On the other hand, some companies are pushing the idea that engineers should build robust self-evaluating agent pipeline with human feedback in the loop so that agents write most of the production code. Creao's CEO said that they rearchitected their entire production systems in two weeks this January. He also claimed that their agents implemented so many features so fast that they had to wait their business development to catch up.

I wonder how we can evaluate these two options: using AI to 100X the output versus using AI to advance one's craft.

In the meantime, the productivity gain of AI is real. Case in point, An engineering org of Snowflake has met all its OKRs ahead of time in the first quarter for the time in the company's history. It had never happened, and usually meeting 70% of the planned OKR would be considered an achievement. I can imagine the stress of the engineers when they see such outcome.