Episode

You have an infrastructure problem, not an AI problem

Podcast
CDFAM Computational Design Symposium
Published
Sep 12, 2026
Duration seconds
945
Processing state
not_requested
Canonical source
https://www.designforam.com/p/you-have-an-infrastructure-problem
Audio
https://api.substack.com/feed/podcast/215419037/5b42ce4e49fc83498ac3df2cdfebf272.mp3
JSON
/v1/public/podcasts/cdfam-computational-design-symposium-7077587/episodes/you-have-an-infrastructure-problem-not-an-ai-problem
Markdown
/podcast/cdfam-computational-design-symposium-7077587/you-have-an-infrastructure-problem-not-an-ai-problem.md

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Summary

CDFAM Computational Design Symposium — Barcelona 2026 Javier Blanco Cordero · Quix Engineering teams have found AI useful for discrete tasks: SQL queries, graphs, summaries. Higher-value work, root cause analysis, physics-based ML, production deployment, remains out of reach. The standard diagnosis is that the models need to improve. Javier Blanco Cordero's experience points the other way: the models are already sufficient. The infrastructure surrounding them is not. Using a real rotor balancing case involving 50,000 rotors per year, this talk walks through what it takes to move AI from task-level support to autonomous engineering investigation. With the right infrastructure in place, a model that had underperformed on summary data identified a discriminating signal in 100 kHz vibration data that decades of domain expertise had missed. That same model independently designed a deployment plan that reduced total balancing runs by 41%. The presentation covers what was built, the results, and what it means for any organization sitting on complex engineering data. Links Watch the talk on YouTube Cite this talk Search the full text of every recorded CDFAM presentation This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com