In partnership with

You Don’t Need to Be Technical. Just Informed

AI isn’t optional anymore—but coding isn’t required.

The AI Report gives business leaders the edge with daily insights, use cases, and implementation guides across ops, sales, and strategy.

Trusted by professionals at Google, OpenAI, and Microsoft.

👉 Get the newsletter and make smarter AI decisions.

Lead with AI—no coding needed

Hey, here are some of our tips and tricks for better AI results.

The Complete Guide to Better AI Chat Results

Introduction

Getting exceptional results from AI chatbots like ChatGPT, Claude, or other language models isn't about luck—it's about crafting thoughtful prompts that unlock their full potential. This guide will transform how you interact with AI by showing you specific techniques that consistently produce deeper, more useful responses.

The Power of Specific Prompting

The difference between mediocre and exceptional AI responses often comes down to how you frame your request. Vague prompts produce generic answers, while specific, well-structured prompts unlock sophisticated analysis and creative solutions.

Core Techniques for Better Results

1. Force Deep Analysis

The Problem with Vague Requests:

• "Make this sound better"

• "Improve my writing"

• "Help me with this"

The Solution - Be Specific About the Type of Analysis You Want:

Instead of: "Make this sound better." Ask: "Break this down like a writing coach. What's weak, what's strong, and how can it be improved?"

Why This Works: You're defining a specific role (writing coach) and requesting structured analysis (weak/strong/improvements). This prompts the AI to engage in systematic evaluation rather than surface-level editing.

Other Examples:

• "Analyze this business proposal like a venture capitalist. What risks do you see, what opportunities excite you, and what questions would you ask?"

• "Review this code like a senior developer. What are potential bugs, performance issues, and areas for refactoring?"

• "Examine this argument like a philosophy professor. What logical fallacies exist, what premises need support, and how could it be strengthened?"

2. Challenge Assumptions

The Problem with One-Sided Requests:

• "Write a persuasive argument"

• "Support my position"

• "Agree with my point"

The Solution - Request Opposition and Critical Thinking:

Instead of: "Write a persuasive argument." Ask: "Play devil's advocate against my argument. What flaws can you find, and how would you counter them?"

Why This Works: This technique forces the AI to think critically and expose weaknesses you might not have considered. It's like having a debate partner who strengthens your position by attacking it.

Advanced Applications:

• "Present the strongest possible case against [your position], then help me address those counterarguments"

• "What would my biggest critic say about this approach, and are they right?"

• "Challenge every assumption I'm making in this plan. What could go wrong?"

3. Define Clear Roles and Perspectives

Transform generic responses by assigning the AI specific expertise or viewpoints.

Examples:

• "Respond as a seasoned project manager with 15 years of experience"

• "Take the perspective of someone who disagrees with this completely"

• "Analyze this as both a marketer and a consumer"

4. Request Structured Outputs

Guide the AI toward organized, actionable responses.

Instead of: "What do you think about this?" Ask: "Give me three strengths, three weaknesses, and three specific recommendations."

Other Structures to Try:

• "Pros, cons, and verdict"

• "Short-term vs. long-term implications"

• "What works, what doesn't, what's missing"

• "Beginner, intermediate, and advanced approaches"

5. Use Comparative Analysis

Examples:

• "Compare my approach to how Google, Apple, and Amazon might handle this"

• "Contrast this solution with the three most common alternatives"

• "How does this differ from the standard industry approach?"

6. Request Multiple Iterations

Instead of: "Write a proposal." Ask: "Write three different versions of this proposal: one conservative, one aggressive, and one creative. Then tell me which situations each would work best in."

7. Demand Specific Evidence and Examples

Instead of: "Is this a good strategy?" Ask: "What specific evidence supports or contradicts this strategy? Give me real-world examples of when similar approaches succeeded or failed."

Advanced Prompting Strategies

3. Refine Step by Step

The Problem with All-at-Once Requests:

• "Rewrite this post to sound engaging"

• "Make this better"

• "Improve this content"

The Solution - Break Down the Process:

Instead of: "Rewrite this post to sound engaging." Ask: "First, improve clarity. Then, add storytelling. Finally, boost emotional impact."

Why This Works: This technique prevents the AI from trying to fix everything simultaneously, which often leads to muddled results. By requesting sequential improvements, you get cleaner, more intentional changes at each stage.

Advanced Applications:

• "Step 1: Fix grammar and structure. Step 2: Strengthen the argument. Step 3: Add compelling examples."

• "First pass: Remove jargon. Second pass: Add personality. Third pass: Optimize for readability."

• "Phase 1: Identify the core message. Phase 2: Build supporting evidence. Phase 3: Craft a memorable conclusion."

4. Reverse Engineer Success

The Problem with Generic Creation Requests:

• "Write a viral post"

• "Create engaging content"

• "Make something popular"

The Solution - Learn from What Works:

Instead of: "Write a viral post." Ask: "Analyze the top viral posts in [niche] and craft one using their structure and engagement techniques."

Why This Works: Rather than guessing what might work, you're building on proven patterns. The AI can identify successful elements and adapt them to your specific context.

