Introduction
Building AI-powered products is both exciting and challenging. In this guide, we'll share our learnings from building dozens of AI products.
Start with the Problem
The biggest mistake we see teams make is starting with "we want to use AI" rather than "we have this problem to solve."
Key Questions to Ask
- What problem are you solving?
- How are users currently solving this problem?
- Will AI meaningfully improve the solution?
Data is Everything
Your AI is only as good as your data. Before writing a single line of ML code, invest heavily in data quality.
Start Simple, Iterate Fast
Don't jump straight to deep learning. Often, simpler approaches work well. Only add complexity when needed.