In this episode of Build What's Next, Theo Munoz, Miguel Ribeiro, and Natan Szczepaniak discuss Machine Learning Operations (MLOps) and why an estimated 80% of ML models built in notebooks never make it to production. The hosts argue that the failures stem less from technology and more from organizational issues like a lack of clear ownership, insufficient investment in data engineering, and poor data foundations. Learn how standardization, shared ownership between business and engineering, and robust model governance are crucial to scaling AI safely, especially as the industry shifts towards Gen AI.

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Episode Resources: 

Method.com

Theo Munoz on Linked-In: /in/theo-munoz-090a88151/

Miguel Ribeiro on Linked-In: /in/miguel-ribeiro-3439328a/

Natan Szczepaniak on Linked-In: /in/natan-sz/