This week on Code x Connor, we’re joined by Brian Fornelli of Conagra Brands to discuss operationalizing AI in large enterprises, why companies are overcomplicating adoption, and where generative AI actually delivers value. Brian is a Senior Director of Data Solutions and Engineering at Conagra Brands, where he focuses on building production-grade machine learning systems and scalable software solutions that improve operational decision-making. With over 15 years of experience spanning applied machine learning, engineering, and enterprise systems, his work centers on deploying practical AI solutions that drive measurable outcomes in complex operational environments. In this episode, we discuss: → Why cross-functional teams outperform traditional enterprise org structures for AI → The risks of deploying probabilistic AI into real-world operations → Why most enterprise problems don’t need advanced AI → The importance of observability, governance, and traceability in AI systems → How enterprises balance platforms like Palantir, Databricks, and Snowflake → Why AI-generated software may matter more than AI-powered operations → The coming pricing, supply, and GPU challenges facing enterprise AI → Why organizations need better ways to measure AI ROI and productivity → The risks of unbounded “vibe coded” enterprise applications → Why deterministic systems and traditional ML still matter alongside LLMs Be sure to follow us to get the latest information, and schedule a meeting with us through www.codestrap.com! Conagra Website: https://www.conagrabrands.com/ LinkedIn: https://www.linkedin.com/company/conagra-brands/ Guest: https://www.linkedin.com/in/brian-fornelli/ Codestrap Dorian: https://www.linkedin.com/in/dorian-smiley-97a72a14/ Connor: https://www.linkedin.com/in/connordeeks/ CodeStrap (X): https://x.com/Codestrap_ai CodeStrap (LI): https://www.linkedin.com/company/codestrap