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Streamlined Meal Planning Automation

Dec 3, 2024

Automating Meal Planning with Make.com

Introduction

  • Presenter: Jason
  • Objective: Streamline meal planning for nutritionists and fitness coaches using Airtable and OpenAI GPT.
  • Key Benefits: Automates meal planning, creates personalized meal plans, generates shopping lists.

Components of the Workflow

Airtable Setup

  • Tables Used:
    • Client:
      • Fields:
        • Client ID: Created using a formula with concatenate function.
        • Status: Active/Inactive to filter clients.
        • Contact Details: Email, mobile number.
        • Diet Preferences: Vegan, low-carb, vegetarian, dairy-free, Mediterranean.
        • Goals: Caloric intake, macronutrient ratios.
        • Type: Duration and meals covered (e.g., 7 days, breakfast, lunch, dinner, snacks).
        • Allergies and Notes.
    • Meal Plan:
      • Meal Plan ID.
      • Week Starting Date.
      • Shopping List.
      • Inspirational Quote.
      • Links to Meals.
    • Meals:
      • Day of the Week.
      • Meal Type (breakfast, lunch, dinner, snack).
      • Description, Portions, Ingredients, Instructions.

Scenario Execution

  • Airtable Search Records:
    • Finds active clients.
    • Scheduled to run every Saturday at 8 AM.
  • Integration with ChatGPT:
    • Assumes the role of a nutrition expert.
    • Inputs: Diet preference, goals, days, allergies, notes.
    • Output: JSON with meal plan, shopping list, inspirational quote.
  • Record Creation in Airtable:
    • Formats dates and creates linked records in Meal Plan and Meals tables.

Iteration and Formatting

  • Iterators:
    • Iterate through meal plans and meals.
    • Convert numbers to day names.
  • Text Aggregator:
    • Formats meal details into HTML.

Email Dispatch

  • Email Content:
    • Subject: "Meal Plan for Week Starting..."
    • HTML content includes formatted meals and shopping list.
    • Includes uplifting quote and contact information.

Demonstration

  • Example Records: Elon Musk and Steve Wozniak.
  • Processed records for two clients.
  • Output includes detailed meal and shopping list in an email format.

Conclusion

  • Outcome: Successfully automated meal planning.
  • Availability: Blueprint link in description for setting up similar workflows.
  • Call to Action:
    • Thumbs up and subscribe for more tips.
    • Available for questions and assistance.

Final Notes

  • Emphasizes innovation and client empowerment through automated solutions.