Productivity LLM Prompts Easy Automation Ready

Science-Backed Morning Routine Builder

Helps you design a neuroscience-based, highly personalized morning routine by analyzing your habits, goals, and constraints, then giving you tailored routines and an implementation plan.

Best Model
ChatGPT GPT-5.5 / Claude Sonnet 4.6SOP and workflow building
Brevity Mode
Standard
Difficulty
Easy
Automation
Yes

Use This When

SOPs, task systems, delegation, automation mapping.

Inputs Needed

Current workflow, tools, people involved, bottleneck, desired output, frequency, approval rules.

Expected Output

Workflow map, SOP, automation opportunities, owner/RACI, tools, checklist, maintenance cadence.

The Workflow Prompt

Copy-paste ready. Replace [bracketed placeholders] with your specifics.
You are a operations consultant and productivity systems designer.

Objective:
Science-Backed Morning Routine Builder

Context:
Helps you design a neuroscience-based, highly personalized morning routine by analyzing your habits, goals, and constraints, then giving you tailored routines and an implementation plan.

Original task:
Describe the neuroscience behind morning routines and why the first 90 minutes after waking disproportionately affect daily productivity. Then list five common morning routine mistakes that sabotage energy and focus (such as checking email immediately or skipping breakfast), explaining the specific negative impact of each mistake on cognitive performance throughout the day.

Inputs I may provide:
Current workflow, tools, people involved, bottleneck, desired output, frequency, approval rules.

Operating instructions:
- First, restate the objective in one clear sentence.
- If critical information is missing, ask up to 5 focused questions. If there is enough information to proceed, make practical assumptions and label them.
- Use a Standard response style.
- Be specific to the business, audience, channel, and constraints provided.
- Avoid generic AI advice. Give concrete recommendations, examples, templates, copy, or steps I can use.
- When current facts, competitors, laws, prices, policies, or market claims matter, use current research and cite sources.
- Do not expose hidden chain-of-thought. Provide a concise rationale or decision summary instead.
- End with a short QA checklist that helps me verify the output.

Required output:
Workflow map, SOP, automation opportunities, owner/RACI, tools, checklist, maintenance cadence.

Caution:
Avoid generic output; require concrete examples, assumptions, and next steps.

QA Follow-Up Checklist

After the AI returns its output, verify against:

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

Follow-Up Prompt

Run this next to refine the first output into a client-ready version.
Now turn the result for 'Science-Backed Morning Routine Builder' into a client-ready version: tighten wording, remove fluff, add missing assumptions, and provide the next 3 actions.

Avoid / Cautions

Avoid generic output; require concrete examples, assumptions, and next steps.

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