

Free Lesson
AI Engineering in 30 Minutes: Become an AI-Native Engineer
30 min
Jun 29, 2026 6:00 PM
What you'll learn
Why your model isn't the problem — your pipeline is
Most "dumb AI" bugs are retrieval or ordering failures. Trace a bad output to the stage that broke.
How to make an AI system you can trust in production
Evals before vibes. The minimum testing setup that catches regressions before your users do.
Live build: turn a flaky prototype into something solid
Add retries, fallbacks, and guardrails so it fails safely instead of confidently making things up.
Why this topic matters
Anyone can wire up an API call and get an impressive demo. Shipping something that survives real users, weird inputs, and scale is a different job — and it's the one companies are actually hiring for. AI engineering is the layer between "it worked on my machine" and "it works for ten thousand people who'll try to break it." It's the gap between a cool weekend project and a product.
You'll learn from

Aki Wijesundara, PhD
AI Founder | Educator | Google AI Accelerator Alum

Manu Jayawardana
AI Advisor | Co-Founder & CEO at Krybe | Co-Founder of Snapdrum
Previously Students from