> Now we are shifting the goalpost. Who even claimed AI solves 100%. I think you lost track of the discussion. I pointed out that in the absolute best case sce

> Now we are shifting the goalpost. Who even claimed AI solves 100%. I think you lost track of the discussion. I pointed out that in the absolute best case scenario LLMs only focus on tasks that represent a fraction of a software engineer's work. Then, once you realize that, you will understand that the total gains of optimizing away the time taken on a fraction of a task only buys you a modest improvement on total performance. It can speed up a task, but it does not and cannot possibly eliminate the whole job. To see what I mean, see Amdahl's law. https://en.wikipedia.org/wiki/Amdahl%27s_law https://en.wikipedia.org/wiki/Amdahl%27s_law Again, only a fraction of the tasks of a regular software engineering role involves writing code. Some high-profile roles claim their entry level positions at best spend 50% of their time writing code. If LLMs can magically get rid of said 50%,the total speedup is at best 2x speedup in delivery. You can look at that and think to yourself "hey that's a lot". That is not what's being discussed here. I mean, read the blog post you are commenting on. What's being discussed is that LLMs reduce time spent on a fraction of the software development tasks, but work on other software engineering activities increases as it's no longer blocked by this bottleneck. As others have wrote, the so-called AI doesn't reduce work: it intensifies it. https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies-it https://hbr.org/2026/02/ai-doesnt-reduce-work-it-intensifies... Also, why do you think the phenomenon of AI-induced burnout, dubbed AI fatigue, is emerging? Processes are shifting, but the work is still there.