But yes, if you change incentives, you can change behavior. And if you can find a way to create and enforce incentives that push toward an outcome you want, then you get more of that outcome. This is a good lesson to remind people of: incentives matter. So often---especially in discussion of public policy---we see conflation of stated desires with incentives, and of incentives with "cash paid to someone". The former is fallacy, and the latter myopic.

Comments URL: https://news.ycombinator.com/item?id=47557179

Points: 11

# Comments: 1

That is a nihilistic take. That it's pointless and everything about the domain (measurement of productivity) is meaningless.

"Productivity" is no more made up of a concept than "good work". The fact that many attempts to measure it are quite dumb (e.g., the idea of using LOC as a metric) does not mean the whole idea is not worth considering or discussing.

That is an unsatisfying answer. I can point to anecdotes that suggest AI is hurting productivity or improving it, but those don't make an argument. And the extremes on either side make it very difficult to consider. How do you weigh "An LLM deleted my production database" against "I built a business on the back of AI-assisted software"?

I think we have to wait and see. And we should revisit questions of cost and value continuously, not just about LLMs, but generally in life. Most of my motivation (though not an overwhelming majority) around using LLMs right now is a mix of curiosity and wanting to avoid the fate of the steam shovel.

The full PDF is available for download. It's mostly a series of essays, so you can pick and choose and read nonlinearly. It's worth thinking about beyond nihilistic takes.

I would honestly appreciate constructive feedback on LLM usage, because, as I stated, I am constantly having to rework code that LLMs generate for me. The value I get from LLMs is not in code generation.

I'm not sure if this is a direct response to the article or a general point. The article includes an appendix about my use of LLMs and the domains I have used them in.

I am fully on board with gen AI representing a paradigm shift in software development. I tried to be careful not to take a stance on other debates in the larger conversation. I just saw too many people talking about how much code they're generating as proof statements when discussing LLMs. I think that, specifically---i.e., using LOC generated as the basis of any meaningful argument about effectiveness or productivity---is a silly thing to do. There are plenty of other things we should discuss besides LOC.

If an activity (getting code into source files) used to take up <50% of the time of programmers, then removing that bottleneck cannot even double the throughput of the process. This is not taking into account non-programmer roles involved in software development. This is akin to Amdahl's law when we talk about the benefits of parallelism.

I made no argument with regard to threat to the profession, and I make none here.

(author here)

Happy to discuss further.

I have given instructions to repeat, but more slowly, and people will still click through errors without a chance to read. I have asked people to go step by step and pause after every step so we can look at what's going on, and they will treat "do thing and close resulting error" as a single step, pausing only after having closed the error.

The only explanation I have that I can understand is that closing errors and popups is a reflex for many people, such that they don't even register doing it. I don't know if this is true or if people would agree with it.

I've seen this with programmers at all levels of seniority. I've seen it with technically capable non-programmers. I've seen it with non-technical people just trying to use some piece of software.

The only thing that's ever been effective for me is to coach people to copy all text and take screenshots of literally everything that is happening on their screen (too many narrow screenshots that obscure useful context, so I ask for whole-screen screenshots only). Some people do well with this. Some never seem to put any effort into the communication.