🔗 Chains and Processes
Master prompt chaining and complex workflows. Connect prompts to solve sophisticated problems.
1. Task Decomposition
Break down complex problems
Complex tasks produce better results when broken down into smaller, focused subtasks.
❌ Single complex task:
"Analyze this document, extract data, create a summary, and generate recommendations"
✓ Decomposed tasks:
1. "Extract the key data from this document"
2. "Analyze the extracted data and identify patterns"
3. "Create an executive summary of the analysis"
4. "Generate 5 recommendations based on the summary"
✓ Benefits
Greater accuracy, easier debugging, component reuse
🎯 When to Use
Tasks with multiple steps or types of processing
2. Prompt Chaining
Connect prompts in sequence
The output of one prompt feeds into the next prompt’s input. Create processing pipelines.
Prompt 1
Extraction
Prompt 2
Analysis
Prompt 3
Synthesis
💡 Tip
Keep each prompt focused on a single responsibility. This makes maintenance and debugging easier.
3. Multi-Step Prompts
Multiple phases in one prompt
Guide the model through sequential phases within a single prompt.
# Multi-Step Prompt
Execute the following steps in order:
**STEP 1 - ANALYSIS:**
Identify the 3 main problems in the text.
**STEP 2 - PRIORITIZATION:**
Sort by impact (high/medium/low).
**STEP 3 - SOLUTIONS:**
Propose a solution for each problem.
4. Plan → Execute → Review
3-Phase Framework
Separate planning from execution for more consistent results.
1️⃣ PLAN
"Create a detailed plan to solve [X]. Don't execute it yet."
2️⃣ EXECUTE
"Execute the plan above step by step."
3️⃣ REVIEW
"Review the execution and identify improvements."
5. Iterative Refinement
Improve through cycles
Use the output as a basis for refinement in subsequent cycles.
# Refinement Cycle
Prompt 1: "Write a draft about [X]"
Prompt 2: "Improve this text, focusing on [CRITERION]"
Prompt 3: "Refine it again, taking [FEEDBACK] into account"
6. Context Control in Chains
Manage information across prompts
Decide what to pass along and what to discard to optimize tokens and focus.
Summarize before passing
Summarize long outputs before passing them to the next prompt.
Extract key entities
Extract only entities relevant to the next step.
State management
Keep "state" structured (JSON) between calls.
7. Structured Practical Cases
Real-World Workflows
📝 Content Pipeline
Research → Outline → Draft → Edit → SEO
📊 Data Analysis
Extract → Clean → Analyze → Visualize → Report
💻 Code Review
Scan → Identify → Classify → Suggest → Document
📧 Email Automation
Classify → Extract → Route → Draft → Send
🚀 Next: Module 4
Continue to Multimodal Prompting and master images, videos, and visual content!