This episode was streamed live from Agile meets Architecture conference.

In this episode, we discuss the multi-year journey of Circle K’s eMobility organization as it scales to support growth from Norway to European and global markets.

The eMobility organization began as a small team focused on validating the electric vehicle (EV) charging business in Norway. However, due to its success, it quickly had to shift from “validating to scaling” and expand to various countries and multiple products in an industry that is still in development.

Throughout the episode, Eduardo and Guro will share valuable “mistakes”, lessons learned, experiments, methods, and practices we have employed during this journey. We will particularly emphasize the importance of breaking down functional silos within the organization as a means to support sustainable scaling. Initially, we focused on overcoming the Product and Technology silos. Still, in time, we went further to develop truly cross-functional value streams, also involving and continuously engaging with marketing, sales, operations, and other disciplines, with the goal of defining the best ways to support the activities necessary for rapid and sustainable business growth.

Eduardo and Guro have employed various ideas and techniques, including Domain-driven Design, Team Topologies, Wardley Mapping, and others. However, you will see that there are no silver bullets. The secret is embracing this as a continuous improvement process, involving people with knowledge and expertise, maximizing learning, and empowering value streams and their teams to drive the necessary design and decision-making with a clear long-term vision.

• Architecture Modernization Enabling Team

• Independent Service Heuristics (ISH)

  • https://github.com/TeamTopologies/Independent-Service-Heuristics

  • https://teamtopologies.com/news-blogs-newsletters/2024/8/7/newsletter-ish-enhancing-modularity-and-autonomy

• Core Domain Charts

• Susanne Kaiser: Architecture for Flow

This episode was streamed live from Agile meets Architecture conference.

We all know it - our team has become too big, meetings take too long, half of the conversations don’t apply to our work, and the sprint goal is now “finish all stories in the sprint”! The classic textbook and the chatbot are certain: The team should be split!

And this is indeed the optimal solution. But real life isn’t a textbook, and our resources aren’t infinite. What if instead of slicing to be a-two-pizza-team, we asked the question: “What do we actually need to work well together?”

After over 4 years working with several large data science and engineering teams that wrestled with multiple variations of the same problem, we’ve resisted the urge to split by the book.

Instead of insisting on the one right way, we want to show you how tuning in, listening, and deliberately choosing the solution, can bring back the fun, ease and coveted efficiency we all are after.

That could mean: changing who does what in the team, redrawing team boundaries, or combining pragmatic approaches of multiple organizational design systems like LeSS, Team Topologies, and Fluid Teams.

The trick is to stop chasing the perfect model and start designing something that actually fits both the team’s culture and unique problem domain. Think of it like tailoring a suit: it has to fit the people wearing it, not just look good on a cover.

Der Informatik-Pionier Peter Naur formulierte 1985 in seinem Aufsatz “Programming as Theory Building” die These, dass Programmieren im Kern bedeutet, eine Theorie zu entwickeln – ein tiefes Verständnis eines Problems und seiner Lösung.

Diese Perspektive erklärt, warum Änderungen an bestehenden Systemen so schwierig sind, wie Legacy-Software entsteht und weshalb iterative Softwareentwicklung so wirkungsvoll sein kann.

In dieser Episode diskutiert Eberhard Naurs Überlegungen und setzt sie in Beziehung zu aktuellen Herausforderungen der Softwareentwicklung – etwa zur verbreiteten Vorstellung im Kontext generativer KI, Programmieren bestehe primär lediglich im Erzeugen von Code.

Links

• Programming as Theory Building

• Prof. Christiane Floyd zu “menschenzentrierter Software-Entwicklung”

• KI = Bullshit

• Software-Entwicklung = Lernen?