Getting your AI system into production isn’t the finish line. It’s the point where the real work begins.
In this episode of Bringing Data and AI to Life, host Nick Dobbins sits down with Maria Vechtomova, Co-Founder of Cauchy, MLOps expert and O’Reilly author, to unpack what it really takes to make AI reliable beyond the experimentation phase. She breaks down the four principles underpinning MLOps as well as the challenges of evaluating GenAI outputs, governing agentic systems and integrating AI across complex enterprise environments.
The conversation makes one thing clear: AI cannot be treated like static software. Because when the outputs, failure modes and evaluation criteria keep changing, the work is never really “done.”
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