What I Learned From Building My First End-to-End AI Systems

Most people learn AI through notebooks, but real systems require more than model training.

Key Lessons

1. Data Matters More Than Models

A good dataset will beat a fancy model almost every time.

2. Architecture Must Be Modular

AVA taught me this.
Small, reusable “skills” made the assistant far easier to scale.

3. Logs and Observability Are Critical

You need to know:

• what ran
• how long it took
• where failures happened

4. Human Feedback Improves Systems

Early testers shaped my import duty calculator and portfolio system.

5. Good UX Makes AI Useful

People care more about simplicity than underlying complexity.

These lessons guide every new AI project I build.