Measuring the actual impact of AI coding (Friends)

衡量人工智能编码的实际影响(朋友)

The Changelog: Software Development, Open Source

2025-07-12

1 小时 3 分钟
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Abi Noda from DX is back to share some cold, hard data on just how productive AI coding tools are actually making developers. Teaser: the productivity increase isn't as high as we expected. We also discuss Jevons paradox, AI agents as extensions of humans, which tools are winning in the enterprise, how development budgets are changing, and more.
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  • Welcome to ChangeLog and Friends, a weekly talk show about taking more walks.

  • Thanks to our partners at fly.io, the public cloud built for developers and AI agents who ship.

  • We love Fly, you might too.

  • Learn more at fly.io.

  • Okay, let's talk.

  • Well, friends, I'm here with Damien Schengelman, VP of R&D at Auth0,

  • where he leads the team exploring the future of AI and identity.

  • So cool.

  • So Damien, everyone is building for the direction of Gen AI,

  • artificial intelligence, agents, agentic.

  • What is Auth0 doing to meet that future possible?

  • So everyone's building Gen AI apps, Gen AI agents.

  • That's the fact.

  • It's not something that might happen, it's going to happen.

  • And when it does happen,

  • when you are building these things and you need to get them into production,

  • you need security, you need the right card rails.

  • And identity, essentially authentication authorization, is a big part of those card rails.

  • What we're doing at OZero is using our 10 plus years of identity developer tooling to make it simple for developers,

  • whether they're working at a Fortune 500 company,