The hidden cost of AI coding

This has been my experience as well, and really leaves me puzzled as to what anyone is gushing about.

Can I just about corral the LLM into producing working output? Yea, sometimes. From a technology perspective, that’s pretty cool!

But is it a productivity boost? Absolutely not. Like not even close. Every time it would have been faster for me to just write the code myself.

I really don’t know how to square the vast gulf between my experiences and many other peoples’.

I'm still spending less effort/time. A very significant amount.

I do write plenty of things myself. Sometimes, I ignore AI completely and write 100s of lines. Sometimes, I take copilot suggestions every other line, as I'm writing something "common" and copilot can "read" my mind. And sometimes, I write 100s of lines purely by prompting. It is a fine line when to do which; also depends on mood.

I am not worried about that as I spend hours everyday reading. I'm also the type of person who, when something is needed in a document, do not search for it using CTRL+F, but manually look thru it. It always takes more time but I also learn adjacent things to the topic I need.

And I never commit a single line from AI without reading and understanding it myself. So it might come up with 100 line solution for me, but I probably already know what I wanted and off chance it came up with something correct but in a way I did not know, I do read and learn it.

Ultimately, to me, the knowledge that I can !reset null in docker compose override is important. Remembering if it is !null reset or reset !null or !reset null (i.e., syntax) is not important. My offhand knowledge is not getting worse as I am constantly learning things; I just focus less on specific syntaxes or API signatures now.

You can apply the same argument with IDE. Almost all developers will fail to write proper JS/TS/Java etc without IDE help.

Unfortunately, I'm at a stage of personal life where I do not have time to blog. I'd love to but :(

The stuff I work on for company is confidential and even getting authorization to use AI was such a hassle.

Based on some of your replies, I think you have an impression of current generation AIs that is 100% wrong. I can not blame you as the impression you have, is what the AI companies want you to have, that's what they are hyping.

In another comment, you mentioned someone should demo how AI can add a non-leaf feature to a non-trivial LOC codebase. This is what AI companies say AI can do. But the truth is, (current gen) AIs can not do this except a few rare cases. I can not demo this to you as I can't do this and do not attempt to do it either on day to day tasks.

The issue is context. What you are asking requires AI to have a huge amount of context that it simply is not equipped to handle (at least not right now).

What AIs are really good at is to do small fragment of a task given enough clear requirements.

When I want AI to write a Handler in my Controller, I don't just ask it to "write a function to handle POST call for entity E."

I write the javadoc /* */ comment that defines the signature and explains a little about how the core process of this handling works. I can even copy/paste similar handler from another controller if I think that will help.

Ultimately, my brain already knows the input, output and key transformations that needs to happen in this function. I just write minimal amount (esp comments) and get AI to complete the rest.

So if I need to write a non-leaf feature, I will break it down to several leaf features and then pass it on to AI and if needed, manually assemble them.

I had to write 500LOC bash script to handle a software deployment. This is not the way to do it but I was forced by circumstances created by someone else. Anyways, if I had to write the whole thing by hand, it'd take multiple days as bash syntax is not forgiving and the stuff I needed to do in the script were quite complex/crazy (and stupid).

I think I wrote about 50+ lines of text describing the whole process, which you can think of as a requirement document.

With a few tries, I was able to get the whole script with near accuracy. My reading revealed some issues. Pointed them to AI. It fixed them. Tests revealed some other issues. Again, AI fixed them after pointing out. I was able to get the whole thing done in just an hour or so.

I'm really struggling to understand your argument, are you trying to argue in short-term or long-term trends? I'm trying to argue that in aggregate, life is getting better for people, while also awknowledging that there's not an equal distribution. For example, food has decreased in price 4x since 1900 in real terms[1]. I don't see how that's not more affordable.

> You skated right past the need for a smartphone.

Hmm? Like when I said "Another cost is it's pretty much impossible to do anything without a smartphone and internet"?

> a good Uber Eats driver can make about $13 to $16 an hour

Source? That doesn't line up with what I found.

> A performance, mind, that is subject to dozens of factors entirely outside the control of the driver.

This is just FUD if you haven't cited your sources on average/median/distribution of pay in whatever area.

You have a very good point on liability issues though.

> The solution is I think quite simple here

Thus increasing prices of rides, causing users to stop using the service, further shrinking pay? Uber just started being profitable after dumping billions of dollars in subsidies, on top of bad pay. If you make them full-time employees, you may just shut off the one source of income they have.

Uber won because they offered a superior service to taxis. I'm not going to open the can of worms of their predatory behavior, but there was still a significant part that was a better service.

Again, I am planning on helping these people, I think they should be helped, but you really need to think through what could happen if you force a company to become insolvent.

[1] https://ourworldindata.org/grapher/long-term-prices-food?foc...

  > However, in that world, a company that chooses not to contribute

I swore I addressed this point, but I can't find it. You're right. I should have addressed this.

But this is still not an optimal strategy. It can give you a short term edge, but you're completely right that it destroys the natural coalition equilibrium. The result is that this destroys the coalition. You get the benefit for a small time period but it doesn't take long for the coalition to be abandoned and once that is done, you no longer gain from this strategy. In this situation the total utility in the system decreases! Not just globally, but each player's utility drops! That's a major problem! It is sacrificing long term rewards for short term ones. Importantly, those long term rewards are quite significant while the short term ones are not.

  > How do we adjust the incentives so that bad actors are not motivated to cheat the system?

My answer? The government. I'm not a fan of big government, but they definitely have a role to play in the economy. A third party actor that serves as a moderator. Regulation to ensure that (near) globally beneficial (yet unstable) equilibria are maintained. Such regulation is beneficial to all parties involved, even the one that wants to undermine the coalition. I mean we can't just have shit being fucked up every time there's a dumb or malicious actor. A lot of things are unstable equilibria and it does take work to maintain them. A third party (especially one that benefits from global utility as opposed to individual utility) is necessary for stability. The other answer is, of course "The People". But this is a much more chaotic group, more easily influenced by nearsighted actors who can often convince them to also be shortsighted, especially when dealing with more abstract concepts..

  > this is similar to playing Iterated Prisoners' Dilemma

It's worth noting here that Tit-for-tat strategies are optimal in this game AND maximal utility to any party is achieved when all parties cooperate continuously. But it is worth noting that humans are a bit irrational and have memory. Also worth noting that human actors are not rational. Hence the need for a third party moderator, which logically benefits both parties by saying "Stop being dumb and shooting yourself in the foot. This is an iterative game."

For some reason people think zero-sum games are common. Lump of Labor (Fixed-Pie) Fallacy is really common[0]. I do see high rates of zero-sum thinking around here on HN and in CS communities, and I'm not sure why it is so common. While I don't have the same expectations for the general public, we create things out of essentially limitless resources. We frequently create value that does not require additional compute or meaningful consumption of current resources (which is also increasing as time marches on). Our whole job is built on the fact that the pie continually grows in size and we are strongly rewarded for making the pie larger in the first place!

[0] https://en.wikipedia.org/wiki/Lump_of_labour_fallacy