When you ask an AI to do everything at once ("research, outline, write and format a 2,000-word report"), quality drops. Prompt chaining fixes this by turning one big request into several small ones.
How it works
Each prompt does one job, and its output becomes the input for the next. You review each step before moving on, so mistakes don't snowball.
An example chain for a blog post
- Research: "List the 10 questions readers ask about [topic]."
- Angle: "Suggest 3 unique angles. Recommend one."
- Outline: "Create an outline for angle 2 with H2s and key points."
- Draft: "Write section 1 using these notes: [notes]."
- Edit: "Tighten this draft by 20% and improve the intro."
Why it works
- Each step gets the model's full attention.
- You can correct direction early.
- It's easier to see which step caused a problem.
- You can reuse steps as templates.
Chains for other tasks
- Data: clean → summarise → find insights → write recommendations
- Code: spec → plan → write → test → review
- Marketing: persona → angles → headlines → ad copy
Tips
Keep a document with your best chains. Paste the key output from the previous step into the next prompt rather than relying on the AI's memory of a long chat.