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GOTO - The Brightest Minds in Tech
GOTO - The Brightest Minds in Tech

The AI Engineer's Guide to Surviving the EU AI Act • Larysa Visengeriyeva & Barbara Lampl

13 January 2026 32:29 GOTO

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About this episode

This interview was recorded for the GOTO Book Club.
http://gotopia.tech/bookclub

Check out more here:
https://gotopia.tech/episodes/409

Dr. Larysa Visengeriyeva - Author of "The AI Engineer’s Guide to Surviving the EU AI Act" & Independent Consultant for EU AI Act Engineering
Barbara Lampl - Behavioral Mathematician at empathic business by Barbara Lampl

RESOURCES
Larysa
https://x.com/visenger
https://bsky.app/profile/visenger.bsky.social
https://github.com/visenger
https://www.linkedin.com/in/larysavisenger

Barbara
https://x.com/BarbaraLampl
https://www.linkedin.com/in/barbaralampl
https://barbara-lampl.tumblr.com

Links
https://ml-ops.org
https://github.com/visenger/awesome-mlops
https://eur-lex.europa.eu/eli/reg/2024/1689/oj/eng
https://machinelearningcanvas.com
https://louisdorard.gumroad.com/l/mlcanvas
https://ml-ops.org/content/crisp-ml

DESCRIPTION
Barbara Lampl interviews Larysa Visengeriyeva, software engineer and "godmother of MLOps", about her new book on AI engineering and compliance. What starts as a discussion about the EU AI Act quickly reveals a deeper truth: the real challenge isn't regulatory compliance - it's fundamental engineering practices.

Larysa argues that quality AI systems require robust MLOps, comprehensive documentation, and proper data governance, whether regulation mandates it or not. Drawing from frameworks like CRISP-ML and the Machine Learning Canvas, the book provides practical checklists and methodologies for taking AI projects from prototype to production. Written partially in Ukraine during wartime, this "battle-tested" guide addresses the gap between technical and non-technical stakeholders, offering a common language for building sustainable AI systems.

RECOMMENDED BOOKS
Larysa Visengeriyeva • The AI Engineer's Guide to Surviving the EU AI Act • https://amzn.to/42SKOuU
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns • https://amzn.to/4ox4Eos
Phil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZ
Diana Montalion • Learning Systems Thinking • https://amzn.to/3ZpycdJ
Bernd Rücker • Practical Process Automation • https://amzn.to/3cs3BSH
Lauren Maffeo • Designing Data Governance from the Ground Up • https://amzn.to/3QhIlnV
Katharine Jarmul • Practical Data Privacy • https://amzn.to/46XPrns
Zhamak Dehghani • Data Mesh • https://amzn.to/3tTCwAC
Kate Stanley & Mickael Maison • Kafka Connect • https://amzn.to/40Jq5Jz

AI Research Today
Serious Conversations About Real AI Research; decoding the ArXiv into your headphones.

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