5 Question Mistakes That Waste Your AI Tokens (And How to Fix Them)

You've probably experienced this: you ask ChatGPT or Claude something, get a mediocre response, and spend the next 10 minutes in a frustrating back-and-forth trying to get what you actually needed.

That's not AI being "bad." That's your question being unclear.

After analyzing thousands of questions through QuestionCraft, I've identified five patterns that consistently produce poor results. Here's what they are and exactly how to fix each one.

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Mistake #1: The Lazy Open

What it looks like:

• "Tell me about leadership."
• "Help me with my resume."
• "What should I do about my business?"

Why it fails: These questions have infinite valid answers. The AI has to guess what you actually want, and it will almost always guess wrong. The fix: Add goal + context + specificity. ❌ "Tell me about leadership." ✅ "I'm a new manager (promoted 2 months ago) struggling with a team member who has more experience than me. What are three specific techniques for leading people who know more than you do?"

The second question tells the AI exactly what you need. Same topic, radically different usefulness.

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Mistake #2: The Kitchen Sink

What it looks like: A 500-word question that asks 12 different things at once. Why it fails: Cognitive overload—for both you and the AI. You'll get shallow answers to each part, none of which fully address your actual need. The fix: One question, one clear goal. If you have multiple questions, ask them separately. ❌ "I need help with my marketing strategy, also what do you think about my pricing, and can you review my website copy, plus I'm wondering about the best social media platforms, and should I do email marketing or focus on SEO, and what about paid ads?" ✅ "I'm launching a B2B SaaS product. Right now, I need help with ONE thing: my positioning statement. Here's my current version: [statement]. What's unclear or uncompelling about this?"

Handle one thing well before moving to the next.

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Mistake #3: The Assumption Trap

What it looks like:

• "Why isn't my marketing strategy working?"
• "Why does my team keep missing deadlines?"
• "Why can't I lose weight?"

Why it fails: These questions assume you've already diagnosed the problem. But what if the strategy is fine and execution is the issue? What if the deadlines are unrealistic? What if it's not about diet at all? The fix: Question your question first. Ask for diagnosis before solutions. ❌ "Why isn't my marketing strategy working?" ✅ "My marketing isn't producing leads. Before I change strategy, help me diagnose: Is this more likely a strategy problem, an execution problem, or a market timing problem? What evidence would indicate each?"

Let the AI help you figure out WHAT's wrong before jumping to solutions.

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Mistake #4: The Vague Emotion

What it looks like:

• "I'm frustrated with my team."
• "I feel stuck in my career."
• "This project is overwhelming me."

Why it fails: Emotions are valid, but they're not questions. The AI doesn't know what you want it to do with this information. The fix: Translate emotion into a desired outcome. ❌ "I'm frustrated with my team." ✅ "I'm frustrated because my team misses deadlines and I end up doing their work. I want to hold them accountable without micromanaging. What's the first conversation I should have, and what should I say?"

Same frustration, but now there's a clear ask.

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Mistake #5: The Answer-in-Disguise

What it looks like:

• "Don't you think we should launch the product sooner?"
• "Isn't it better to just fire him?"
• "Shouldn't I focus on growth over profitability?"

Why it fails: These aren't questions—they're opinions seeking validation. You're not looking for insight; you're looking for agreement. The fix: Ask what you actually want to know. ❌ "Don't you think we should launch the product sooner?" ✅ "What are the risks of launching two months early vs. the risks of waiting for the planned date? I'm leaning toward launching early—what am I probably not considering?"

If you already have an opinion, be explicit about it and ask for the counterargument.

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The Pattern Behind All Five Mistakes

Notice what all these mistakes have in common: they put the burden on the AI to figure out what you actually need.

When you ask a vague question, you're essentially saying "read my mind." And while AI is impressive, mind-reading isn't in the feature set.

The fix is always the same: be specific about what you want, why you want it, and what you'll do with it.

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A Quick Self-Check

Before you send your next important question to AI, ask yourself:

1. Goal: What specific outcome do I want?

2. Context: What does the AI need to know to help me?

3. Actionability: What will I actually DO with this answer?

If you can't answer those three questions about your question, rewrite it until you can.

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Go Deeper

This post covers just one aspect of effective questioning. For the complete framework—including Bloom's Taxonomy for AI prompts, the 60-Second Question Check, and 10 before/after transformations—read The Ultimate Guide to Asking Better Questions in the AI Age.

Or if you want hands-on practice, try QuestionCraft. You bring your real question, and the Question Engine guides you through improving it—then shows you how different AI models respond to your optimized question.

Ask better questions. Get better answers.