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HUPPPPPP edited this page Aug 4, 2025 · 9 revisions

🚀 Sprint Retrospective – Sprint 1

Date: 28/07/2025
Sprint Duration: 15/07/2025 – 03/08/2025
Attendees: Navheen, Krittapas

🎯 Sprint Goal

Establish the foundation for the course-to-AI assistant application by setting up core frameworks, defining the data handling strategy, and initiating UI planning and development.

✅ What Went Well

  • Framework Setup Complete: Successfully set up and integrated React (frontend), FastAPI (backend), and Render (deployment).
  • Clear Data Strategy: Agreed on converting course descriptions into standardized JSON format for use with LLMs.
  • UI Planning & Development Started: Krittapas began implementing the frontend based on initial wireframes.
  • Effective Task Division: Tasks were clearly split — Navheen focused on backend setup and data structure, while Krittapas focused on UI.
  • Prototype Delivered: A working version of the prototype was completed and ready for client presentation.
  • Positive Client Feedback: The client appreciated the clean UI design and overall direction of the project.

🔴 What Could Be Improved

  • Time Buffer for Unexpected Issues: A minor delay occurred during the setup phase. Adding buffer time in future sprints may help avoid impact on other tasks.
  • Documentation of Setup Steps: Some configurations took extra time due to lack of documentation. This can be improved in the next sprint.

🔁 What To Try Next Time

  • Start Backend and Frontend Tasks in Parallel using mock data to reduce idle time.
  • Document Environment Setup Clearly to ease onboarding and reduce confusion.
  • Begin API Integration Earlier to allow more time for handling edge cases.

📦 Sprint Outcome

Deliverable Status
React, FastAPI, and Render configured ✅ Completed
Course data structuring strategy defined ✅ Completed
Initial frontend UI implemented ✅ Completed
Functional prototype delivered ✅ Completed
Client presentation and feedback session ✅ Completed

🎉 The sprint goal was successfully achieved. The team laid a strong foundation and received encouraging client feedback on the prototype. Momentum is building heading into Sprint 2, which will focus on refining the data pipeline, improving UI interactions, and beginning LLM integration.

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