Engineering Excellence
This is one of the most common problems I hear from Directors and VPs of Engineering: "I want my team to use data more, but I don't know where to begin." How can I use metrics without making it seem like "big brother"? It&
Engineering Excellence
Do you ever feel like you're always going one step forward and two steps back? Your team is sending out code and merging pull requests, but the project's deadlines keep getting pushed back. It seems like you're running in place, using up resources without
Engineering Excellence
I've seen a lot of metrics come and go in more than a decade of my experience. But one has been very stubborn: Cycle Time. People often use it as a guide for how well engineers do their jobs. It seems like the logic is simple: we must
Engineering Excellence
We've been using negative indicators, like a decline in output, missed deadlines, or an increase in bugs, to gauge the health of our teams for years. We've been told to start looking for the "burnout" in burnout. However, what if we're not
AI in Engineering
So, we've covered the "what" and the "why." In our first post, "Beyond the Hype," we laid out a strategic map for bringing AI into your world. In the second, "Measuring the Unseen Hand," we talked about how to measure
AI in Engineering
The rise of generative AI is not just another trend; it's a fundamental shift in the technological landscape. For software engineering leaders, the question is no longer if they should adopt AI, but how. The temptation is to jump on the bandwagon, acquiring a plethora of AI-powered tools