DecideWise AI

decide AI

Inspiration# About the Project – Daily Decision Helper

Inspiration

The idea for Daily Decision Helper came from observing how much time people spend overthinking everyday decisions—choosing between job offers, planning study schedules, or even deciding whether to take a risk or play it safe. Many of these choices are not about lacking information, but about struggling to organize thoughts logically. I wanted to build a tool that acts like a rational second brain, helping users structure their thinking instead of replacing it.

What I Learned

Through this project, I learned how to design an application that highlights AI reasoning and explainability, not just text generation. I gained hands-on experience using Gemini 3 Flash Preview for multi-step reasoning, prompt structuring for consistent outputs, and building low-latency AI workflows. I also learned how important structured responses are in reducing cognitive load and improving user trust.

How I Built It

The app uses a React frontend for a clean user experience, a FastAPI (Python) backend to handle requests, and MongoDB to store user decisions and responses. Gemini 3 Flash Preview powers the core logic, analyzing user input and generating structured sections—pros, cons, risks, and a recommendation. Internally, the reasoning follows a stepwise evaluation model:

[ \text{Decision Quality} = \sum (\text{Benefits}) - \sum (\text{Costs}) - \sum (\text{Risks}) ]

The results are then formatted into readable sections for clarity.

Challenges

The main challenge was balancing speed and reasoning depth. Ensuring fast responses while preserving meaningful multi-step reasoning required careful prompt design and output structuring. Another challenge was keeping recommendations transparent without exposing unnecessary complexity.