Raj

Great overview. One trend I've noticed is that teams are spending less time debating frameworks and more time investing in developer experience, CI/CD, and reusable design systems. Those decisions seem to have a bigger impact on long-term productivity.

Good list. The conversation around AI product engineering is finally shifting from building demos to delivering production-ready systems. Companies like EPAM, Thoughtworks, Globant, Accenture, and GeekyAnts seem to be differentiating themselves by combining AI capabilities with strong product engineering and scalable architecture.

Great point about the gap between AI experimentation and production readiness. That's where many initiatives seem to stall. I noticed GeekyAnts being mentioned more frequently in discussions around AI-powered product engineering and enterprise applications. Curious if anyone here has firsthand experience working with them.