[pards]

> 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

[xen2xen1]

Interesting point, does that mean AI with favor startup or startup like places? New tools often seem to favor less established and smaller places.

[mountainriver]

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