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.Simple Example:
Instead of: “Analyze this sales report and create a presentation for executives” Try this approach:- Step 1: “Summarize the key findings from this sales report”
- Step 2: “Based on these findings: [paste summary], identify the top 3 issues executives should focus on”
- Step 3: “Create presentation talking points for these 3 issues: [paste issues]“
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
• 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
• Adjust the process as you go
• Break complex tasks into manageable steps
Planning Your Prompt Chain
Before you start, think about how you’d solve this problem yourself:-
Map the Process
What would an expert do step-by-step to complete this task? -
Find Natural Break Points
Where does one logical step end and another begin? -
Plan the Handoffs
What information needs to pass from one step to the next?
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
- Gather: “Extract key features and pricing from these competitor websites”
- Analyze: “Compare our features against these competitors: [paste data]”
- Synthesize: “Based on this comparison, identify our top 3 competitive advantages and disadvantages”
- Recommend: “Create specific recommendations for addressing these competitive gaps: [paste analysis]”
Advanced Chaining Techniques
Branching Chains
Branching Chains
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
Parallel Chains
Parallel Chains
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
Synthesis: Combine both recommendations → Final Strategic Plan
Iterative Chains
Iterative Chains
Refine results through multiple cycles:
- Draft → Review → Revise → Final Draft
- Repeat until quality meets standards
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.
Common Chaining Mistakes
Steps Too Big
Steps Too Big
Problem: Trying to do too much in each step
Solution: Break large steps into smaller, focused tasks
Solution: Break large steps into smaller, focused tasks
Poor Handoffs
Poor Handoffs
Problem: Not providing enough context between steps
Solution: Include relevant context from previous steps
Solution: Include relevant context from previous steps
Losing the Thread
Losing the Thread
Problem: Later steps diverge from the original goal
Solution: Occasionally remind AI of the overall objective
Solution: Occasionally remind AI of the overall objective
Over-Chaining
Over-Chaining
Problem: Creating unnecessary steps that don’t add value
Solution: Test if fewer steps produce similar results
Solution: Test if fewer steps produce similar results
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
• 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
• 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.