Cog - FigBuild 2026

Inspiration

The average person makes thousands of decisions each day. Over time, even small choices create mental fatigue. We were interested in how memory, satisfaction, and internal body signals influence decision making. That led us to explore whether past decisions could meaningfully inform future ones. Cog was inspired by the idea of an “extra sensory perception” for everyday choices, where your previous experiences quietly guide you forward.

What it does

Cog reduces decision fatigue by learning from a user’s past decisions and satisfaction levels. When a user faces a new choice, such as what to prioritize or what to eat, Cog analyzes historical patterns and recommends options that previously led to positive outcomes. It helps users decide faster, conserve mental energy, and avoid overthinking small, repetitive decisions.

How we built it

We designed Cog as an interactive prototype in Figma. The system concept includes decision input through text or voice, satisfaction tracking after each choice, and analytics that visualize patterns over time. We structured the experience around three core components: decision logging, satisfaction scoring, and pattern-based recommendation logic. The prototype demonstrates how these elements connect to form a personalized decision engine.

Challenges we ran into

One challenge was modeling satisfaction in a meaningful way. Satisfaction is subjective and can change over time, so we had to consider how Cog adapts to evolving preferences. Another challenge was avoiding over-reliance on past behavior. We needed to design safeguards so the system does not reinforce unhealthy habits or make high-stakes decisions on the user’s behalf.

Accomplishments that we're proud of

We are proud of creating a cohesive concept that integrates memory, chronoception, and interoception into a practical application. The satisfaction score feature and analytics dashboard clearly demonstrate how decisions can become data that informs future recommendations. We also built an intuitive interface that feels simple despite the complexity behind it.

What we learned

We learned that decision fatigue is not only about quantity but also about cognitive load and emotional state. Designing for internal signals such as stress or hunger adds depth to decision systems. We also learned that personalization must remain flexible, since people’s preferences and goals evolve.

What's next for Cog - FigBuild 2026

Next, we plan to move beyond prototype logic into functional implementation. This includes building a working recommendation model, incorporating adaptive learning to adjust for changing satisfaction patterns, and refining the analytics dashboard. We also aim to test Cog with real users to evaluate how effectively it reduces decision fatigue and improves confidence in everyday choices.