Err, I will disagree on this. It all depends on where you work at.

You can have a bugfree code, but release it in 6 months. Or you can have a code that creates outages once per month, but release it in 3 months (figure of speech, 6 months is optimistic for some projects).

By trying to optimize for 0 bugs, you are losing on the 3 month of business opportunity of high revenue. At FANG scale, that's a lot of money.

Disclaimer: G employee, but this is my own opinion etc.

I think you've intentionally taken what I said to an extreme that makes it absurd. Of course I wasn't saying people should comb through a program until it's bug-free before releasing it.

That said, no one (in their right mind) intentionally releases buggy code. They may release incomplete or under-tested code, of course. But that's not what I'm talking about.

I'm saying that when someone feels like they're "done" (in a reasonable amount of time), some people will end up with more bugs than others. If the trade-off is 3 more hours of work for 1 fewer bug, that's an incredible economy.

And, of course, no metric is perfect or comprehensive. But "bugs per hour" is much better than LoC per hour.

FANG = Facebook, Amazon, Netflix, Google

Thanks, your answer has shed some light on what would be expected. I am glad that the industry does not base productivity on LOC. I also, now know some red flags.

What matter is not the number of lines of code you write. IT's what value you create, how much revenue you generate, or help generate. You can have the worst code, and still make hundreds of millions of dollars. At the end of the day, for a business, that's what matters. Once you are coming to the scale of the code (modularity or lack thereof, etc), you can always rewrite.

Not directly about development, but this should be somewhat of a rule of thumb in general: https://www.slideshare.net/dmc500hats/best-strategy-is-speed...

Time is important. More important than you think.

The value created for the company seems to be the best way to track productivity. It seems that how accurate the chosen metric for the value created is the key thing to watch out for.