In this talk, you will learn practical lessons from taking AI ideas from prototype to production, including architecture decisions, cost considerations, reliability, and integration into existing systems. The session focuses on what actually works in real engineering environments and what teams should watch out for when moving beyond experiments.
Key Takeaways from this talk:

1. What changes when AI moves from demo to real production use

2. Common pitfalls in building and scaling AI features at work

3. Practical ways to design reliable and cost-aware AI applications