Given Gartner’s projection that by 2028, 75% of enterprise software engineers will use AI code assistants, how do you anticipate this shift will impact your negotiations with consulting companies regarding developer rates? Specifically, how will you balance the value provided by human expertise with the efficiencies gained through AI augmentation in these discussions?

I expect improvement in efficiency and quality, but fundamentally, the majority of time in a software development project is not in the code writing. The human factors of figuring out exactly what is needed and how to deliver on that need doesn't change with AI. 

My mother is fond of saying that your wardrobe grows to fill your closet size, and I think that applies in so many other areas too. As we increase the capabilities to deliver, I expect the size of our scopes to grow as well. AI will make the previously unobtainable requests possible, which will consume the availability created by AI. 

AI is like a magic wand, but you still need a magician to wield it. With AI code assistants, handling simpler applications becomes easier, but complex legacy applications remain challenging. Developers who don't upskill will inevitably lose their value, while those who stay current and continuously add value will be in high demand. These skilled developers may use AI assistants and develop application-specific AI components, like chatbots, to serve business needs. In a nutshell, it's still about T&M; technology and skills will vary. To give a simple analogy, just as IDEs have significantly reduced turnaround time for developers compared to writing Java and C++ code in notepad, AI code assistants will help roll out projects faster. However, this can sometimes lead to unrealistic expectations.