Structured Reasoning

Structured Reasoning: Teaching AI to Think Like a Detective 🔍

Imagine you’re a detective solving a mystery. You don’t just guess randomly—you step back, make a plan, follow logical steps, and write notes as you go. That’s exactly what Structured Reasoning methods teach AI to do!

The Big Picture: Why Structure Matters

Think of AI like a super-smart friend who sometimes rushes to answer before fully thinking. Structured Reasoning is like teaching that friend to:

1. Take a breath and look at the bigger picture
2. Make a plan before diving in
3. Show their work step by step
4. Keep notes so they don’t forget important things

Let’s explore each method with a simple analogy: Building a LEGO Castle 🏰

1. Step-Back Prompting: The Helicopter View 🚁

What Is It?

Before solving a problem, you zoom out and ask a bigger, more general question first. It’s like flying a helicopter over a maze before walking through it!

The LEGO Analogy

Without Step-Back: “How do I attach this tiny flag piece?”

With Step-Back: “Wait, what’s the overall design of the castle? Where should towers go?” → Then: “Now I know the flag goes on the tallest tower!”

How It Works

Step 1: See specific question
Step 2: Ask "What's the bigger concept here?"
Step 3: Answer the general question
Step 4: Use that knowledge to solve the specific problem

Real Example

Question: “What happens when you mix vinegar and baking soda?”

Step-Back First: “What do I know about acid-base reactions in general?”

Answer: Acids + Bases → Salt + Water + Gas (sometimes)

Now Solve: Vinegar (acid) + Baking soda (base) = Salt + Water + CO2 bubbles!

When to Use It

• Complex problems that feel overwhelming
• When you’re stuck and need fresh perspective
• Questions that need background knowledge first

2. Skeleton-of-Thought: The Blueprint Method 📋

What Is It?

Before writing a full answer, you create a skeleton (outline) first. Think of it like a builder who draws blueprints before laying bricks!

The LEGO Analogy

Without Skeleton: Start building randomly, hope it looks like a castle…

With Skeleton:

1. Foundation: Gray flat pieces
2. Walls: Four sides, doors on front
3. Towers: Four corners
4. Roof: Red slanted pieces
5. Details: Flags, windows, guards

How It Works

graph TD
    A["Get Question"] --> B["Create Skeleton/Outline"]
    B --> C["Point 1: Main idea"]
    B --> D["Point 2: Supporting idea"]
    B --> E["Point 3: Example"]
    B --> F["Point 4: Conclusion"]
    C --> G["Expand Each Point"]
    D --> G
    E --> G
    F --> G
    G --> H["Complete Answer!"]

Real Example

Question: “Explain how plants make food”

Skeleton First:

1. Plants need ingredients (water, CO2, sunlight)
2. The kitchen is in leaves (chlorophyll)
3. The recipe is photosynthesis
4. The food made is glucose (sugar)

Then Expand Each Point into full sentences!

The Magic Benefit

You can write different parts at the same time (parallel processing), making answers faster and more organized!

3. Program-of-Thought: Think Like a Calculator 🧮

What Is It?

Instead of doing math in your head, you write it out as a mini program—step-by-step calculations that anyone can follow and check!

The LEGO Analogy

Without Program: “I think I need… maybe 50 bricks? Or 100?”

With Program:

walls = 4 sides × 20 bricks = 80
towers = 4 × 15 bricks = 60
roof = 40 bricks
total = 80 + 60 + 40 = 180 bricks

How It Works

graph TD
    A["Word Problem"] --> B["Identify Variables"]
    B --> C["Write Formula/Code"]
    C --> D["Calculate Step-by-Step"]
    D --> E["Get Final Answer"]
    E --> F["Verify: Does it make sense?"]

Real Example

Problem: “A train travels 60 mph for 2.5 hours, then 80 mph for 1.5 hours. How far did it go?”

Program-of-Thought:

# Step 1: First part of journey
distance_1 = 60 mph × 2.5 hours
distance_1 = 150 miles

# Step 2: Second part of journey
distance_2 = 80 mph × 1.5 hours
distance_2 = 120 miles

# Step 3: Total distance
total = distance_1 + distance_2
total = 150 + 120
total = 270 miles

Why It’s Powerful

• Clear: Every step is visible
• Checkable: Easy to find mistakes
• Reusable: Change numbers, same logic works!

4. Scratchpad Prompting: The Thinking Notepad 📝

What Is It?

Give the AI a scratchpad—a space to write down thoughts, try ideas, and work through problems before giving the final answer. Like rough work in math class!

The LEGO Analogy

Without Scratchpad: Build from memory, forget what you tried, repeat mistakes…

With Scratchpad:

SCRATCHPAD:
- Tried blue walls → looked like water, not castle ❌
- Tried gray walls → looks like stone! ✓
- Need taller towers → 20 bricks high
- Flag colors: red and gold → royal look ✓

FINAL: Gray walls, 20-brick towers, red/gold flags

How It Works

The AI gets a special area to “think out loud” before answering:

Question: What's 17 × 23?

SCRATCHPAD:
Let me break this down...
17 × 23 = 17 × (20 + 3)
       = (17 × 20) + (17 × 3)
       = 340 + 51
       = 391

ANSWER: 391

Real Example

Problem: “Is 847 divisible by 7?”

Scratchpad:

Let me check by division...
847 ÷ 7 = ?
7 × 100 = 700
847 - 700 = 147
7 × 20 = 140
147 - 140 = 7
7 × 1 = 7
7 - 7 = 0 ← No remainder!
So: 847 = 7 × 121

Answer: Yes! 847 is divisible by 7.

The Scratchpad Superpower

• Prevents forgetting intermediate steps
• Makes reasoning transparent
• Helps catch errors before the final answer

Comparing All Four Methods

The Master Flow: Combining Methods 🌟

The best prompt engineers often combine these methods:

graph TD
    A["Hard Problem"] --> B[Step-Back: What's the big picture?]
    B --> C["Skeleton: Plan my answer sections"]
    C --> D["Scratchpad: Work through tricky parts"]
    D --> E["Program-of-Thought: Calculate precisely"]
    E --> F["Polish: Clean final answer"]

Quick Tips for Each Method

Step-Back Prompting

“Before answering, first consider: What general principle or concept does this question relate to?”

Skeleton-of-Thought

“Create a brief outline of your answer first, then expand each point.”

Program-of-Thought

“Solve this step-by-step, writing out each calculation like a computer program.”

Scratchpad Prompting

“Use the scratchpad below to work through your reasoning before giving your final answer.”

Your Confidence Boost 💪

You now understand four powerful ways to help AI think more clearly:

1. Step-Back = See the forest, then the trees
2. Skeleton = Blueprint before building
3. Program = Calculate like a computer
4. Scratchpad = Show your work like a math test

These aren’t just AI tricks—they’re good thinking habits for humans too! Next time you face a hard problem, try one of these methods yourself.

You’ve got this! 🚀