🏴‍☠️ Turn generic AI advice into expert consulting

The anti-guessing prompt

Author

Captain YAR
February 28, 2026 • Estimated Reading Time: 7 minutes

Here is the short version: This prompt stops the AI from guessing and forces it to diagnose your problem first, turning a basic chatbot into a long-term strategic partner.

Getting specific, actionable advice from an LLM can often feel like pulling teeth. You ask a question, and the model immediately spits out a generic list of suggestions that don’t quite fit your situation. That is why I was excited to find a post by u/kallushub, who shared a robust framework designed to fix this exact issue. This contributor created a “Consultant Prompt” that forces the AI to pause, gather context, and iterate on solutions rather than just guessing.

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The Consultant Prompt 2.0

Here is the exact text provided by the author. You can paste this directly into ChatGPT, Claude, or any capable model.

You are acting as my strategic problem-solving consultant.

Your job is to help me fully resolve my problem, not just give advice.

Before offering any solutions, you must ask me exactly five diagnostic questions to clarify:

  1. What exactly is happening? What evidence confirms it?

  2. What does success look like in measurable terms? By when?

  3. What constraints, risks, or limits exist?

  4. What resources, leverage, or advantages are available?

  5. What has already been tried? What were the results?

Do not give solutions until I answer.

After I respond:

  • Identify the root cause (separate symptoms from real issues).

  • Highlight key leverage points.

  • Propose 2–3 possible strategies.

  • Briefly compare them by impact, effort, risk, speed, and reversibility.

  • Recommend ONE primary path and explain why.

  • Clearly label assumptions as: Assumption

…

Check out the full prompt here

Credit to kallushub

Why This Approach Works

The genius of this prompt lies in its constraints and structure. The original poster included a “stop sequence” command: “Do not give solutions until I answer.” This prevents the AI from hallucinating a solution based on incomplete data. By forcing the model to ask the five diagnostic questions first, the prompt ensures the AI understands your constraints, resources, and history before it attempts to solve anything.

Furthermore, the prompt uses a Chain-of-Thought technique by asking the AI to separate symptoms from root causes and compare multiple strategies. It doesn’t just give you one answer; it weighs options based on impact, effort, and risk. Finally, the inclusion of an iterative loop means the AI expects you to come back with results, turning the interaction into an ongoing project management session rather than a one-off query.

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Variations to Try

While the original prompt is excellent for general strategy, you can tweak the persona to fit specific niches:

  • The Technical Lead: Change the persona to “Senior Software Architect.” Modify the diagnostic questions to ask about the tech stack, legacy code constraints, and performance requirements.

  • The Fitness Coach: Change the persona to “Elite Sports Physiologist.” Change the questions to ask about current injury status, dietary restrictions, and equipment access.

Best Use Cases

This structure shines when you have a complex problem with multiple variables.

  1. Business Strategy: When you are trying to enter a new market or pivot a product and need to weigh risks against resources.

  2. Career Planning: If you are considering a job switch, the diagnostic questions help clarify what “success” actually looks like for you.

  3. Project Management: Use the execution plan section to generate actual timelines and risk mitigation strategies for team projects.

This is a powerful way to make the AI work harder for you. If you want to see how others are using it or offer feedback, checking out the original Reddit discussion is highly recommended!

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