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The PoC Launch Kit & Team Reflection

Objective 🎯

Your final task is not a traditional presentation. Instead, your team will create a professional "launch kit" for your proof-of-concept, designed to attract new users and convince stakeholders of your project's value. This is your chance to showcase your work in a format that mirrors a real-world product launch.

This will be followed by a reflective team interview to synthesize your learning and critically examine your journey through the course.

Due Date & Evaluation

  • Due: See Canvas.
  • Evaluation: This "launch kit" and the quality of your final application constitute the final assessment for your 45-point Group Project grade. Your work will be evaluated using the main project rubric, particularly the criteria for Technical Execution, UX & Design, and Final Presentation & Demonstration.

Components of the Final Deliverable

The Video Pitch 🎥

Your goal is to create a compelling, marketing-style video. This is not a technical deep-dive; it's a pitch designed to woo potential users and sponsors. It should be concise, professional, and persuasive. The recommended length is 3 to 5 minutes.

  • Content: The video must clearly communicate the problem you're solving, demonstrate your application's core features in action, and articulate its unique value proposition.
  • AI-Powered Creativity: You are explicitly encouraged to use AI in the creation of this video. This is a final opportunity to practice your "AI as a collaborator" skills for tasks like writing the script, creating a voiceover, generating background music, or even producing animated visuals.
  • Submission: Upload your video to a platform like YouTube (as an "Unlisted" video) or Vimeo and place the link prominently at the top of your project's README.md file.

The Quick-Start Guide 📖

QUICK_START.md

This is a practical, user-facing document. It should enable a brand-new user to understand your application's purpose and successfully complete the core tasks you identified in your initial project charter.

  • Content: The guide should include a brief overview of the application and simple, step-by-step instructions for using 2-3 of its key features.
  • Audience: Write for a non-technical user. Avoid jargon and focus on clarity. Your goal is to make a first-time user successful and confident.
  • Submission: Create a new file named QUICK_START.md in the main directory of your team's GitHub repository.

The Peer Review Process 🤝

Giving and receiving professional, constructive feedback is a critical skill.

  • Process: During the closing week of the course, each student will be assigned two other teams' "launch kits" to review. You will watch their video, read their quick-start guide, and use a provided rubric to offer feedback on the clarity, persuasiveness, and professionalism of their work.
  • Grading: Thoughtful completion of the peer review process is a component worth 5 points of your final grade.

The Reflective Team Interview 🧠

This is a 15-minute in-class round table discussion. This is not a defense of your project, but a structured, collaborative conversation to reflect on your team's learning journey.

  • Purpose: The goal is to foster self-reflection. We'll discuss your team's process, how your perspectives on AI have evolved, and whether AI ultimately helped or hindered your critical thinking and learning.
  • Preparation: Your team will be provided with the interview questions in advance to help you prepare for a thoughtful discussion (See examples below).

Interview Questions ❓

On Process & Collaboration

  • Looking back at your GOVERNANCE.md from your project charter, which part of your planned process was most successful in practice, and which part broke down first? Why?
  • Describe a specific moment where using an AI tool as a collaborator (like GitHub Copilot or a process prompt) significantly changed your team's direction or saved you a huge amount of time.
  • What was the most challenging aspect of managing an AI project compared to a traditional software project?

On Technical & Conceptual Understanding

  • What is one major misconception you had about Generative AI at the start of the course that has now changed?
  • If you had to explain the concept of Retrieval-Augmented Generation (RAG) to a non-technical manager in 30 seconds, how would you do it now?
  • Beyond your own project, what do you now understand about the limitations of current LLMs that you didn't appreciate before?

On Critical Thinking & Future Outlook

  • Where did your team find the line between using AI as an effective tool and letting it hinder your own problem-solving or critical thinking? Can you give a specific example?
  • After building your own AI application, what are you most optimistic about regarding AI's future in business? What are you most concerned about?
  • What's one piece of advice you would give to a new team just starting this course and project?

The Personal Journal 📓

The best interviews draw on specific, personal experiences. To prepare for this reflective conversation, I strongly encourage you to keep a simple, informal personal journal throughout the semester. This is not a graded assignment, but a tool for your own benefit.

After a challenging "builder session" or an insightful "learner session," take just five minutes to jot down a few thoughts. A few sentences each week will provide you with a rich set of personal reflections to draw upon, leading to a much more insightful final conversation.

Some prompts to consider for your journal entries:

  • What was the most confusing concept this week, and what finally made it "click"?
  • Describe a specific prompt that failed spectacularly. What did you learn from the failure?
  • Did using an AI tool today feel like a superpower or a crutch? Why?
  • What was a moment of success or friction within your team this week? How did you handle it?
  • What's one thing you believe about AI now that you didn't believe last week?