Episode 27: How to Build Terrible AI Systems

Hugo speaks with Jason Liu, an independent consultant who uses his expertise in recommendation systems to help fast-growing startups build out their RAG applications. He was previously at Meta and Stitch Fix is also the creator of Instructor, Flight, and an ML and data science educator.
They talk about how Jason approaches consulting companies across many industries, including construction and sales, in building production LLM apps, his playbook for getting ML and AI up and running to build and maintain such apps, and the future of tooling to do so.
They take an inverted thinking approach, envisaging all the failure modes that would result in building terrible AI systems, and then figure out how to avoid such pitfalls.
LINKS
The livestream on YouTube (https://youtube.com/live/USTG6sQlB6s?feature=share)
Jason's website (https://jxnl.co/)
PyDdantic is all you need, Jason's Keynote at AI Engineer Summit, 2023 (https://youtu.be/yj-wSRJwrrc?si=JIGhN0mx0i50dUR9)
How to build a terrible RAG system by Jason (https://jxnl.co/writing/2024/01/07/inverted-thinking-rag/)
To express interest in Jason's Systematically improving RAG Applications course (https://q7gjsgfstrp.typeform.com/ragcourse?typeform-source=vg)
Vanishing Gradients on Twitter (https://twitter.com/vanishingdata)
Hugo on Twitter (https://twitter.com/hugobowne)
Upcoming Livestreams
Good Riddance to Supervised Learning with Alan Nichol (CTO and co-founder, Rasa) (https://lu.ma/gphzzyyn?utm_source=vgj)
Lessons from a Year of Building with LLMs (https://lu.ma/e8huz3s6?utm_source=vgj)

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