On the final day of the AI/ML & Prompt Engineering internship at Virtual Height Pvt Ltd, the residency culminated in the testing and presentation of our Capstone Chatbot Projects. Before presenting to the evaluation jury, we ran final validation passes across our codebases checking session concurrency, prompt templates, and styling responsiveness.
1. Final Project Verification & Testing Bounds
We verified and debugged our chatbots to ensure flawless operation across all required criteria: routing, session history storage, personality selectors, and error boundaries. This guaranteed that the final chatbot accepted message inputs, generated replies using the remote API safely, and loaded dynamic side configurations without breaking standard layouts.
2. The Evaluation: Architectural Defense
During the demonstration session, each intern presented their application live to the Virtual Height engineering panel. I walked the jury through my Flask REST API, session cookie partitioning, and sliding window history context to prevent prompt window bloat. They were highly impressed by my technical answers during the Viva Q&A, where I explained structured token boundaries.
3. Residency Completion and Wrap-up
Upon completing the final evaluations, our PhD mentor, Rashmi, commended my technical maturity, explaining to the class that my choices—preferring Flask REST API simplicity over PyTorch bloat and AJAX over page reloads—showed the depth of a seasoned developer. This presentation completes my 2-week residency, cementing structural prompt design and backend API integration into my active portfolio.