Hero Light MCPP (Model, Context, Process, Prompts) is a simple but robust framework for creating AI-driven workflows that can be easily referenced, shared, and repeated. Instead of treating AI interactions as one-off conversations, MCPP helps you capture every essential detail - enabling you or your team to quickly replicate the workflow for similar tasks in the future.

​
Why Use MCPP?

  • Prevent “One-and-Done” Interactions: Too often, prompts and insights are lost once you close your AI chat. MCPP ensures these valuable inputs are preserved.
  • Encourage Transparency and Consistency: Well-documented workflows foster open collaboration, reduce stigma around AI usage, and produce more uniform outputs across the team.
  • Enable Continuous Improvement: MCPP workflows can be easily updated as AI tools improve or your project requirements change.
Hero Light

​
The Four Pillars of MCPP

  1. Model (M): Identify which AI model or tool you’re using—e.g., OpenAI GPT-4, Anthropic Claude, or Google Gemini.
  2. Context (C): Gather the relevant knowledge base or background information. For a PRD, this could include project objectives, design constraints, or user requirements.
  3. Process (P): Break down the workflow into clear, step-by-step actions (e.g., collect requirements, converse with AI section-by-section, finalize the output).
  4. Prompts (P): Document the exact text or questions you feed the AI at each process step—this is crucial for repeatability and for others to learn from your approach.

​
Example Application: Writing a PRD with MCPP

Below is a quick reference example to illustrate how you might apply MCPP to creating a Product Requirements Document (PRD).

​
1. Model (M)

  • openAI o1 (e.g., GPT-4) You may substitute any AI tool your team prefers, such as Claude or Gemini.

​
2. Context (C)

  • Example PRD
    • Product Name: CoffeeVox
    • Goal: A mobile app letting users order coffee via voice commands
    • Audience: Busy professionals seeking a quick ordering process
    • Constraints: Must integrate with payment apps, support loyalty programs, etc.

​
3. Process (P)

  1. Explain the Premise:
    • Introduce the app concept, gather scope, and clarify objectives.
    • Note any must-have features (e.g., multiple coffee shop support, loyalty rewards).
  2. Section-by-Section Conversation:
    • Have the AI prompt you for each PRD section (Objectives, User Stories, Tech Specs, Milestones).
    • Fill in details conversationally to ensure thorough coverage.
  3. Generate the Final PRD:
    • Prompt the AI to compile all gathered information into a standardized PRD format.

​
4. Prompts (P)

  1. Explainer Prompt:
    “You are an experienced product manager. I’m creating a PRD for a new mobile app called CoffeeVox that lets users order coffee via voice commands. We’ll go through each section step by step. First, ask me questions that will help clarify the product’s objectives and scope.”
  2. Conversational Sections:
    “Great. Let’s start with Objectives… [etc.]”
  3. Generation Prompt:
    “Now that we have details for each section, please generate the final PRD for CoffeeVox. Make sure to format it with headings like Introduction, Objectives, User Stories, Technical Requirements, Milestones & Timelines.”

​
Tips for Implementation

  • Start Small: Apply MCPP to one recurring task—such as drafting a weekly report or creating a team announcement—and refine as you go.
  • Share and Iterate: Store your MCPP workflow where teammates can easily find it (e.g., an internal wiki or shared drive). Encourage feedback to improve prompts and processes.
  • Keep Updating: As models evolve or requirements shift, revisit your MCPP documentation to keep it accurate and effective.

​
Additional Resources

  • theoperator.ai: Blog posts on leveraging AI for lean teams and solo operators.
  • Discord Community: Connect with peers to share workflows or see real-world MCPP examples.
Ready to create your first MCPP workflow? Document the Model, Context, Process, and Prompts for a task you handle frequently. Once you see how much time it saves—and how easily others can replicate your steps—you’ll want to build and share more.