Organizational design and Team Topologies after AI

Thoughtworks Technology Podcast

Thoughtworks

Careers, Business, 907234, Technology

4.7 • 53 Ratings

🗓️ 4 September 2025

⏱️ 43 minutes

🔗️ Recording | iTunes | RSS

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Summary

Managing technological change in an organization — particularly a large and complex one — has always been challenging. But thanks to the rapid adoption of AI in all kinds of spheres, from knowledge management to software development to content creation, it's becoming more difficult than ever. How do you strike a balance between governance and safety and autonomy and empowerment? How should teams be structured and how should they work together?

In this episode of the Technology Podcast, Matthew Skelton and Manuel Pais — authors of the influential Team Topologies book — join hosts Birgitta Böckeler and Ken Mugrage to discuss what AI means for organizational design. They discuss how AI is changing team capabilities, what it means for cognitive load and knowledge sharing and how to ensure there's structure and control without constraining experimentation and creativity.

With the second edition of Team Topologies set to be published in September 2025, Matthew and Manuel used the conversation to explore the evolution of their ideas and what they've learned from working with and listening to the stories of many different organizations around the world.

Learn more about Team Topologies: https://teamtopologies.com/

Transcript

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0:00.0	Welcome to a new episode of the ThoughtWorks Technology podcast.
0:12.0	This time we'll be talking about AI once more and about more specifically about using
0:18.5	AI in engineering organizations or more broadly, even for knowledge work.
0:23.5	And my name is Biggita Bockela. I'm a distinguished engineer at ThoughtWorks, and I will be one of your two hosts today, together with my colleague, Ken McGrath.
0:33.1	Hi, everybody. I'm Ken, one of your regular hosts. Good to speak to you again.
0:36.3	And we have two special
0:37.6	guests today of Team Topologies fame, Matthew Skelton and Manuel Paich. Matthew, do you want to go
0:45.4	first and quickly introduce yourself? Sure. Hi. It's great to be here. Thank you so much for inviting
0:50.5	us. We're super excited because we've got the second edition of the Teen Porties Book launching in September 2025. So it's great to be talking about it at this stage,
1:00.6	particularly the AI angle. It's a great time to be like sharing some insights around this.
1:06.3	Yeah, the same. Thanks for invitation. It's really interesting to talk about AI in the context of organizational design and how things might change in the future. And yeah, I really appreciate the invitation.
1:21.8	Welcome. And I think we should set the scene first, maybe like what type of AI usage we're talking about and for what
1:29.0	types of use cases. I mean, I was already talking about, we want to talk about knowledge work,
1:32.6	how to use AI for that, and probably more specifically in the context of engineering organizations.
1:37.8	But there's like such a broad range of situations in which we can use AI, right?
1:42.8	Like there's a lot of talk about throw away work for AI all the
1:46.9	way to like more long-lived sustainable work. What type of range are you all seeing out there and what
1:54.0	types of use cases are you most interested in? That's a good question, right? So there's all kind of
1:59.3	different, there's different flavors of AI to start with. There's the generative stuff, which is what most people think about. And there's a traditional AI machine learning stuff. The traditional stuff clearly is massively valuable in terms of protein folding and large data set analysis and a whole of amazing stuff that you can do there. They're kind of finding a needle in a haystack data search problem.
2:20.0	So that's obviously all still relevant, but the spotlight is purely on the generative
2:24.8	AI stuff at the moment.
2:25.8	I mean, they're actually slightly changing.
	...

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