What does AI engineering actually look like inside modern enterprises — and how close are we to truly autonomous software development?

In this episode of The Recursive Podcast, we sit down with Karol Przystalski, Chief Data and AI Officer at Exadel, to explore how organizations are moving beyond AI experimentation and into AI-native operations.

We discuss the evolution from AI copilots and coding assistants to fully orchestrated engineering systems, why many companies are measuring AI success incorrectly, and how enterprise leaders should think about ROI, productivity, and organizational change in the age of autonomous engineering.

Karol also shares insights into Exadel Colleague — an AI-powered engineering teammate designed to support entire software teams—and explains why the future of AI isn't about replacing humans, but helping them focus on higher-value work.

In This Episode:

🔹 Why AI adoption is shifting from experimentation to real business value
How enterprises have moved beyond AI proof-of-concepts and are now focused on productivity, efficiency, and measurable outcomes.

🔹 The difference between AI-enabled development and AI-native engineering
Why coding assistants are only the first step—and how autonomous systems are transforming entire software development lifecycles.

🔹 How to measure AI ROI beyond token usage
The metrics that actually matter, including productivity gains, human-equivalent hours saved, accuracy, and business impact.

🔹 The future of autonomous engineering and the role of humans
Why AI won't replace software engineers, but will fundamentally change how teams work and what skills will matter most.

🧠 Whether you're an engineering leader, CTO, product executive, or simply curious about the future of software development, this conversation offers a practical look at where enterprise AI is headed next.

Share