Thought Structures

The Thought Forest: How AI Thinks in Different Shapes 🌳

Imagine you’re lost in a big maze. You could try one path at a time (that’s regular thinking). But what if you could split into multiple copies of yourself and try ALL paths at once? That’s what we’re learning today!

The Big Idea: Thoughts Have Shapes!

When we ask an AI to solve a hard problem, HOW it thinks matters just as much as WHAT it thinks. Think of it like this:

• Chain-of-Thought = Walking in a straight line
• Tree of Thoughts = Exploring a branching tree
• Graph of Thoughts = A spider web of connected ideas
• Buffer of Thoughts = A toolbox of saved solutions
• Thread of Thought = Staying focused while ignoring distractions

Let’s explore each one with a fun story!

🌲 Tree of Thoughts (ToT)

What Is It?

Imagine you’re playing a video game where you can SAVE your progress, try different choices, and go BACK if one doesn’t work. That’s Tree of Thoughts!

Instead of thinking one step at a time in a line, the AI:

1. Thinks of MULTIPLE possible next steps
2. Explores each one like branches on a tree
3. Checks which branches look promising
4. Can go back and try a different branch if stuck

Simple Example: The Treasure Hunt

Problem: Find the treasure hidden in one of three caves.

Regular Thinking (Chain-of-Thought):

“I’ll check Cave A… nope. Now Cave B… nope. Now Cave C… found it!”

Tree of Thoughts:

"Let me think about ALL three caves at once:

• Cave A: Dark and scary… probably not good
• Cave B: Has footprints leading in… promising!
• Cave C: Looks empty… skip this

I’ll explore Cave B first!"

graph TD
    A["Start: Find Treasure"] --> B["Cave A: Dark"]
    A --> C["Cave B: Footprints!"]
    A --> D["Cave C: Empty"]
    C --> E["Follow footprints"]
    E --> F["Found Treasure!"]
    style C fill:#90EE90
    style F fill:#FFD700

When To Use It

Tree of Thoughts works great when:

• You need to plan ahead (like chess)
• There are many possible solutions
• You can easily judge if a path is good or bad

Real Prompt Example

Solve this step by step using Tree of Thoughts:
"How can I arrange 3 meetings in one day without conflicts?"

For each step:
1. Generate 3 possible approaches
2. Evaluate which is most promising
3. Continue with the best one
4. Backtrack if you hit a dead end

🕸️ Graph of Thoughts (GoT)

What Is It?

Tree of Thoughts is like branches that never touch. But what if ideas COULD connect to each other in any direction? That’s Graph of Thoughts!

Think of it like a spider web where:

• Ideas can connect to ANY other idea
• You can combine two different paths into one
• Thoughts can loop back and improve earlier ideas

Simple Example: Planning a Birthday Party

Problem: Plan a perfect birthday party.

Tree Approach (Ideas Stay Separate):

• Branch 1: Theme → Superhero → Costumes → Decorations
• Branch 2: Food → Pizza → Need plates → Paper plates

Graph Approach (Ideas Connect!):

• Superhero theme CONNECTS TO food idea = Superhero-themed pizza boxes!
• Decorations COMBINES WITH paper plates = Superhero-printed plates!

graph TD
    A["Party Planning"] --> B["Theme: Superhero"]
    A --> C["Food: Pizza"]
    A --> D["Decorations"]
    B --> E["Costumes"]
    C --> F["Pizza Boxes"]
    D --> G["Paper Plates"]
    B -.->|combine| F
    B -.->|combine| G
    F --> H["Superhero Pizza Boxes!"]
    G --> I["Superhero Plates!"]
    style H fill:#FFB6C1
    style I fill:#FFB6C1

When To Use It

Graph of Thoughts shines when:

• Ideas can improve each other
• You need to merge different solutions
• The problem has interconnected parts

Real Prompt Example

Use Graph of Thoughts to solve this:
"Design a study schedule for 3 subjects."

Instructions:
1. Generate ideas for each subject separately
2. Find connections between subjects
3. Merge related ideas into better solutions
4. Refine by connecting new insights back

📦 Buffer of Thoughts (BoT)

What Is It?

Imagine you have a magic notebook. Every time you solve a problem, you write down the RECIPE for solving it. Next time you see a similar problem, you just look in your notebook!

Buffer of Thoughts = A saved library of “thought templates” the AI can reuse.

Simple Example: Cooking Dinner

Without Buffer (Starting Fresh):

“How do I make pasta? Let me think… boil water… add pasta… how long? I don’t know…”

With Buffer (Using Saved Knowledge):

“Pasta? I have a template for that! Template: COOKING-BOIL Step 1: Boil water Step 2: Add food Step 3: Wait (pasta = 10 min) Step 4: Drain Done!”

