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HUPPPPPP edited this page Aug 11, 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

Sprint Plan – Sprint 2

Date: 11/08/2025
Sprint Duration: 04/08/2025 – 17/08/2025
Attendees: Navheen, Krittapas

Sprint Goal

Deliver a functional prototype of the course-to-AI assistant application with core features implemented, enabling the client to interact with the basic flow and provide early feedback.

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