Is there space for 'craft' in the world of AI?

My friend Alan wrote yesterday in a thread on Bluesky: In my end-of-year review I was described as a 'craft engineer' more than once. I don't disagree with this, but I have to wonder if this approach (one that has been comfortable for me for more than 10 years) is totally incompatible with modern AI tooling and a 'deliver it' mindset in a team? I want to split this across what I do; use the new tools and deliver quickly in my workplace, and not use AI at all for my personal work and use that for the 'craft' I can see these being complimentary to each other, but I am struggling with the change in my day job My current AI use at work is mostly limited to using the tools to collaborate on a plan and scope for a change, then writing the change we have agreed upon by hand. This is a happy medium for me, but it's not very conventional and I am noticeably slower than team mates on pure pace of shipping When we have things like a large state machine to determine lazy loading in a component so…