AI can generate impressive apps in minutes. But why do so many AI-powered prototypes fail when real users start using them?

In this episode of AI Thoughtmakers, we sit down with Manuinder Sekhon, Tech Lead I at GeekyAnts, to discuss why many AI-generated applications struggle in production despite looking polished on the surface.

From authentication gaps and database bottlenecks to observability, scalability, and backend reliability, we explore the invisible engineering work that separates a demo from a real product.

Key topics covered:

• Why AI-generated prototypes often collapse under real user traffic

• The hidden 90% of engineering work founders don't see

• Common backend issues in AI-generated applications

• Why observability and monitoring are essential for production systems

• The risks of shipping AI-built products too early

• How AI coding tools are changing startup expectations

• The difference between validating an idea and launching a product

• What founders should do before building with AI tools

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Connect with the Speakers

LinkedIn - / manuindersekhon

Connect with Prem:

LinkedIn - / premgoswami