A very very large part of programming is boilerplate code you cant get past, it must be written.

A huge part is integration testing.

You have like hundreds or thousands of tests that are very repetitive. "Open this, click that, do this, type that, wait... assert this happens"

You have all these in a human readable format/doc provided to you by your requirements team

You uabe to convert all of that into code so a program can do the steps, such that it runs every day to confirm "website isnt broken boss!"

Converting all that human text into code is very easy but very monotonous

It can be tens of thousands of lines of code, easily.

This type of task is extremely easy for AI though, especially if you start it off with 10~15 examples to show it how it outta be done

Then you just give it the doc and go "okay draw the rest of the owl please"

This is called "nth shot prompting", where it has samples to start with and then it just copies your work 1000 times given input.

AI is extremely good at this.

It can turn weeks of work into hours.

The ability to turn human contextual English into code is one of its top skills, and turns out for a serious prod scale app at a company, thats like... 90% of software dev

And since we can work in parallel, I can focus more of my effort on that remaining actually challenging 10% where stuff matters more.

Its like swapping from pulling a wagon by hand of dirt to a job site, to instead pulling it with machine.

I get that part done 10x faster/easier, or better, and now I can actually put my time/energy into way more important shit than just hauling dirt around.

Summarized: when ppl talk about it making them do their job faster/better, its usually cuz it got rid of a bunch of boring parts and now they can focus on the actually important parts of their job more, and thus produce way higher quality results net.