Hi there! I’m Koki Kusano, in charge of researching service design at R4D.
From January to February 2026, we conducted the Personal Design Project in Yamagata City in collaboration with the Yamagata University School of Collaborative Regional Innovation and Data Science’s Co-Creation Prototyping Lab (Mitomi Laboratory). In this project, 20 participants—mainly young people in Yamagata—spent about three weeks engaging in personal design: thinking, creating, and testing their own ideas with the help of generative AI. In this article, I’ll introduce the project’s concepts, processes, and some examples of what participants came up with.
What is personal design?
Personal design is an approach where individuals design something from their own ideas.
Until now, when designing services and products, experts have primarily been responsible for research, planning, and implementation. However, with the rapid advancement of technologies like generative AI, general consumers with their own challenges and desires are increasingly able to investigate, think, and experiment for themselves. We believe that this change will give way to a new form of design, and we call that approach “personal design.”
There are three main things we hope to see from personal design.
The first is the discovery of value that has not been put into words or expressed before. The information gathered by experts through interviews differs in nature from the information that emerges when individuals actively think and act on their own. We believe that by engaging in personal design, individuals will be able to shape the vague thoughts in their minds into a clearer and more concrete form.
The second is addressing the limitations of resources. Local communities have various challenges and needs, but not everything can be addressed by businesses and government alone. If individuals can identify and solve the problems they can take into their own hands, there is a possibility that more things will progress as a whole.
The third is the empowerment of individuals. By engaging in personal design—thinking and taking action for themselves—individuals may be able to expand their own possibilities. During the project, I strongly felt this potential as I watched the participants work with great enthusiasm.
This project was conducted mainly with young people in Yamagata. At Mercari R4D, we aim to expand implementation of our work to various regions and contexts toward our mission to circulate all forms of value to unleash the potential in all people. Yamagata is a place rich in local wisdom and connections, while also having significant potential for new initiatives utilizing digital technology.
We gathered 20 participants, including students from Yamagata University and Tohoku University of Art & Design, as well as working adults in the area. As a result, we had participants from various backgrounds working on projects starting from their own personal ideas.
Project process
The process of the Personal Design Project is based on three pillars: dialogue with AI, dialogue between people, and actual experimentation. We gathered four times over approximately three weeks.
Dialogue with AI (Personal Design Facilitator)
One of the distinctive mechanisms of this project is a dedicated conversational AI called the Personal Design Facilitator, which I’ve been researching. This AI helps participants verbalize their personal ideas.
Specifically, as participants chat with the AI, the AI continuously poses questions like, “Why is that?” and “Can you describe the situation in more detail?” Through this process, the participants find themselves putting into words things that they weren’t even conscious of themselves.
The AI can also output the verbalized content in a structured story-like format, making it easier for participants to convey their thoughts to others and providing material helpful for considering where to go for the next prototype.
Support for prototyping with AI
After verbalizing their personal ideas, participants move on to the step of trying small experiments (prototyping). AI also plays a role here.
For example, we worked together with the Personal Design Facilitator to create hands-on prototypes trying out small, new ideas in everyday life. By actually trying out these small, new ideas, participants discovered unexpected insights, like realizing something they thought would work one way ended up doing something different. We also used other commercial generative AI services to create web app prototypes. Participants simply tell the AI the kind of app or feature they want to create, and it generates a working prototype. It’s one thing to think through ideas in text, but when you actually see a working prototype in front of you, new realizations keep coming—like noticing that something’s different from how you pictured it or that it could really use another feature that you hadn’t thought of.
This allowed participants to bring their ideas to life and test them, even without any particular programming skills.
Dialogue between people
Some things can’t be discovered just by talking with AI—namely, the empathy and inspiration that come from talking with other people.
In this project, we used an online collaboration tool to share each participant’s ideas and experiments, and set up regular opportunities for conversation. We established some ground rules for these conversations. Each speaker shares their perspective for 2–3 minutes, after which listeners ask questions or offer comments. In groups of four, the participants take turns as the speaker. The focus was on empathy and inspiration—not evaluation. Conversations like “That’s a great idea” or “What if we tried this instead?” spark new perspectives that one could never reach alone.
