We've all done RAG, now what?

2025-09-29 · 44 min · episode 330 · 7 entities

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Asserted relationships

→ hosted by Daniel Whitenack and Chris Benson person

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Feed author/publisher: Daniel Whitenack and Chris Benson
→ discusses Technology company

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→ hosted by Practical AI LLC company

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Feed author/publisher: Practical AI LLC

Entities found in this episode

companys 4

mentioned Practical AI LLC company

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evidence rules-v5
Feed author/publisher: Practical AI LLC
mentioned Technology company

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Feed category: Technology
discusses Technology company

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Feed category: Technology
hosted by Practical AI LLC company

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evidence rules-v5
Feed author/publisher: Practical AI LLC

persons 2

mentioned Daniel Whitenack and Chris Benson person

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evidence rules-v5
Feed author/publisher: Daniel Whitenack and Chris Benson
hosted by Daniel Whitenack and Chris Benson person

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evidence rules-v5
Feed author/publisher: Daniel Whitenack and Chris Benson

concepts 1

mentioned RAG concept

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RAG

Episode description as stored

Longtime friend of the show Rajiv Shah returns to unpack lessons from a year of building retrieval-augmented generation (RAG) pipelines and reasoning models integrations. We dive into why so many AI pilots stumble, why evaluation and error analysis remain essential data science skills, and why not every enterprise challenge calls for a large language model. Featuring: Rajiv Shah – LinkedIn Daniel Whitenack – Website , GitHub , X Upcoming Events: Join us at the Midwest AI Summit on November 13 in Indianapolis to hear world-class speakers share how they’ve scaled AI solutions. Don’t miss the AI Engineering Lounge , where you can sit down with experts for hands-on guidance. Reserve your spot today! Register for upcoming webinars here !