ymyms

I was shocked by this as well. I think it's a natural property of large organizations and it takes great effort and great leaders to fight it.

The way I think about it is that building something truly successful comes with a tremendous amount of momentum. So much momentum that growth for these companies still occurs.

The people hired into a mature organization are literally there just to keep the lights on and let the momentum do its work. They also create and grow their little fiefdoms.

You can try and build something and innovate there, but it takes a deeply concerted effort to try and sustain it. Even if something is made wildly successful and is growing 50-100% year over year, it still likely pales in comparison to the 0.005% growth of the large core business.

Even if the new innovation is given space to breath, it can be killed at any point by the core business as the fiefdoms look over and say: that should be part of my org, or those resources can be better spent on the core business. So instead of waiting the years it takes for the new, small thing to grow large enough to be important it is easily killed by the parts of the organization just keeping the lights on.

There are definitely salient points in the article and I appreciate its value in imploring us to really stop and consider the ramifications of what this technology might deliver. I think the analogy to cars and the unintended consequences for all manner of society is particularly apt.

That said, the final point is one I take issue with:

> For example, I’ve got these color-changing lights. They speak a protocol I’ve never heard of, and I have no idea where to even begin. I could spend a month digging through manuals and working it out from scratch—or I could ask an LLM to write a client library for me. The security consequences are minimal, it’s a constrained use case that I can verify by hand, and I wouldn’t be pushing tech debt on anyone else. I still write plenty of code, and I could stop any time. What would be the harm?

To me, there is no intrinsic value in solving this problem other than rote problem solving reps to make you a better problem solver. There isn't anything fundamental about the protocol they've never heard of that operates the lights. It's likely similar to many other well-thought out protocols in the best case and in the worst case is something slapped together.

There are certainly deeper, more fundamental concepts to learn like congestion control algorithms in TCP. Most things in software though are just learning another engineer's preferences for how they thought to build something.

I poke at this because if an exercise only yields the benefit of another rep of solving a problem, then it holds less water to me. I personally don't think there will be fewer problems to solve with this technology, just a different sort at a different layer of the stack.

They apparently are working on and are going to release 2(!) different versions of siri. Idk, that just screams "leadership doesn't know what to do and can't make a tough decision" to me. but who knows? maybe two versions of siri is what people will want.

A human SWE can use an LLM to refactor and reduce some of the debt just as easily too. I think fundamentally, the possible rate of new code and new technical debt introduced by LLMs is much higher than a human SWE. Left unchecked, a human still needs sleep and more humans can't be added with more compute.

There's an interesting aspect to the LLM debt being taken on though in that I'm sure some are taking it on now in the bet/hopes that further advancements in LLMs will make it more easily addressable in the future before it is a real problem.

All code is technical debt though. We can't spend infinite hours finding the absolute minima of technical debt introduced for a change, so it is just finding the right balance. That balance is highly dependent on a huge amount of factors: how core is the system, what is the system used for, what stage of development is the system, etc.

I also feel like it makes me more productive but measuring software engineering productivity is famously difficult. If there was an easy way to measure it, managers at bigco would have employed it with abandon years ago.

Huh? Where did I say that's what I like? I'm just trying to discuss for discussion's sake. Personally, I want a world that rewards the people who put their thought, care, and craftsmanship into something more than those that don't. In order to live in that world, I think we need to discuss the parts (maybe the whole) that don't and why that might be.

I didn't mean to imply LoC as a measurement of productivity. What I really mean is more "amount of useful code produced to a level the human-using-the-llm determines to be useful".

To try and give an example, say that you want to make a module that transforms some data and you ask the LLM to do it. It generates a module with tons of single-layer if-else branches with a huge LoC. Maybe one human dev looks at it and says, "great this solves my problem and the LoC and verbosity isn't an issue even though it is ugly". Maybe the second looks at it and says, "there's definitely some abstraction I can find to make this easier to understand and build on top of."

Depending on the scenario and context, either of them could be correct.

My gut says that is not a property of LLM evangelists, but a property of current internet culture in general. People with strong, divisive, and engaging opinions seem to do well (by some definition of well) online.

I mean, isn't driving the business forward really what matters (outside of academia, open source, and other such endeavors). We live in a hyper competitive market. All else being equal, if company A can produce "millions of lines of slop", constantly living on the knife-edge of disaster but not falling over it, they will beat company B that artificially slows themselves down. Up until the point company A implodes, but that's not necessarily a given if pre-LLM companies are any indication.

"I find LLMs useful as a sort of digital clerk - searching the web for me, finding documentation, looking up algorithms. I even find them useful1 in a limited coding capacity; with a small context and clear guidelines."

I am curious why the author doesn't think this saves them time (i.e. makes them more productive).

I never had terribly high output as a programmer. I certainly think LLMs have helped increased the amount of code that I can write, net total, in a year. Not to superhuman levels or even super-me levels, just me++.

But, I think the total time spent producing code has gone down to a fraction and has allowed me more time to spend thinking about what my code is meant to solve.

I wonder about two things: 1. maybe added productivity isn't going to be found in total code produced, because there is a limit on how much useful code can be produced that is based on external factors 2. do some devs look at the output of an LLM and "get the ick" because they didn't write it and LLM-code is often more verbose and "ugly", even though it may work? (this is a total supposition and not an accusation in any way. i also understand that poorly thought out, overly verbose code comes with problems over time)

Heh yeah, my comment does kinda scream credit card. What I really mean is something programmable for narrow use-cases like multiple forms of payments, transit, or other stuff like building access.

I wonder if this makes room in the market for some simpler device for payments. Something like a wearable that you can tap-to-pay and has the signed software attenuation but nothing else so you can't be tracked using GPS.