One-liner: Build a multi-step AI workflow where each step's output feeds into the next — turning a complex task into a repeatable pipeline.
Pick a task that has at least 3 distinct phases. Examples: writing a blog post (research, outline, draft, edit), analyzing a dataset (clean, analyze, summarize, recommend), or preparing a presentation (topic research, slide structure, talking points, Q&A prep).
Build a 3-step chain. Each step is a separate prompt. The output of each step becomes the input of the next.
Step 1 — Research/Gather:
You are a research assistant. Your job is to gather the raw material for [your task].
Topic/context: [describe what you're working on]
Produce a structured collection of: key facts, relevant examples, important considerations, and any constraints. Organize by theme. Do not draft anything — just collect the ingredients.
Copy the output. Start a new prompt (or clearly reset context).
Step 2 — Structure/Draft:
You are a content architect. Your job is to turn raw research into a structured draft.
Here is the research material: [paste Step 1 output]
The final deliverable is: [describe what you need — a blog post, a report, a strategy doc, etc.]
Create a structured draft. Include clear sections, key arguments in order, and placeholders for any examples or data points from the research. Focus on logical flow and completeness.
Copy the output. Start a new prompt.
Step 3 — Polish/Critique:
You are a senior editor. Your job is to make this draft publication-ready.
Here is the draft: [paste Step 2 output]
The audience is: [describe who will read this]
Do three things:
- Improve clarity — simplify any convoluted sentences, cut unnecessary words
- Strengthen weak points — flag any claim that needs better support and add it
- Check consistency — ensure tone, terminology, and formatting are uniform throughout
Produce the final version with an editor's note listing your key changes.
Now document the chain. Write down the 3 prompts as a reusable template (with [PLACEHOLDERS] for the parts that change). You've just built a prompt pipeline.
Here's what you're about to do:
"Done" looks like: A completed deliverable that went through a 3-step pipeline, plus a documented prompt chain template with placeholders for reuse.
In WA-Basic-01, you built a single reusable prompt. Here, you're learning to chain prompts into a workflow — the building block of all production AI automation. Every AI-powered pipeline (content generation, data analysis, document processing) is fundamentally a prompt chain with handoffs. The skill you're building — decomposing a task into stages, defining clear inputs and outputs, managing context between steps — is the same skill used in tools like n8n, Zapier AI, or custom LLM pipelines. Manual chaining teaches you what to automate and where the bottlenecks live.
Ready for more? Try WA-Advanced-01 — where you'll design and document a complete AI-automated workflow for a business process.
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