Ai Workflow Designer

---
name: ai-workflow-designer
description: "Design an AI-assisted workflow for a recurring task — which steps to hand to AI, which to keep human, and how they connect — so you get leverage without losing quality or control. Use when asked how do I use AI for [process], automate this with AI, design an AI workflow, or where does AI fit in my process. Produces a map of the task's steps split into AI-does / human-does / human-checks, the right tool/prompt for each AI step, the hand-offs and review points, the failure modes to guard against, and a start-small rollout — turning a manual process into a reliable AI-assisted one that keeps you in control."
homepage: https://mohitagw15856.github.io/pm-claude-skills/skill/ai-workflow-designer.html
metadata:
  {
    "openclaw": { "emoji": "🧠" }
  }
---

# AI-Workflow Designer

The mistake people make with AI is bolting it onto a task randomly — or trying to fully automate something that needs judgment, then losing trust when it goes wrong. Real leverage comes from designing the workflow: deciding which steps AI does well, which need a human, and where the checkpoints are. This maps that for your recurring task, so you get the speed of AI with the reliability of human judgment where it matters — and you stay in control.

## What This Skill Produces

- **The step map** — the task broken into steps, each labeled: 🤖 AI does it · 🧑 human does it · ✅ human checks it (AI drafts, human approves)
- **The right tool/prompt per AI step** — what to use and how to prompt it for each automated step
- **Hand-offs & checkpoints** — how outputs pass between steps and where the human review points are (so errors are caught, not propagated)
- **Failure modes & guards** — where this workflow could go wrong (AI errors, hallucination, edge cases) and the checks that catch them
- **A start-small rollout** — how to introduce it incrementally and build trust before relying on it
- **The keep-human line** — the steps that should stay human (judgment, relationships, high-stakes calls) and why

## Required Inputs

Ask for these if not provided:
- **The task/process** — the recurring thing you want AI to help with
- **The current steps** — how you do it now, manually
- **The stakes** — how much errors cost (drives how many human checkpoints)
- **Your tools** — the AI tools/access you have
- **Your comfort** — how much you want to automate vs. keep hands-on

## Framework: Split The Steps, Check The Seams

1. **Map the current steps.** Lay out how the task is done now — you can't design the AI version without seeing the manual one.
2. **Sort each step.** For each: is it something AI does reliably (drafting, summarizing, extracting, transforming), something needing human judgment (decisions, relationships, high-stakes), or something AI drafts and a human approves?
3. **Pick tools and prompts.** For each AI step, the right tool and a reliable prompt (often from a prompt library) — so the step works consistently.
4. **Design the seams.** Where outputs hand off between steps is where errors hide — add review checkpoints at the seams, especially before anything irreversible or external-facing.
5. **Guard the failure modes.** Name where AI could err (wrong facts, edge cases, confident nonsense) and the specific check that catches it before it matters.
6. **Roll out small.** Start with the low-risk steps, verify the quality, and expand — building trust rather than automating everything and hoping.
7. **Keep humans where it counts.** Be clear which steps should stay human — judgment, empathy, and high-stakes calls aren't candidates for automation.

## Output Format

### AI workflow: [the task]

**Step map**
| Step | Who | Tool/prompt (if AI) |
|---|---|---|
| [step] | 🤖 AI / 🧑 human / ✅ AI-drafts-human-approves | |

**Checkpoints:** [human review points — esp. before irreversible/external steps].
**Failure modes & guards:** [where AI could err → the check that catches it].
**Keep human:** [the judgment/relationship/high-stakes steps] — and why.
**Roll out:** [start with low-risk steps → verify → expand].

## Quality Checks
- [ ] Maps the current manual steps first
- [ ] Sorts each step into AI / human / AI-drafts-human-approves
- [ ] Assigns the right tool/prompt to each AI step
- [ ] Puts review checkpoints at the hand-off seams
- [ ] Names failure modes and specific guards
- [ ] Keeps human judgment steps human; rolls out incrementally

## Anti-Patterns
- **Bolting AI on randomly** with no step analysis.
- **Fully automating** a task that needs judgment.
- **No checkpoints** at the seams — errors propagate.
- **Ignoring failure modes** until something breaks.
- **Big-bang automation** instead of a trust-building rollout.

## Example Trigger Phrases
- "How do I use AI for my weekly reporting process?"
- "Design an AI-assisted workflow for handling customer emails."
- "Where does AI fit in my content process, and where shouldn't it?"
- "Help me automate part of this task with AI without losing control."
- "Map out an AI workflow for my recurring [task]."