Doing the SDLC in the AI Era: How to Use AI Efficiently
I haven’t written a blog post in a while, but this topic has been on my mind because so many teams are still struggling with it: where does AI actually fit in the software development lifecycle? AI is here, and at this point that is no longer the interesting part. The more important question is how to use it strategically. As these tools become more expensive, organizations need a clearer plan for where AI creates real value and where it simply adds cost, noise, or unnecessary complexity. When generative AI first exploded into the workplace, many companies rushed to experiment with it without fully understanding how it fit into their delivery model. Some teams wanted to use it everywhere. Others pushed back hard, especially when the conversation turned to job security. A few years later, I still see many organizations wrestling with the same underlying problem: they are treating AI as a blanket strategy instead of a tool that should be applied selectively. So here is my view...