish by asking:

“Do you have any questions for me to help you do your best work?”

This prompt invites ChatGPT to pause, look for gaps, and clarify before jumping to conclusions. That one question often triggers follow-up questions that uncover missing context, unclear priorities, or overlooked details.

You’ll start getting questions like:

“Should I keep the tone casual or professional?”
“Is there a word count or length you’re aiming for?”
“Should I pull examples from the data you provided, or keep it general?”
“Do you want me to focus on recent trends or historical patterns?”

What changes: You catch misunderstandings before they happen. Your first response becomes your final response because ChatGPT actually understood the assignment.

This final step helps you slow down just enough to get the output right the first time, instead of fixing it later.

How This Framework Works in Real Life

To help show how this framework can be used, let’s use the following scenario: You’re a team lead who needs to create training materials for your customer support team. They’ve been struggling with the most common questions about your software’s reporting features, which is leading to longer call times and some frustrated customers.

This is exactly the kind of task where most people get stuck with ChatGPT. It seems straightforward enough—you need training materials—but there are actually dozens of ways ChatGPT could interpret that request. Without the right setup, you’ll likely get something generic and unusable.

Let’s see what happens when you approach this task the typical way versus using the four-part framework.

The “Before” (Typical Beginner Approach)

What most people would type into ChatGPT:

“Help me create training materials for customer support questions about reporting.”

What ChatGPT gives back: A generic 500-word document with sections like:

“Introduction to Customer Support Training”
“Understanding Reporting Fundamentals”
“Best Practices for Handling Customer Inquiries”
“Sample Q&A Scenarios”

It’s technically correct but completely useless. The format is wrong, the content is too broad, and it doesn’t address your specific software or team needs. You end up spending 30 minutes trying to rewrite your request or just giving up and creating the document yourself.

The “After” (Using the Four-Part Framework)

Step 1: What are we doing? “I need to create a training document that helps our customer support team handle the most common questions we get about our software’s reporting features.”

Step 2: Why are we doing it? “I’m creating this because our newer team members are struggling with these questions, and it’s creating longer response times and some frustrated customers. I want something they can reference quickly during calls.”

Step 3: What does success look like? “Success looks like a one-page reference sheet with the top 5 reporting questions, clear answers for each one, and maybe a troubleshooting tip. It should be formatted so someone can scan it quickly while they’re on a call with a customer.”

Step 4: Do you have any questions for me? “Do you have any questions for me to help you do your best work?”

ChatGPT’s response: “I’d be happy to help create that training reference sheet. A few questions to make sure I get this right:

Should the tone be more conversational (like you’re talking to the customer) or more instructional (like internal notes)?
Do you want me to include any specific software terms or keep it in plain language?
For the troubleshooting tips, should these be step-by-step instructions or just quick pointers?
Do you have the actual customer questions you’d like me to work from, or should I suggest common ones based on typical reporting software issues?”

The result: You get a better outcome – a scannable, one-page reference sheet that your team can actually use during customer calls.

Start Getting Better Responses Today

The biggest shift most ChatGPT users need isn’t more prompts—it’s more structure. Instead of diving straight into requests, build this habit:

Pick one task you do regularly (emails, summaries, brainstorming sessions)
Use this four-part framework your next three times
Notice how responses improve when you provide context upfront
Save your best framework variations for different types of work
Stop second-guessing yourself—this approach works consistently

You don’t need to get it perfect on the first try. If ChatGPT gives you something close but not quite right, you can fine-tune it by pointing back to your original success criteria or adding more context.

Most professionals see immediate improvement in their first session. You’ll spend less time rewording, less time fixing responses, and more time actually getting useful work done.

Remember: ChatGPT isn’t broken when it gives you mediocre results. It just needs better input to give you better output. This framework provides exactly that.