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Overview

In this lesson, you will learn:

• What prompt chaining is and why it matters
• How to link multiple prompts to solve complex tasks
• Beginner-friendly ways to design prompt chains
• Practical examples for reasoning, summarization, coding, and workflow automation

By the end, you will know how to create multi-step prompt workflows for more sophisticated AI outputs.

💡 Key Concepts

• Prompt Chaining: Breaking a complex task into smaller sub-tasks, each handled by its own prompt, then linking outputs.
• Sequential Reasoning: Each prompt uses the previous prompt’s output to move forward.
• Improved Accuracy & Structure: Complex problems are easier to solve when broken into steps.
• Beginner-Friendly Approach: Even simple prompt chains can automate multi-step reasoning or actions.

🧠 Concept Explanation

1. What is Prompt Chaining?

Sometimes a single prompt is not enough for a multi-step task. Prompt chaining solves this by:

1. Dividing the main task into smaller sub-tasks
2. Creating a separate prompt for each sub-task
3. Feeding the output of one prompt into the next

Example – Writing a Report:

Step 1 Prompt: Summarize the first paragraph.  
Step 2 Prompt: Summarize the second paragraph.  
Step 3 Prompt: Combine summaries into a single concise report.

• This improves accuracy, readability, and reasoning.

2. Why Prompt Chaining Matters

• Handles multi-step reasoning or tasks that a single prompt can’t manage
• Reduces errors by isolating each step
• Makes outputs structured and predictable
• Beginner tip: Start with 2–3 linked prompts, then expand chains gradually

3. Beginner-Friendly Strategies

1. Break tasks logically: Summarization → analysis → recommendation
2. Use outputs from previous prompts as input to the next
3. Combine with CoT or ReAct for each step
4. Iterate and refine: Adjust prompt clarity or format based on AI output
5. Use roles if tone or style matters

🧩 Practical Examples

Example 1: Summarization Chain

Prompt 1: Summarize paragraph 1 in one sentence.  
Prompt 2: Summarize paragraph 2 in one sentence.  
Prompt 3: Combine both summaries into a 3-sentence overview.  
Output: Clear, concise multi-paragraph summary.

Example 2: Coding Task Chain

Prompt 1: Write a Python function to reverse a string.  
Prompt 2: Write a function to capitalize each word in the string.  
Prompt 3: Combine both functions into one final program.  
Output: Fully working Python code with both functionalities.

Example 3: Workflow Automation Chain

Prompt 1: Extract tasks from email.  
Prompt 2: Prioritize tasks.  
Prompt 3: Generate a to-do list in bullet points.  
Output: Structured, actionable task list.

⚙️ Tools for Beginners

• ChatGPT / OpenAI Playground: Manually link outputs between prompts
• Replit / Jupyter Notebook: Automate prompt chaining using Python scripts
• LangChain (later in Builder Zone): For fully automated multi-step chains

🧭 Step-by-Step Beginner Activity

1. Pick a multi-step problem: summarization, coding, or email task.
2. Break it into 2–3 sub-tasks.
3. Write a separate prompt for each sub-task.
4. Pass outputs from one prompt to the next.
5. Compare single-prompt vs. chained output for clarity and accuracy.

📝 Exercises

1. Summarize a 3-paragraph article using 3 linked prompts.
2. Solve a coding task in 2 steps: generate function → test it with sample input.
3. Create a workflow chain for an email inbox: extract tasks → categorize → generate a daily plan.
4. Experiment with combining CoT + ReAct in each step of your chain.

🔍 Summary & Key Takeaways

• Prompt chaining links multiple prompts to solve multi-step tasks.
• Break problems into logical sub-tasks for better structure and accuracy.
• Use outputs from one prompt as input to the next.
• Combine with CoT and ReAct for improved reasoning and action.
• Beginner-friendly chains lay the foundation for advanced workflows and automation in the Builder Zone.