Post

My impression is that AI coding is on a "pick two of three" triangle: scope, ship speed, and correctness. Small tools are (speed + correctness) fast prototypes are (speed + scope) and big projects are (scope + correctness). Every project that tries to be all three degrades to "fast prototype."

Definitely, probably the interesting thing is that the acceleration doesn't seem to somehow distribute equally. I think probably because the scope has gone way up

1 repost20 likes

And a lot for developers my self included are doing a *ton* of maintained related things we never really had the appetite for in the past to do due to the time and effort to do.

Like building out comprehensive service level mocks for upstream dependencies outside your control. Hardening infrastructure across the board by auditing your terraform setups. Updating documention, building our buzzing and chaos suites for complex systems to test durability and recovery, ect ect

although the attention of the other people on your team that used to be scarce (for eg code reviews and long term architecture discussions) is now too small to detect with the naked eye