Expanded Examples:

• "Study the three most successful product launches in tech this year. What common elements made them work, and how can I apply those to my launch?"

• "Analyze the top-performing LinkedIn posts from industry leaders. What hooks, structures, and calls-to-action do they use consistently?"

• "Break down the most engaging TED talks in my field. What storytelling techniques can I adapt for my presentation?"

5. Make It Think in Layers

The Problem with Single-Approach Requests:

• "Make this copy more effective"

• "Write a better version"

• "Improve this message"

The Solution - Request Multiple Strategic Approaches:

Instead of: "Make this copy more effective." Ask: "Give me three rewrites: one concise, one storytelling-driven, and one with psychological triggers."

Why This Works: Different situations call for different approaches. By requesting multiple versions with distinct strategies, you get options to choose from and insights into various persuasion techniques.

Other Layered Approaches:

• "Create three versions: one for beginners, one for experts, and one for skeptics"

• "Write this three ways: formal/professional, conversational/friendly, and bold/provocative"

• "Give me logical version, emotional version, and social proof version"

• "Show me the direct approach, the story approach, and the question-based approach"

6. Force Unique Perspectives

The Problem with Generic Explanations:

• "Explain this concept"

• "Describe how this works"

• "Tell me about this topic"

The Solution - Assign Specific Communication Contexts:

Instead of: "Explain this concept." Ask: "Explain this as if you were a TED speaker simplifying it for a global audience."

Why This Works: Context shapes communication style. By specifying the setting and audience, you get explanations tailored to specific communication goals and constraints.

Perspective Variations:

• "Explain this like you're pitching to investors who have 2 minutes of attention"

• "Describe this as if you're teaching your grandmother who's never used technology"

• "Present this like you're a documentary narrator making it fascinating for mainstream audiences"

• "Break this down as if you're a coach motivating someone who's intimidated by the topic"

• "Explain this like you're a consultant presenting to executives who hate technical jargon"

The "Explain Like I'm Five, Then Like I'm a PhD" Technique

"First, explain this concept as if I'm a complete beginner. Then, dive deep into the technical details for someone with advanced knowledge."

This gives you both accessibility and depth in one response.

The Scenario Planning Method

"Walk me through three scenarios: best case, worst case, and most likely. What should I prepare for in each?"

The Multi-Stakeholder Perspective

"How would a customer, an employee, a shareholder, and a competitor each view this decision?"

The Time-Based Analysis

"Analyze the immediate effects (next month), medium-term implications (next year), and long-term consequences (5+ years) of this choice."

Common Prompting Mistakes to Avoid

1. Being too vague: "Help me with marketing" vs. "Create a content strategy for B2B SaaS targeting startup founders"

2. Asking for agreement instead of analysis: "Don't you think this is great?" vs. "What are the potential problems with this approach?"

3. Single-shot thinking: Asking one question instead of building on responses with follow-ups

4. Ignoring context: Not providing enough background information for meaningful analysis

5. Accepting first responses: Not pushing for deeper analysis with follow-up questions

Follow-Up Question Techniques

The first response is often just the beginning. Use these follow-ups to dig deeper:

• "Can you elaborate on [specific point from their response]?"

• "What would someone who disagrees with this analysis say?"

• "Give me three concrete examples of this in action"

• "What are you assuming that might not be true?"

• "How would this change if [different constraint/condition]?"

Putting It All Together: A Complete Example

Weak Prompt: "Help me improve my team's productivity."

Strong Prompt: "Analyze my team's productivity challenges like an organizational psychologist. Here's our situation: [specific context]. What behavioral patterns might be causing issues, what environmental factors should I consider, and what evidence-based interventions would you recommend? Then play devil's advocate—what could go wrong with each recommendation?"

Follow-up: "Now compare your recommendations to what Google, Toyota, and a top consulting firm might do differently. What unique insights does each approach offer?"

The Meta-Principle

The underlying secret to all effective AI prompting is this: Ask the AI to think the way you want it to think, not just to give you what you want to hear.

Instead of seeking confirmation, seek insight. Instead of requesting output, request analysis. Instead of looking for agreement, look for understanding.

Practice Exercises

Try rewriting these weak prompts using the techniques above:

1. "Write a business plan"

2. "Is this a good idea?"

3. "Make this email better"

4. "Help me solve this problem"

5. "What should I do?"

6. "Create viral content"

7. "Explain quantum physics"

8. "Make this presentation better"

The goal isn't just better AI responses—it's training yourself to think more critically and systematically about the challenges you face.

Conclusion

Exceptional AI interactions don't happen by accident. They result from intentional prompting that pushes the AI beyond surface-level responses into deep, structured analysis. By forcing the AI to adopt specific roles, challenge assumptions, and provide evidence-based reasoning, you transform it from a simple question-answering tool into a sophisticated thinking partner.

The techniques in this guide work because they mirror how human experts actually think: systematically, critically, and from multiple perspectives. Master these approaches, and you'll consistently get AI responses that are not just helpful, but genuinely insightful.