Category: Organisational Design
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Stream of Teams
It was great to chat with Matthew Skelton about the intersection of Team Topologies and AI/ML product delivery – watch the recording. This was the subject of the final chapter of Effective Machine Learning Teams, in which we used the Team Topologies model to explore effectiveness at the level of “between teams”. We covered a…
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Effective topologies for Data and ML teams
I presented this talk at the Melbourne Data Engineering meetup, on a wild and wet Friday night. Having your cake and eating it too – Effective topologies for Data and ML teams (slides) In the talk I explore how Team Topologies provides patterns for reconciling fast flow of value with (multiple) specialisations in data and…
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Hopsworks and multidisciplinary ML
I recently had a brief but fun chat with Hopsworks about the multidisciplinary nature of building machine learning products, as part of their 5-minute podcast series hosted by Rik Van Bruggen. See the transcript and video at 5-minute-interview-with-david-colls-nextdata. Rik and I talked about how David, Ada and I address this multidisciplinary perspective in our book…
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Effective ML Teams on Thoughtworks Tech Podcast
I recently recorded an episode of the Thoughtworks Technology Podcast with my Effective Machine Learning Teams co-authors Ada Leung and David Tan, hosted by Scott Shaw and Ken Mugrage. The episode is number 146 – Building at the intersection of machine learning and software engineering. It was great to chat about the book and share…
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EMLT Q&A
A fun Q&A with Thoughtworks on the drivers, key messages and writing process for Effective Machine Learning Teams (EMLT) with my fellow authors Ada and David. It’s neat to be featured alongside all the other many great books from Thoughtworks authors. Find the book, trial and purchase options at O’Reilly, and find yourself a nice…
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Dealing with data inventory
Data held by businesses is often described as an asset. This can be misleading or even incorrect. In any case, data managed inappropriately leaves value on the table, inflates cost, reduces responsiveness, and creates risk. Some data held by businesses would better be described as inventory. It might one day be a true asset, but…
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Effective Machine Learning Teams in print
My book Effective Machine Learning Teams is now in print! Building ML solutions requires multi-disciplinary collaboration. EMLT shows how to use design practices to identify the right products, how to apply good data science and software engineering practices to build products right, and how to structure ML teams and organisations so that they are right…
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7 wastes of data production – when pipelines become sewers
I recently had the chance to present an updated version of my 7 wastes of data production talk at DataEngBytes Melbourne 2023. I think the talk was stronger this time around and I really appreciated all the great feedback from the audience. Check out the video below and the slides. Thanks to Peter Hanssens and…
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Perspectives edition #27
I was thrilled to contribute to Thoughtworks Perspectives edition #27: Power squared: How human capabilities will supercharge AI’s business impact. There are a lot of great quotes from my colleagues Barton Friedland and Ossi Syd in the article, and here’s one from me: The ability to build or consume solutions isn’t necessarily going to be…
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22 rules of generative AI
Thinking about adopting, incorporating or building generative AI products? Here are some things to think about, depending on your role or roles. I assume you’re bringing your own product idea(s) based on an understanding of an opportunity or problems for customers. These rules therefore focus on the solution space. Solutions with generative AI typically involve…