Blog
The case for an AI-Augmented Development methodology
Let’s examine what engineering teams, AI Champions and AI communities of practice need to explore, reflect on, and share. So they can apply new learnings across different teams and contexts, advance the craft, and scale AI-Augmented Development adoption.
Where AI Ends and Human Value Begins
Replacing developers with AI often leads to costly organisational mistakes. Discover how leading organisations leverage uniquely human strengths to get the best out of AI, and how engineers can future-proof their careers.
AI Coding Test-first Vs Test-after: pros & cons
Test-First is the clear winner of the pre-AI coding era. But how does AI-assisted development change the balance between Test-First and Test-After? Who is the winner now?
Coding with AI: 2 alternative philosophies
Broadly speaking, AI-coding techniques fall into two distinct and alternative philosophies, you don’t want to confuse or mix.
AI-assisted coding: how to ensure real productivity gains?
Recent studies show that the productivity impact of AI-assisted coding can even be negative. A “perception gap” can make developers feel more productive when their output drops. Here, I explore ways to pursue real positive productivity gains.
2025 digest: Agile the ugly, the bad and the good
For all companies that are now sustaining or gradually restarting their investments in Agile – here is a summary of decades of lessons learned by companies adopting Agile
Complexity-thinking: selection of sources
Selection of sources worth following from the book: The forgotten new philosophy of work, management & leadership
Agile: How practitioners have changed from the pioneers to today
Many have already explored the trajectory of Agile adoption, the changes in sentiment toward Agile, and the recent challenges.
This is a new look at how the population of Agile practitioners changed over time.
When/How to move effectively tasks/responsibilities outside the team (2-part)
Whether it is to a Subject Matter Expert, an external contractor, an Agency, a Global/shared Function, a Team Topologies’ Platform team or a Complicated subsystem team, when and how can some tasks and/or responsibilities be effectively moved outside the team?