> code output is rarely the reason why projects that I worked on are delayed
This is very true at large enterprises. The pre-coding tasks [0] and the post-coding tasks [1] account for the majority of elapsed time that it takes for a feature to go from inception to production.
The theory of constraints says that optimizations made to a step that's not the bottleneck will only make the actual bottleneck worse.
AI is no match for a well-established bureaucracy.
[0]: architecture reviews, requirements gathering, story-writing
[1]: infrastructure, multiple phases of testing, ops docs, sign-offs
Interesting point, does that mean AI with favor startup or startup like places? New tools often seem to favor less established and smaller places.
Disagree it’s normally the integration and alignment of systems that takes a long time e.g. you are forced to use X product but their missing a feature you need to wait on