It is kind of funny that throughout my career, there has always been pretty much a consensus that lines of code are a bad metric, but now with all the AI hype, suddenly everybody is again like “Look at all the lines of code it writes!!”
I use LLMs all day every day, but measuring someone or something by the number of lines of code produced is still incredibly stupid, in my opinion.
It all comes from "if you can't measure it you can't improve it". The job of management is to improve things, and that means they need to measure it and in turn look for measures. When working on an assembly line there are lots of things to measure and improve, and improving many of those things have shown great value.
They want to expand that value into engineering and so are looking for something they can measure. I haven't seen anyone answer what can be measured to make a useful improvement though. I have a good "feeling" that some people I work with are better than others, but most are not so bad that we should fire them - but I don't know how to put that into something objective.
Yes, the problem of accurately measuring software "productivity" has stymied the entire industry for decades, but people keep trying. It's conceivable that you might be able to get some sort of more-usable metric out of some systematized AI analysis of code changes, which would be pretty ironic.
Ballmer hasn’t been around for a long long time. Not since the Red Ring of Death days. Ever since Satya took the reins, MBAs have filled upper and middle management to try to take over open source so that Sales guys had something to combat RedHat. Great for open source. Bad for Microsoft. However, Satya comes from the Cloud division so he knows how to Cloud and do it well. Azure is a hit with the enterprise. Then along comes AI…
Microsoft lost its way with Windows Phone, Zune, Xbox360 RRoD, and Kinect. They haven’t had relevance outside of Windows (Desktop) in the home for years. With the sole exception being Xbox.
They have pockets of excellence. Where great engineers are doing great work. But outside those little pockets, no one knows.
I believe the "look at all the lines of code" argument for LLMs is not a way to showcase intelligence, but more-so a way to showcase time saved. Under the guise that the output is the/a correct solution, it's a way to say "look at all the code I would have had to write, it saved so much time".
It's all contextual. Sometimes, particularly when it comes to modern frontends, you have inescapable boilerplate and lines of code to write. Thats where it saves time. Another example is scaffolding out unit tests for series of services. There are many such cases where it just objectively saves time.
I wonder if we can use the compression ratio that an LLM-driven compressor could generate to figure out how much entropy is actually in the system and how much is just boilerplate.
Of course then someone is just going to pregenerate a random number lookup table and get a few gigs of 'value' from pure garbage...
it's still a bad metric and OP is also just being loose by repeating some marketing / LinkedIn post by a person who uses bad metrics about an overhyped subject
Ironically, AI may help get past that. In order to measure "value chunks" or some other metric where LoC is flexibly multiplied by some factor of feature accomplishment, quality, and/or architectural importance, an opinion of the section in question is needed, and an overseer AI could maybe do that.
I use LLMs all day every day, but measuring someone or something by the number of lines of code produced is still incredibly stupid, in my opinion.