In this episode of AI ThoughtMakers, Suresh Konakanchi shares a hard truth many teams discover too late:
AI prototypes rarely fail because of the model — they fail because they were never designed for production.
Today, AI can generate polished demos in days. But behind impressive interfaces and fast-moving prototypes, most products still lack the foundations required for real-world reliability, scalability, and long-term growth.
This conversation explores the critical gap between prototype and production — and why many organizations get trapped in endless rebuild cycles instead of sustainable progress.
Suresh breaks down what actually makes AI systems production-ready, including:
- Spec-driven development and why clarity matters before coding
- The hidden risks behind “demo-ready” AI products
- Production checklists teams often ignore
- Scalability, observability, reliability, and edge-case handling
- Why poorly defined requirements lead to repeated refactors
- The importance of understanding AI limitations before deployment
- Building systems that can evolve without constant rebuilding
Are you building something that only looks production-ready — or something truly built to scale?
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About AI ThoughtMakers
AI ThoughtMakers is a podcast series exploring how AI is transforming products, engineering, business strategy, and decision-making through conversations with industry leaders and technology experts.
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.