App Experiments
Learning AI by building real projects
AI makes it possible to go from idea to working product in days. Find a problem, build a solution, put it in front of real users. Validated ideas can become real products. Failed ones become lessons.
Projects
BUBU
Rotating Savings Tracker for Paluwagan Groups
Problem: Filipino rotating savings (paluwagan) are tracked via paper or group chats. Easy to lose, hard to verify.
Solution: A simple web app: create groups, invite members, track contributions, auto-advance cycles.
Building himo
Portfolio Construction & AI Meta-analysis
A meta-analysis of building this portfolio: escaping WordPress, embracing Next.js, and vibe-coding with AI.
The Approach
Find a Problem
Something you or someone you know actually deals with
Plan Before Code
Use AI to break down schema, flows, edge cases
Build UI First
Mock data, iterate fast, then wire up backend
Document the Patterns
What worked, what didn't, what's reusable
Why Experiments?
AI lets you build in days, not months
Real users validate better than theories
Ship fast → learn fast → iterate fast
Every experiment is a potential product
The goal: Validate fast, ship fast. If it works, scale it. If it doesn't, you learned something. Either way, you're building real skills with AI.