PeerWealthy
See how you compare
This page is the product layer. The articles below are the context layer: why I built it, what I learned, and how the product fits into the broader system on nielskaspers.com.
About the project
Most people have no idea if they're doing well financially. They compare themselves to influencers flexing unrealistic wealth, friends who exaggerate, or national averages that ignore local cost of living.
PeerWealthy fixes this. It shows you anonymous, real data from people in your area, your age group, your career stage. No guilt. No judgment. Just clarity.
The magic: every user who checks their standing anonymously contributes to the dataset—creating a flywheel where the community unknowingly helps each other get better at finances.
Key features
Hyper-local comparisons
Compare with people in your city, age group, and career stage—not national averages.
Privacy-first
All data is anonymized and aggregated. No personally identifiable information stored.
Community-powered
Every comparison strengthens the dataset for everyone.
Actionable insights
Not just rankings—personalized tips and next steps.
Related articles
These pieces explain the build decisions, systems, and lessons behind PeerWealthy.
Building a finance app with SwiftUI and zero iOS experience
How a product manager with no Swift experience shipped an iOS finance app using Claude Code, SwiftUI, and TCA.
How to build a comparison product people actually trust
If your product asks people to compare sensitive options, trust has to be visible at the moment of judgment. Here is the framework I am using while building PeerWealthy.
How I use Claude Code to build products as a PM
A non-engineer PM's guide to shipping real products with Claude Code—from iOS apps to automation systems.
Agent debt is already here
AI workflows do not usually break all at once. They decay through overlapping tools, stale instructions, polluted memory, and missing review gates. Here is what agent debt looks like in practice and how to avoid it.