One-liner: Design, document, and test a complete AI-automated workflow for a real business process — from trigger to output, with error handling and quality gates.
Pick a real business process that currently takes you 30+ minutes and involves multiple steps. Examples: weekly reporting, content production, customer onboarding documentation, project status updates, invoice processing.
Phase 1 — Map the current process. Send this:
I'm going to automate this business process: [describe the process].
Help me map the current manual workflow:
- What triggers the process? (time-based, event-based, request-based)
- What are the sequential steps from trigger to final output?
- What inputs does each step require?
- What decisions are made at each step? (if/then logic)
- Where are the bottlenecks or error-prone points?
- What's the final deliverable and who receives it?
Present this as a numbered workflow with decision points marked.
Phase 2 — Design the AI workflow. Send:
Now redesign this as an AI-automated workflow. For each step, specify:
Step Human or AI? If AI: what prompt template? If Human: what decision? Input Output Quality gate Rules:
- Some steps should remain human (judgment calls, approvals, sensitive decisions)
- Every AI step needs a quality gate — how do you know the output is good enough to proceed?
- Include error handling — what happens when an AI step produces bad output?
- Include a feedback mechanism — how does the workflow improve over time?
Phase 3 — Write the prompt templates. For each AI step in the workflow:
Write the production-ready prompt template for Step [N]: [step name]
The template should include:
- Role definition for the AI
- Clear input specification with [PLACEHOLDERS]
- Exact output format requirements
- Quality criteria the output must meet
- An example of good output vs. bad output
This prompt should work reliably every time with different inputs. It should be usable by someone who didn't design the workflow.
Phase 4 — Run the workflow end-to-end. Execute the full pipeline with real data. Track:
Phase 5 — Document the blueprint. Create a 1-page workflow document:
Write a "Workflow Blueprint" for this process that includes:
- Trigger: What starts the workflow
- Flow diagram: Step-by-step with decision points (use text-based flowchart)
- Prompt templates: Reference to each template (step number and name)
- Quality gates: What to check at each stage
- Error handling: What to do when something fails
- Maintenance: How to update the workflow as requirements change
- Metrics: How to measure whether the workflow is working well
Here's what you're about to do:
"Done" looks like: A complete, tested workflow blueprint with prompt templates, quality gates, and measured time savings. Something you could hand to a colleague and they could execute without additional explanation.
In WA-Intermediate-01, you built a 3-step prompt chain. Here, you're building a production-grade workflow — the kind of thing that saves hours per week and can be delegated. The key differences from an intermediate prompt chain: quality gates (not just chaining outputs blindly), error handling (what happens when AI fails), and documentation (others can run it without you). This is directly transferable to tools like n8n, Make, or Zapier with AI steps. The blueprint format is also the deliverable that organizations pay consultants to produce.
You've reached the advanced level for Workflow Automation. From here, consider:
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