Before beginning development we established a consistent schedule for progress updates with our sponsor, which proved invaluable for maintaining team accountability and adherence to Dr. Starks’ goals and expectations.Throughout each development cycle the trajectory of our system changed significantly, and these regular meetings enabled our team to stay on the same page and make continual progress.

The most important task during our project cycle was finding the right tech stack. Substantial effort went into determining the right tools as choosing incorrectly could potentially require re-engineering everything from scratch well into development. The system architecture was then blueprinted to ensure all variables were accounted for, followed by designing, with coding coming last due to its time intensive nature. Development was finally executed on a feature by feature basis to promote measurable progress and mitigate dependency issues come deployment.

Since the inception of the idea of an empathetic chatbot, Dr. Starks had grand ideas on how to navigate the nascent field of artificial intelligence to support struggling youth. This led to the unforeseen need to significantly refine project scope, as within the extensive features originally planned there were many unnecessary and circumstantially detrimental features that impaired the user experience. For instance, originally it was planned to split the site into two sections, one where users in need could search for local resources such as food and shelter, and the other for the empathetic chatbot. The ability to search was ultimately scrapped to make the project feasible as it was decided that Mendy could provide resource direction as necessary given the context of the conversation.

Another significant challenge encountered was the ethical concerns raised by artificial intelligence in a healthcare setting. While AI has the potential to revolutionize treatment plans, its generative nature can yield inaccurate or insensitive results. AI’s reliability cannot yet be trusted without supervision, making its integration into the healthcare sector potentially detrimental. To combat this, our site includes disclaimer stating that Mendy may provide inaccurate information. We also made sure to meticulously train our LLM using over 76,000 conversations to maximize the probability of providing  appropriate responses, especially given sensitive queries pertaining to potentially dangerous or harmful situations.

Since our initial prototype, substantial improvements in Mendy’s responses were made, largely based on insights we gained through user testing and building the system itself. An originally unforeseen problem user feedback uncovered was that Mendy had a tendency to be excessively verbose. In one case, a user entered the query “I love lemons” and Mendy provided a three paragraph response about lemons, thus responses were made more concise when possible to enhance user experience.

Another issue arose when we began to implement our mockups as we realized the fun, bubbly aesthetic we had designed seemed insensitive given our mission to support individuals who feel overwhelmed and might prefer a safe, relaxing environment. We redesigned our site to be simple and calming, incorporating a slowly breathing gradient background to ensure our users felt comfortable and supported.