Because usually the people who lose their jobs are people who do not adapt to the market.

Right now it's not clear in which direction everything is involving and that's why people experiment with handing all their data to random agents, figuring out how to store and access context, re-use prompts and other attempts to harness this tech. Most of these will maybe be useless in a year as they might be deeply integrated into the next wave of models but staying on top of the development has always been part of the fun of working in this field.

People are building bots to do the most legible thing possible which is feature in X amount of time. But it doesn't matter if the bottleneck is human thinking time required to output quality code rather than X amount of code written.