Prompt Chaining
Prompt chaining means breaking one big task into smaller connected steps. Each step does one job, and its output becomes the input for the next.
This is a simple learning demo. The AI outputs below are predefined to show the idea, not a real AI model.
Small steps, connected together
Imagine cooking a big meal. You don't do everything in one motion, you chop, then cook, then plate. Each step builds on the last. Prompt chaining works the same way with AI.
Instead of one giant prompt, you write a series of small prompts. The answer from step 1 is handed to step 2, step 2's answer goes to step 3, and so on, until the task is done.
Too much at once is hard to control
When you ask for everything in a single prompt, the AI has to juggle many goals at the same time. That is where things slip:
Same goal, two ways to get there
Goal: write a blog post about AI safety. Compare doing it in one shot versus a chain of steps.
“Write a complete blog post about AI safety.”
- ✕ Tries to do outline, writing, editing, and title all at once.
- ✕ Weak spots are hard to fix without redoing everything.
- ✕ Quality is uneven, some parts thin, some off-topic.
Outline → expand → polish → title → summary.
- ✓ Each step has one clear, easy job.
- ✓ You can check and fix a single step, not the whole post.
- ✓ Every part gets proper attention, so quality is steadier.
Watch output flow from step to step
Run the chain one step at a time. Each step takes the previous step's output as its input, until the task is complete. Hit Try another task to see the same idea on a different job.
Reach for a chain when…
- • Prompt chaining = splitting a big task into small connected steps.
- • Each step's output becomes the next step's input.
- • Chains give you more control, fix one step, not the whole task.
- • Quality is steadier because each step has one clear job.
- • Use chains for big, multi-stage tasks; keep simple tasks as one prompt.