Design an AI agent workflow for a repetitive task
Maps a repetitive task into steps an AI agent can do, which tools it needs, and where a human must approve before anything is sent.
I want to automate this repetitive task with an AI agent: {{TASK}}
Tools and apps involved: {{TOOLS}}
What could go wrong if it makes a mistake: {{RISK}}
Design the workflow:
1. Trigger: what starts it.
2. Steps: what the agent does at each step, and which tool it uses. Note which steps need tool access (via an integration, API or MCP server).
3. Decisions: where the agent must choose, and the rules for choosing.
4. Human checkpoints: every point where a person must approve, especially before sending, paying, deleting or publishing.
5. Guardrails: permissions to give (read only where possible), limits, and how to handle instructions found inside emails or documents.
6. Failure handling: what happens when data is missing or unclear.
7. How to test it on 10 real past examples before switching it on.
Keep it practical for a small team. Suggest the simplest version first.Example output
Trigger: new invoice email arrives. Agent steps: read PDF, extract fields, match to purchase order, draft entry in accounting tool. Human checkpoint: approve before posting. Tools: email (read only), accounting app (draft only).
How to use
Start with a task that is boring, frequent and low risk. Run the first version with approval on every step, then remove checkpoints only where the agent has been right every time.
Why it works
Agents work in loops of reasoning and acting with tools, so mapping each step to a tool and a decision rule makes the design concrete. Human checkpoints and least-privilege access are the guardrails that keep a wrong step from becoming an expensive one.