How It Works

graph TD
    A["New Problem"] --> B{Similar to saved template?}
    B -->|Yes| C["Load Template"]
    B -->|No| D["Solve from scratch"]
    C --> E["Apply Template"]
    E --> F["Solution!"]
    D --> G["Create New Template"]
    G --> H["Save to Buffer"]
    H --> F
    style C fill:#98FB98
    style H fill:#87CEEB

The Three Parts of Buffer of Thoughts

1. Problem Distiller - Looks at the new problem and figures out what TYPE it is
2. Meta Buffer - The library of saved thought templates
3. Buffer Manager - Picks the best template and applies it

When To Use It

Buffer of Thoughts is perfect when:

• You solve similar problems often
• Speed matters (templates are faster!)
• You want consistent, reliable answers

Real Prompt Example

Using Buffer of Thoughts approach:

First, identify what type of problem this is:
"Calculate 15% tip on a $45 meal"

Then apply the appropriate template:
- PERCENTAGE-CALCULATION template:
  1. Convert percent to decimal (÷100)
  2. Multiply by the amount
  3. Round if needed

Result: 15 ÷ 100 = 0.15 × 45 = $6.75

🧵 Thread of Thought (ThoT)

What Is It?

Imagine you’re trying to read a book, but your little sibling keeps asking random questions. Thread of Thought teaches you to:

1. Stay focused on the MAIN question
2. Handle interruptions without getting lost
3. Come back to what matters

It’s like having a FOCUS SUPERPOWER for messy, confusing problems!

Simple Example: The Noisy Classroom

Problem: “What’s 5 + 3? Also, the sky is blue. And cats say meow. Back to math - what’s the answer?”

Without Thread of Thought:

“5 + 3… wait, sky is blue? Cats? I’m confused… what was the question?”

With Thread of Thought:

"Let me focus on what matters…

• MAIN THREAD: Math question (5 + 3)
• Ignore: Sky color (not relevant)
• Ignore: Cat sounds (not relevant)
• ANSWER: 5 + 3 = 8"

How It Works

graph TD
    A["Messy Input"] --> B["Identify Main Thread"]
    B --> C["Filter Out Noise"]
    C --> D["Focus on Key Info"]
    D --> E["Clear Answer"]
    style B fill:#FFD700
    style C fill:#FF6B6B
    style E fill:#90EE90

The Magic Words

Thread of Thought uses a special phrase to stay focused:

“Walk me through this context in manageable parts step by step, summarizing and analyzing as we go.”

This magic sentence helps the AI:

• Break down confusing information
• Keep track of what’s important
• Ignore the noise

When To Use It

Thread of Thought saves the day when:

• The problem has lots of irrelevant information
• Context is long and confusing
• You need to find the needle in the haystack

Real Prompt Example

Using Thread of Thought, analyze this:

"My car is red. I need to get to the airport
by 3 PM. Traffic is usually bad on Mondays.
My favorite food is pizza. The airport is
30 miles away. I like jazz music."

Focus thread: Getting to airport on time
Relevant: 3 PM deadline, traffic, 30 miles
Ignore: Car color, food, music

Analysis: Leave early due to Monday traffic!

🎯 Quick Comparison: Which Shape Should I Use?

🌟 The Family Portrait

All these techniques are part of the “Chain-of-Thought Family” - they all help AI think STEP BY STEP, but in different SHAPES:

graph TD
    A["Chain-of-Thought Family"] --> B["Tree of Thoughts"]
    A --> C["Graph of Thoughts"]
    A --> D["Buffer of Thoughts"]
    A --> E["Thread of Thought"]
    B --> B1["Branches & Backtracks"]
    C --> C1["Web of Connections"]
    D --> D1["Template Library"]
    E --> E1["Focus Filter"]
    style A fill:#FFD700

💡 Remember This!

• Tree = Explore branches, go back if stuck 🌲
• Graph = Connect ideas like a spider web 🕸️
• Buffer = Use saved recipes for speed 📦
• Thread = Stay focused, ignore noise 🧵

You now understand how AI can think in DIFFERENT SHAPES to solve different problems. That’s pretty amazing!

🚀 Try It Yourself!

Next time you face a tricky problem, ask yourself:

• Should I explore multiple paths? (Tree)
• Can my ideas connect and improve each other? (Graph)
• Have I solved something like this before? (Buffer)
• Is there lots of noise I need to filter out? (Thread)

Pick the right shape, and watch your problem-solving superpowers grow!