In ICYMI Episode #1024, Jon Krohn tracks the gap between AI investment and AI return, from the technology side to the people side. Hear from Pete Johnson, Jerry Yurchisin, Priyanka Vergadia and Tristan Handy, discussing why four out of five organizations have the structures for AI success in place while only one in five sees the returns, which decisions should never be handed to a language model however confident it sounds, how to structure Claude skills so that your output stops being slop and why the semantic layer matters more, not less, now that analytics agents are the ones asking the questions.

Additional materials: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠www.superdatascience.com/1024⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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In this episode you will learn:

(00:56) Vector Search, Agentic Memory and Effective RAG

(09:20) Mathematical Optimization in the Agentic AI Era

(17:30) Anyone Can Write Code Now, So What Gets You Hired?

(27:14) How dbt Won Analytics Engineering

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