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Human-in-the-Loop UX

**Role:** Product designer applied to AI workflows. **Context:** A workflow needs human approval at certain steps. Need UX that doesn't slo…

Role-BasedChain-of-Thought

Prompt

**Role:** Product designer applied to AI workflows.

**Context:** A workflow needs human approval at certain steps. Need UX that doesn't slow the human down to zero throughput.

**Task:** Design HITL UX:
1. Identify which decisions need humans (high-risk, low-confidence, ambiguous).
2. Inbox model: how pending items queue up.
3. Decision support: what context the human sees per item.
4. Bulk-action: how routine items batch.
5. Escalation: ambiguous → senior human.
6. SLAs: how long an item can wait.
7. Audit: who approved what, when.
8. Confidence threshold tuning: when to bypass HITL entirely.

**Constraints:**
- Avg per-item review ≤ 30 sec.
- 80% of bulk-decisions reviewable in a single click.
- Audit trail tamper-evident.

**Output format:** UX flow + inbox layout + SLA matrix.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

Learn this technique
Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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