2. Prompt Chaining

Mini-Project: Blog Post Refiner

A prompt chain that drafts, critiques, and polishes a blog post through sequential LLM steps.

View on GitHub

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Description

Prompt Chaining decomposes a task into a fixed sequence of steps, where each LLM call processes the output of the previous one. Each step is a focused, well-defined subtask with its own prompt, and the output of one step feeds directly into the next.

When to Use

• Tasks that can be cleanly decomposed into sequential subtasks
• When each step benefits from a specialized prompt
• Workflows where intermediate validation is needed (e.g., generate then verify)
• Data transformation pipelines (extract -> transform -> summarize)

Benefits

Benefit	Description
Reliability	Each step has a focused prompt, reducing errors
Debuggability	Easy to pinpoint which step failed
Quality Control	Each step's output can be validated before passing forward
Modularity	Steps can be independently tested and improved

Architecture Diagram

flowchart LR
    A[User Input] --> B[Step 1: Generate Draft]
    B --> C[Step 2: Analyze Draft]
    C --> D[Step 3: Finalize]
    D --> E[Final Output]

    style A fill:#4CAF50,color:#fff
    style B fill:#2196F3,color:#fff
    style C fill:#2196F3,color:#fff
    style D fill:#2196F3,color:#fff
    style E fill:#4CAF50,color:#fff