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
• 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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What is AI Thoughtmakers?
AI ThoughtMakers is a leadership-driven podcast featuring conversations with CTOs, founders, engineering leaders, and AI experts discussing real-world AI adoption, scalable engineering, product innovation, and the future of technology.