(1) The “finish and move on” engineer
They care about quality, but coding is not their whole identity. They value their time, their family, their hobbies, and the ability to close the laptop at 5. AI helps with the repetitive parts of the job: boilerplate, simple tests, first drafts, migration scripts, documentation cleanup, and sometimes even parts of the important coding part
That is not a bad thing and very popular in corporate world. It helps them finish the work, reduce the boring parts, and move on with life.
(2) The engineer who is deeply attached to the craft
Then there is another group: the engineers who enjoy understanding the system, debating trade-offs, and enjoy the deeper logic behind every single loc. They are not against AI, but they tend to use it with more caution.
I often see senior folks being more skeptical, not because they reject AI, but because they know where the hard part of software actually lives: incidents, operations, legacy systems, unclear requirements, and people - team context.
They ack that AI is useful for removing some of the boring work. But they do not let it drive their works.
Both patterns are fine. But it is clear to me that the productivity gain from AI is still a bit of a mist, it depends heavily on the person using it, their skill level, their judgment, and the incentives around them