AI Workflow ArchitectureMaster PromptExpert

Multi-Agent Workflow Designer

Design a multi-agent workflow that produces better work with fewer handoffs — practical enough to implement this week, not abstract theory.

Best ModelChatGPT GPT-5.5 Thinking / Claude Opus 4.7Workflow architecture
Brevity ModeExhaustive
DifficultyExpert
AutomationNeeds user context

Use This When

Scaling agency delivery with AI, productizing internal workflows, designing internal tools, when one prompt isn't enough.

Inputs Needed

Process goal, team roles, tools, inputs, output, approval rules.

Expected Output

Workflow map, agent roles, prompts, handoffs, QA gates, tooling, implementation plan, maintenance rules.

The Workflow Prompt

prompt.md21 lines
You are a AI workflow architect and agency operations consultant.

Objective:
Design a multi-agent workflow that produces better work with fewer handoffs.

Inputs I will provide:
Business process, input sources, team roles, tools, output requirements, review rules, bottlenecks, risks.

Instructions:
- Start by identifying the business objective and the likely leverage point.
- Ask up to 5 focused questions only if required. If enough context exists, proceed and label assumptions.
- Produce client-ready work, not generic advice.
- Use concrete examples, templates, and priority order.
- Mention risks, dependencies, and what must be verified before launch.
- End with a short QA checklist and next 3 actions.

Required output:
Workflow map, agent roles, prompts, handoffs, QA gates, tooling, implementation plan, maintenance rules.

Quality bar:
The workflow should be practical enough to implement this week.
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QA Follow-Up Checklist

After the AI returns its output, verify against:

  1. 1Output is specific to the provided business and context.
  2. 2Assumptions are clearly labeled.
  3. 3No unsupported claims without source checks.
  4. 4Next actions are clear and usable.

Follow-Up Prompt

refinementRun after first output
Now turn the result for 'Multi-Agent Workflow Designer' into a client-ready version: tighten wording, remove fluff, add missing assumptions, and provide the next 3 actions.

Avoid / Cautions

Avoid generic output. Push the model for concrete agent roles, prompts, and handoffs grounded in the actual workflow — not best-practice clichés.

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