Chain-of-Thought Prompting
What is chain-of-thought?
Chain-of-thought (CoT) prompting asks the AI to show its reasoning step by step before giving a final answer. Adding Think step by step or Let's reason through this dramatically improves accuracy on complex tasks.
Without CoT: How many days between Jan 15 and Mar 20? → Often wrong on edge cases.
With CoT: How many days between Jan 15 and Mar 20? Think step by step. → AI breaks it down: days remaining in January + all of February + days in March = correct answer.
When to use CoT
Use chain-of-thought when:
• The task involves multi-step reasoning (math, logic, planning)
• You need to verify the AI's logic, not just the answer
• The task requires weighing multiple factors
• You want to catch errors before they propagate
Don't use it for simple, factual, or creative tasks where step-by-step reasoning adds no value.
Prompt chains: connecting multiple prompts
A prompt chain is a sequence of prompts where each output becomes the input for the next.
Example chain for writing a blog post:
1. Generate 5 blog post ideas about AI tools for Arabic entrepreneurs. → pick one
2. Create a detailed outline for: [chosen title] → get structure
3. Write Section 1 based on this outline: [outline] → get draft
4. Review this draft for clarity and suggest 3 improvements: [draft] → refine
5. Translate this final version to Arabic: [refined draft] → localize
Each step is focused, making the overall result far better than one mega-prompt.
Key Takeaways
- Adding 'Think step by step' dramatically improves accuracy on complex tasks.
- Chain-of-thought lets you verify the AI's reasoning, not just the answer.
- Prompt chains break big tasks into focused steps — each output feeds the next.
- Use CoT for multi-step reasoning; skip it for simple tasks.
Build a 3-step prompt chain
Choose a task that's complex enough to need multiple steps (e.g., writing a business proposal, planning a content calendar, analyzing a problem). Design and run a 3-step chain.