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
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
Remember that feeling when a new tool promised to change everything, only to leave you wondering if it actually made a difference? That's often the quiet concern swirling around the integration of Artificial Intelligence (AI) into our software development lifecycle (SDLC). AI is no longer a futuristic concept;
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
Recently, engineering metrics, developer productivity, and developer experience have gained significant attention in leadership circles. But large organizations have started to measure the effectiveness of their engineering organizations and systems for quite a while. DORA: Although a lot of leaders in the industry had their own signals and metrics to
EvolveDev
Welcome to the Evolvedev blog! We are excited to welcome you on our journey in helping software engineering organizations achieve excellence. Software is the backbone of every business. However, the process of developing and maintaining this software can be complex and costly, often operating in silos. With the age of