The author lists specific tasks LLMs can't do today. But there's no fundamental reason they won't be able to in the near future. Domain expertise, understanding downstream effects, configuring CI pipelines - these are all learnable patterns. As models get larger, are trained on more diverse datasets, size of context window increases, and new architectures emerge, these capabilities will come online rapidly. The jump from GPT-3 to GPT-4 was substantial, and we should expect continued leaps.
This doesn't mean human developers will become obsolete overnight. But it does mean the nature of software development work is likely to change significantly. Lower-level coding tasks may be increasingly automated, shifting focus to higher-level design, architecture, and problem framing.
Rather than dismissing the potential impact, we should be preparing for a world where AI significantly augments or even replaces many current development tasks. This might involve focusing more on skills that complement AI capabilities or exploring new areas where human creativity and insight remain critical.