Objective

The goal in this stage of the project was to develop a problem statement that accurately relates to and represents our proposed solution. In order to fully grasp the concept of our problem and create an app that caters to users’ needs, secondary research needed to be conducted.

Framing The Design Challenge

This worksheet allowed my team and me to be able to decipher if our app idea could actually work. I think that the most important aspect was refining our problem and the context. Creating a main “How Might We” question made it clearer to see if our upcoming solutions would relate to the problem we are trying to solve. Brainstorming constraints that we need to consider was incredibly insightful because it is easy to imagine an idea that is utopian and unrealistic.

Secondary Research

Because most AI scheduling apps require payment for their features, we utilized articles found online that rated some of the resource options. The chosen competitors include Sunsama, Claude/ChatGPT, and ReclaimAI. Our team found helpful insights that we could keep in mind for the development of our scheduling app and common issues across each program. Since we were not able to test some of the apps for ourselves, visiting their home websites was useful to view what special features they promote and what their graphic user interface looks like.

Some universal strengths include: break-time features, pomodoro timer integration, pulling tasks and meetings from other apps, the ability to break up big tasks, and a reflection-focused workflow. Viewing what our competitors have to offer helps us generate ideas for our own app and learn what to include and what not to include. The universal weaknesses include: high cost for the advanced apps, manual task scheduling, limited platform support, and the AI’s need for too much detail to be successful. A quote from Matthew Guay’s article, “I Tested 9 AI-Powered Scheduling Assistants. My Favorite Is the One With the Least AI,” that I thought was especially helpful was, “The best results come when you add more data to tasks. If you set the priority, detail your sub-tasks, and categorize work, the AI is more likely to schedule tasks in a way that will make your work flow together.”

AI Usage

In this process, I utilized Google Gemini’s AI overview feature to conduct some secondary analysis and Figma’s Make to generate a sample app just to see what it could create. Google’s AI overview helped me find the weaknesses of some competitors’ websites since all I could find were the positives. Figma was able to create an app directly based on the information I gave it. The interaction prototyping and visuals were very impressive.

Challenges

I think the most difficult aspects of this phase lie in the “Frame Your Design Challenge Worksheet.” It was challenging to find a problem that interested everyone on our team, which integrates artificial intelligence, and was realistic. Within the worksheet, I found myself struggling to come up with fresh ideas about how AI could uniquely solve our team’s problem. To combat these challenges, we conducted secondary research at the same time as filling out the worksheet. Seeing what others had to offer made it easier to brainstorm ideas for our own app.