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You’ve mastered writing individual prompts—now it’s time to tackle bigger business challenges by connecting multiple prompts together. Think of this as upgrading from single tasks to complete workflows.

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What is Prompt Chaining?

Prompt chaining is like creating a work process—each step builds on the previous one to create a complete solution. Instead of asking AI to do everything at once, you guide it through a logical sequence of steps, just like you would with a human team member.

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Simple Example:

Instead of: “Analyze this sales report and create a presentation for executives” Try this approach:
  1. Step 1: “Summarize the key findings from this sales report”
  2. Step 2: “Based on these findings: [paste summary], identify the top 3 issues executives should focus on”
  3. Step 3: “Create presentation talking points for these 3 issues: [paste issues]“

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Why Use Prompt Chaining?

Better Results

• AI focuses on one task at a time
• Each step builds on quality output
• Easy to catch and fix mistakes early

More Control

• See exactly what AI is thinking
• Adjust the process as you go
• Break complex tasks into manageable steps

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Planning Your Prompt Chain

Before you start, think about how you’d solve this problem yourself:
  1. Map the Process
    What would an expert do step-by-step to complete this task?
  2. Find Natural Break Points
    Where does one logical step end and another begin?
  3. Plan the Handoffs
    What information needs to pass from one step to the next?

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Common Business Workflow Patterns

  • Analysis Workflow
  • Creation Workflow
  • Decision Workflow
  • Action Workflow
Best for: Research, data analysis, strategic planningPattern: Gather → Analyze → Synthesize → RecommendExample: Competitive Analysis
  1. Gather: “Extract key features and pricing from these competitor websites”
  2. Analyze: “Compare our features against these competitors: [paste data]”
  3. Synthesize: “Based on this comparison, identify our top 3 competitive advantages and disadvantages”
  4. Recommend: “Create specific recommendations for addressing these competitive gaps: [paste analysis]”

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Advanced Chaining Techniques

Sometimes you need different paths based on intermediate results:Main Chain: Analyze → Assess Risk Level → Branch
  • If High Risk: Escalation Protocol → Crisis Response Plan
  • If Medium Risk: Monitoring Plan → Regular Updates
  • If Low Risk: Standard Process → Routine Follow-up
Run multiple chains simultaneously, then combine results:Chain A: Technical Analysis → Technical Recommendations Chain B: Business Analysis → Business Recommendations
Synthesis: Combine both recommendations → Final Strategic Plan
Refine results through multiple cycles:
  1. Draft → Review → Revise → Final Draft
  2. Repeat until quality meets standards

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Quality Control in Prompt Chains

Check Each Step

When reviewing each step, ensure the output makes sense, contains all necessary information for the next step, and includes no missing key details.

Maintain Consistency

Keep the same role/perspective when appropriate, ensure context carries forward properly, and watch for contradictions between steps.

Document Your Process

Save successful chains as templates, note what works well for different types of tasks, and track where chains typically break down.

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Common Chaining Mistakes

Problem: Trying to do too much in each step
Solution: Break large steps into smaller, focused tasks
Problem: Not providing enough context between steps
Solution: Include relevant context from previous steps
Problem: Later steps diverge from the original goal
Solution: Occasionally remind AI of the overall objective
Problem: Creating unnecessary steps that don’t add value
Solution: Test if fewer steps produce similar results

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When to Chain vs. Single Prompts

Use Chaining When

• Task has multiple logical phases
• You need to verify intermediate results
• Process is complex or high-stakes
• You want maximum control over output

Use Single Prompts When

• Task is straightforward
• You need quick results
• Risk of errors is low
• Chaining adds unnecessary complexity
Start with simple 2-3 step chains, then gradually tackle more complex business processes as you build confidence. The key is thinking systematically about how work gets done, then translating that logic into a series of connected prompts that guide AI through the same expert process a human would follow.
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