# Lets Think Step by Step

When we ask an AI a complex question without a structured approach, it can easily get confused or miss important details. Think of it like solving a puzzle without following any order—you might end up with a mess. The **LTSS prompting** method helps avoid this by

Author: Jeremy Morgan*Published: October 20, 2024*

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Hey there, tech enthusiasts! Today we’re diving into a super practical AI technique called **“Let’s Think Step-by-Step” (LTSS)** prompting. If you’re working with AI models, like GPT, and want them to tackle complex problems more clearly and accurately, this is a method you’ll want to master. It’s all about guiding the model through problems by breaking them down into smaller, manageable pieces. Let’s dig into how this works and why it’s so powerful!

## Why Step-by-Step Thinking is a Game Changer

When we ask an AI a complex question without a structured approach, it can easily get confused or miss important details. Think of it like solving a puzzle without following any order—you might end up with a mess. The **LTSS prompting** method helps avoid this by:

- Creating a
**logical flow**through the problem. - Making the AI’s reasoning easy to follow.
- Catching mistakes early by validating each step.
- Providing a clear
**trail**of how decisions were made.

By telling the model to take it step-by-step, you ensure better results. It’s like leading a friend through a maze one turn at a time instead of pointing them toward the exit from a distance and hoping they figure it out.

## How LTSS Prompting Works: The Core Ingredients

Ready to dive in? The **LTSS** method is built on five core principles:

### 1. Clear Initial Instruction

Start by telling the AI to break the problem down step-by-step. This sets the tone and makes it clear what’s expected. Something like, “Let’s solve this step by step,” will do the trick.

### 2. Logical Breakdown

Next, you break the problem into simple, logical steps. Each one should build on the last to create a natural progression through the problem.

### 3. Explicit Reasoning

At every step, the AI should explain *why* it’s doing what it’s doing. This makes the thought process transparent and helps spot errors before they pile up.

### 4. Validation

After each step, check the results. Does the AI’s answer make sense so far? If not, better to catch it now than wait until the end!

### 5. Synthesize the Final Answer

Once all the steps are complete, pull everything together for the final solution. This ensures everything lines up correctly, and nothing is left hanging.

## How to Build an LTSS Prompt

Let’s walk through the steps of crafting a solid LTSS prompt.

### 1. Start with a Clear Problem

First, lay out the problem clearly and tell the model to work through it step-by-step. Instead of saying, “How much does John have left?” try: “Let’s break it down step by step.”

### 2. Break the Problem into Steps

Create logical steps. Here’s an example for a simple math problem:

**Step 1**: “John has 12 apples.”**Step 2**: “He gives 3 apples to his sister.”

### 3. Validate Results After Each Step

Make sure to check each step before moving forward. After the model calculates how many apples John has left, confirm it got the right number before moving on.

### 4. Apply Common Patterns

Certain types of problems—like math or decision-making—follow common patterns. If you recognize a pattern, use it to your advantage and guide the model through the familiar process.

## LTSS in Action: Real-World Examples

Here are some practical uses of the LTSS method:

### Example 1: Solving a Math Problem

**Traditional Prompt**:

“If John has 12 apples, gives 3 to his sister, buys 6 more, and then uses 4 for a pie, how many does he have left?”

**LTSS Prompt**:

“Let’s solve this step by step:

- John starts with 12 apples.
- John gives 3 apples to his sister. (12 - 3 = 9)
- John buys 6 more apples. (9 + 6 = 15)
- John uses 4 apples for a pie. (15 - 4 = 11)

**Final Answer**: John has 11 apples left.”

### Example 2: Decision-Making

**Traditional Prompt**:

“Should I invest in stocks or bonds?”

**LTSS Prompt**:

“Let’s approach this decision step by step:

- What’s your risk tolerance?
- How long is your investment horizon?
- What’s the current economic outlook?
- Compare the potential risks and returns of stocks and bonds.
- Based on this, here’s my recommendation.”

### Example 3: Debugging Code

**Traditional Prompt**:

“Why isn’t this code working?”

**LTSS Prompt**:

“Let’s debug this step by step:

- Check the function structure.
- Verify the base cases.
- Review the logic for generating the sequence.
- Test edge cases to ensure they’re covered.”

## Best Practices for LTSS Prompting

Here’s how to get the most out of LTSS:

**Use it for complex tasks**: LTSS is ideal for problems that have multiple steps or require careful thought.**Keep steps clear and simple**: Don’t combine too many things into one step, or you’ll confuse the AI (and yourself!).**Validate each step**: Always double-check after each step to catch errors early.**Avoid skipping steps**: This one’s crucial—every step is there for a reason!

## Wrapping Up: Why LTSS is a Must-Know Tool

The **“Let’s Think Step-by-Step”** technique is like a map for guiding AI through tricky problems. It helps avoid missteps, makes the process clearer, and leads to more reliable answers. Whether you’re working on complex math, logic puzzles, or even debugging, LTSS can give your AI prompts a serious upgrade.

What do you think? Ready to try this out with your next AI project? Let me know how it goes!

Happy coding!

I wrote a book! Check out A Quick Guide to Coding with AI.

Become a super programmer!

Learn how to use Generative AI coding tools as a force multiplier for your career.

Questions or Comments? **Yell at me!**

- Jeremy