DiscoverCatalog & Cocktails: The Honest, No-BS Data PodcastHow to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-Anderson
How to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-Anderson

How to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-Anderson

Update: 2025-04-10
Share

Description

Hugo Bowne-Anderson, Independent Data & AI Scientist, joins us to tackle why most AI applications fail to make it past the demo stage. We'll explore his concept of Evaluation-Driven Development (EDD) and how treating evaluation as a continuous process—not just a final step—can help teams escape "Proof-of-Concept Purgatory." How can we build AI applications that remain reliable and adaptable over time? What shifts are happening as boundaries between data, ML, and product development collapse? From practical testing approaches to monitoring strategies, this episode offers essential insights for anyone looking to create AI applications that deliver genuine business value beyond the initial excitement.

Comments 
In Channel
loading
00:00
00:00
x

0.5x

0.8x

1.0x

1.25x

1.5x

2.0x

3.0x

Sleep Timer

Off

End of Episode

5 Minutes

10 Minutes

15 Minutes

30 Minutes

45 Minutes

60 Minutes

120 Minutes

How to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-Anderson

How to Get Out of AI Proof-of-Concept Purgatory with Hugo Bowne-Anderson

data.world