After the project ended, participants shared positive feedback about these conversations, noting that they were engaging and that they gained new insights.
A schedule of four sessions over about three weeks
The project consisted of four sessions:
- Session #1 (1/29): Offline dialogue: Participants engaged in dialogue with AI and with other participants and began to put their ideas into words
- Session #2 (2/5): Online dialogue: Participants shared their thoughts and what they tried, and engaged in dialogue with other participants
- Session #3 (2/12): Online consultation: Participants further shared their thoughts and what they tried, and deepened their discussions
- Session #4 (2/19): Offline presentations: Participants presented their thoughts and what they tried, and left comments
Between sessions, participants had time to take what they learned and try things out on their own. Because tasks like dialogue with AI and prototype creation can be done in one’s own everyday environment, participants were able to work at their own pace outside of the sessions.
Examples of personal design that emerged through dialogue and experimentation
Although the project period was short—just three weeks—each participant’s personal ideas gradually became clearer through dialogue with AI, dialogue with other participants, and hands-on experimentation. Some pivoted direction along the way; even so, they began to take shape as concrete actions. Here, I’d like to present several examples where the process was particularly impressive.
Case 1: Using food logging to discover and tackle a deeper challenge
This participant’s starting point was an interest in food that began when they were in fourth grade. They enjoyed taking photos of their meals, but found it hard to stay motivated to keep records. They had a vague concern that the photos they took would just get buried in their phone’s camera roll.
As they explored their own perspective through dialogue with AI, they began to understand why they found it hard to keep going. The issue was not a lack of willpower, but rather pressure to record everything perfectly that they were unconsciously putting on themself. After realizing this, they began creating a prototype of a food logging app using generative AI services.
Through the process of creating and testing, they gained an even deeper understanding. Knowing their tendency to give up after a few days helped them arrive at a design that let go of perfectionism: rather than aiming to record everything perfectly, making it a light habit to randomly select a dish each day was essential for consistency. They also found themself taking actions they couldn’t have imagined before the project, like taking on the challenge of deploying their work to a code-sharing platform for the first time.
Case 2: Vague frustration turning into a clear goal
This participant felt a vague frustration that while designs they created in their classes were praised and led to personal growth, they didn’t reach the hands of actual users.
As they explored this frustration through dialogue with AI, it became clear that they had a strong desire for their work to be genuinely used in someone’s daily life. This led to the idea for a system called Campus Link, which would set up a request box within a university so students could request and create things that leverage each other’s expertise, helping them build their portfolios at the same time.
During the dialogue with other participants, many people said that this sounded like a great idea. Participants were eager to consult with their professors and bring something to life for this system, too.
Case 3: Pivoting from finding motivation to accepting incompleteness
This participant struggled with perfectionism: they had such high ideals that even when they came up with ideas, they ended up not being able to do anything about them.
The first thing this participant worked on was a prototype app designed to boost motivation during the preparation stage. However, when they actually tried using it, they found that buttons and text on a screen were not enough to motivate them. In fact, they realized that breaking tasks down into smaller steps was actually causing them to pursue a different kind of perfectionism. This led to a new discovery: the very approach of trying to force themself to get moving was counterproductive for them.
The turning point was the day of presentations between project participants. It sparked a complete shift in perspective—transforming the thought of something being “incomplete” from something negative into a positive force. They switched gears to work on a new concept of anonymously sharing unfinished ideas so that others can move them forward, which was a complete departure from their original idea.
In conclusion
Although the project only ran for about three weeks, 20 participants were able to articulate their own ideas, create prototypes, and actually put them to the test, with the help of generative AI.
What we found most significant was that, with AI supporting the articulation and prototyping of personal ideas, it was possible to create concrete prototypes in just three weeks. Even participants without specialized skills were able to shape their ideas through dialogue with AI, test them, and gain new insights from there. By combining the unique strengths of both AI and people, each participant was able to shape their ideas into something real and tangible. The process yielded highly insightful data. The data enabled us to understand the kinds of challenges each person faced, how they put those challenges into words, and what inspired them to try new things. These are all valuable insights from a design research perspective.
We plan to continue exploring how to further develop the outcomes of this project moving forward. If you’re interested in the personal design approach, please feel free to reach out!