1.
In his recent white paper “AI-Ready Code: How Code Health Determines AI Performance”, Adam Tornhill comes to the conclusion that GenAI is even more inclined to create errors due to bad code than human developers.
You can read the full paper here.
2.
In her article “Building Foundations for Continuous (AI-accelerated) Change”, Susanne Kaiser points out that team topology and architecture are crucial if you want to benefit from the faster pace of AI-generated code.
You can read the full article here.
I find this is especially interesting in the light of this quote from the book “Accelerate”, by Kim, Humble and Forsgren, about what kind of architecture you need to enable high software delivery performance:
“We set out to discover the impact of architectural decisions and constraints on delivery performance, and what makes an effective architecture. We found that high performance is possible with all kinds of systems, provided that systems – and the teams that build and maintain them – are loosely coupled.”
I would like to add 'high cohesion' (from a business perspective) to 'loosely coupled' as another important pairing principle.
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