AI Engineering Beyond the Hype: Harnesses, Guardrails and Production Reality

Generative AI has made it easier than ever to build impressive prototypes. But turning those prototypes into secure, reliable and cost-effective enterprise systems is a very different challenge.

In this episode of Enterprise Tech Talk, host Saumitra Kalikar speaks with Adam Witanowski about AI Engineering and what it takes to move from prototype hype to production reality.

Adam brings deep experience across software engineering, AI architecture, startups, consulting and enterprise delivery. The conversation explores why AI engineering is becoming a distinct discipline — not because traditional software engineering no longer matters, but because AI-generated delivery changes the speed, scale and risk profile of the entire software delivery lifecycle.

Key topics include:

• Why AI engineering is more than prompt engineering or model selection
• The difference between AI prototypes and production-grade systems
• Harness engineering and meta-harnessesPolicy-as-code, runtime controls and enterprise guardrails
• Vibe coding vs spec-driven and goal-driven development
• Loop engineering, token cost and context driftTesting, evals and the changing role of QA
• RAG, long-context models, knowledge graphs and enterprise memory
• AI governance, security, FinOps and responsible adoption

The key message: enterprise AI success will not come from model choice alone. It will come from the engineering systems, context layers, governance controls and guardrails organisations build around AI.

This episode is designed for CIOs, CTOs, enterprise architects, software engineering leaders, AI leaders, product leaders and technology executives navigating the next phase of enterprise AI adoption.

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