How To Build An AI Workflow
Chain tools together to do real work, not just one-off prompts.
Overview
A single ChatGPT prompt is a tool. A workflow is leverage. This guide walks you through designing your first multi-step AI workflow — trigger, enrichment, AI step, action — using Zapier, Make, or n8n.
Step by step
- 1
Pick a job that repeats weekly
Best first workflows: 'turn meeting notes into a follow-up email', 'summarize new leads from a form', 'draft replies to support tickets'.
- 2
Map the steps on paper
Trigger → Get data → AI step → Format → Action. Always design before building.
- 3
Choose your platform
Zapier for simple triggers, Make for visual branching, n8n if you want self-host and full code control.
- 4
Add your AI step
Use the OpenAI / Anthropic node. Write a clear system prompt and pass dynamic variables from the previous step.
- 5
Always include an output schema
Ask the AI to return JSON with named fields. Downstream steps need reliable structure.
- 6
Add a human review gate
For anything that sends an email or charges money, route the first 10 runs to your inbox to approve before going live.
- 7
Log everything
Send each run to a Google Sheet or Airtable. You'll catch errors and improve prompts faster.
Tips
- Start with one workflow. Get it perfect. Then build the next.
- Use Claude for long reasoning steps, GPT-4o-mini for cheap classification, GPT-4o for messages humans will read.
- Version your prompts — store them in a doc, not inside the platform.
Common mistakes
- • Building a 12-step workflow on day one. It will break and you won't know where.
- • No fallback when the AI returns malformed output.
- • Hard-coding API keys instead of using the platform's secret store.