✍️ A mathematician published a book in 1945 that might make you dramatically better at using AI.

His name was George Pólya, and his idea was surprisingly simple: solving difficult problems isn’t just about being smart. It’s about knowing how to approach them.

He broke problem-solving into four steps. Eighty years later, they’re still incredibly useful, especially when working with AI.

1. Understand the problem. Define exactly what you’re trying to solve. What do you know, what are you assuming, and what’s still missing?

2. Devise a plan. Look for similar problems, explore different approaches, or break the challenge into smaller pieces.

3. Carry out the plan. Work through each step and check whether the reasoning actually holds up.

4. Look back. Did it work? Could you have done it more simply? What can you learn for next time?

The fourth step is the one people often neglect. They get an answer and move on without checking whether it makes sense or understanding why it worked.

Here’s a Claude prompt you can use to put Pólya’s method into practice:

Prompt:

Act as a problem-solving tutor using George Pólya’s four-step method.

My problem: [DESCRIBE YOUR PROBLEM]

1. Help me define the problem precisely. Separate known facts, assumptions, constraints and unknowns.
2. Suggest three possible approaches, using analogous problems or simpler subproblems.
3. Choose the most promising approach and walk me through its execution, checking each step.
4. Evaluate the result, identify weaknesses and extract reusable lessons.

Don’t jump straight to the answer. Help me understand the reasoning.

The idea isn’t simply to get better answers from AI. It’s to use AI to improve the way you think, approach unfamiliar challenges and solve problems independently.

Stop asking AI only for answers. Start using it to train your problem-solving skills.

@aipost 🏴