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2025 was the year AI accelerated everything — code, decisions, delivery, and expectations.
But acceleration came with lessons.
In this episode, we reflect on what actually changed when generative and agentic AI entered real production systems — not demos, not labs, but software that teams had to run, maintain, and be accountable for.
This conversation explores why prompting was never engineering, how autonomy without structure created fragility, why no-code didn’t remove complexity, and what it really means to design AI systems that behave reliably over time.
2026 isn’t about using smarter models or moving faster.
It’s about building AI like software — with constraints, resilience, domain intelligence, and accountability designed in from the start.
If you’re building, deploying, or operating AI systems in the real world, this episode sets the tone for what comes next.
By Naveen Balani3.2
55 ratings
2025 was the year AI accelerated everything — code, decisions, delivery, and expectations.
But acceleration came with lessons.
In this episode, we reflect on what actually changed when generative and agentic AI entered real production systems — not demos, not labs, but software that teams had to run, maintain, and be accountable for.
This conversation explores why prompting was never engineering, how autonomy without structure created fragility, why no-code didn’t remove complexity, and what it really means to design AI systems that behave reliably over time.
2026 isn’t about using smarter models or moving faster.
It’s about building AI like software — with constraints, resilience, domain intelligence, and accountability designed in from the start.
If you’re building, deploying, or operating AI systems in the real world, this episode sets the tone for what comes next.

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