Episode

Why AI engineering needs old-school discipline

Podcast
The New Stack Podcast
Published
Apr 24, 2026
Duration seconds
1466
Processing state
not_requested
Canonical source
https://thenewstack.simplecast.com/episodes/why-ai-engineering-needs-old-school-discipline-At9M7eQV
Audio
https://cdn.simplecast.com/media/audio/transcoded/317e9dbc-9a52-4da7-9725-c4578874b757/5672b58f-7201-4e0e-b0af-da702259d97f/episodes/audio/group/f1049951-6f1a-42a6-9eb6-6ede485eec6b/group-item/0f80bea6-b2d4-4b14-bf63-220ef631ac4e/128_default_tc.mp3?aid=rss_feed&feed=IgzWks06
JSON
/v1/public/podcasts/the-new-stack-podcast-1092634/episodes/why-ai-engineering-needs-old-school-discipline
Markdown
/podcast/the-new-stack-podcast-1092634/why-ai-engineering-needs-old-school-discipline.md

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Summary

In this episode of The New Stack Makers, Nimisha Asthagiri of ThoughtWorks explores why many AI initiatives stall between proof of concept and production. A key issue is that organizations focus on speed—asking how to move faster—rather than rethinking what new capabilities AI actually enables. Successful companies take a systems-thinking approach, investing in organizational literacy and aligning teams around meaningful use cases instead of retrofitting AI into existing workflows.