It's simple. AI speeds the 80% of development that was never the blocker.

Arguably makes the remaining 20% even harder to handle.

I'm sure that AI can be a huge boost to great, mature developers. Which are insanely rare in an industry that has consistently promoted brainless ivy league coders farming algo quizzes for months.

But those with a huge sensibility and experience can definitely be enabled to produce more.

But the 20% is still there and again, it's easy to make it way harder because you're less intimate with the brittle 80%.

Stuck behind Apple's app review process.

> So what?

As mentioned in a comment here:

> Maybe the top 15,000 PyPi packages isn't the best way to measure this? > Apparently new iOS app submissions jumped by 24% last year

Looks like most LLM generated code is used by amateurs/slop coders to generate end-user apps they hope to sell - these user profiles are not the type of people who contribute to the data/code commons. Hence there's no uptick in libs. So basically a measurement issue.

Intel AI denoiser in Blender.

I have a number of small apps and libraries I've prompted into existence and have never considered publishing. They work great for me, but are slop for someone else. All the cases I haven't used them for are likely incomplete or buggy or weird, the code quality is poor, and documentation is poor (worse than not existing in many cases.)

Plus you all have LLMs at home. I have my version that takes care of exactly my needs and you can have yours.

This article is very poorly researched and reasoned, but it's in the "AI hater" category so I guess it's no surprise it's on the front page.

Number of iOS apps has exploded since ChatGPT came out, according to Sensor Tower: https://i.imgur.com/TOlazzk.png

Furthermore, most productivity gains will be in private repos, either in a work setting or individuals' personal projects.

My take is you are missing out on a barrage of "Shadow AI" and bespoke LoB and B2B software (By "Shadow AI" I mean the (unsanctioned) use of GenAI in Shadow IT, traditionally dominated by Excel and VBA).

All of the above are huge software markets outside of the typical Silicon Valley bubble.

I’ll ask another question. Why isn’t software getting better? Seems like software is buggier than ever. Can’t we just have an LLM running in a loop fixing bugs? Apparently not. Is this the future? Just getting drowned in garbage software faster and faster?

I think this is a great question to ask and maybe I need my own blog to post about these things as I might reply with a big comment

Making Unpublished Software for Themselves

One issue is, I think maybe a lot of people are making software for themselves and not publishing it - at least I find myself doing this a lot. So there's still "more software produced than before", but it's unpublished

LOC a Good Measure?

Another question is like Lines of Code, about if we best measure AI productivity by new packages that exist. AI might make certain packages obsolete and there may be higher quality, but less, contributions made to existing packages as a result. So actually less packages might mean more productivity (although, generally we seem to think it's the opposite, conventionally speaking)

Optimizing The Unnoticeable

Another issue that comes up is maybe AI optimizes unnoticeable things: AI may indeed make certain things go 100x faster or better. But say a website goes from loading in 1 second to 1/100th of a second... it's a real 100x gain, but in practice doesn't seem to be experienced as a whole lot bigger of a gain. It doesn't translate in to more tangible goods being produced. People might just load 100 pages in the same amount of time, which eats up the 100x gain anyway (!).

Bottleneck of Imagination

I think also this exposes a bottleneck of imagination: what do we want people to be building with AI? People may not be building things, because we need more creative people to be dreaming up things to build. AI is only fed existing creative solutions and, while it does seem to mix that together to generate new ideas, still the people reading the outputs are only so creative. I've thought standard projects would be 1) creating open source alternatives to existing proprietary software, 2) writing new software for old hardware (like "jailbreaking" but doesn't have to be?) to make it run new software so that it can be used for something other than be e-waste. 3) Reverse engineering a bunch of designs so you can implement some new design on them, where open source code doesn't exist and we don't know how they function (maybe kind of like #1). So like there is maybe a need for a very "low tech" creation of spaces where people are just regularly swapping ideas on building things they can only build themselves so much, to either get the attention of more capable individuals or to build up teams.

Time Lag to Adapt

Also, people may still be getting adjusted to using AI stuff. One other post detailed that the majority of the planet does not use AI, and an even smaller subset pays for subscriptions. So there's still a big lag in society of adoption, and of adopters knowing how to use the tools. So I think people might really experience optimizing something at 100x, but they may not know how to leverage that to publish it to optimize things for everyone else at 100x amount, yet.

Social Media Breakdown?

Another problem is, I have made stuff I'd like to share but... social media is already over-run with over-regulation and bots. So where do I publish new things? Even on HN, there was that post about how negative the posters can be, who have said very critical things about projects that ended up being very successful. So I wonder if this also fuels people just quietly creating more stuff for their own needs.

Has GDP Gone Up or Time Been Saved?

Do other measures of productivity exist? GDP appears to have probably only gone up a bit. But again, could people be having gains that don't translate to GDP gains? People do seem to post about saving time with AI but... the malicious thing about technology is that, when people save 10 hours from one tool, they usually just end up spending that working on something else. So unless we're careful, technology for some people doesn't save them much time at all (in fact, a few people have posted about being addicted to AI and working even more with it than before AI!).

Are There Only So Many "10x Programmers"?

Another issue is, maybe there are only a minority of people who get "10x" gains from AI; at the same time, "lesser" devs (like juniors?) have apparently been displaced by AI with some layoffs and hiring freezes.

Conclusion

I guess we are trying to account for real gains and "100x experiences" people have, with a seeming lack of tangible output. I don't think these things are necessarily at odds with each other for some of the aforementioned reasons written above. I imagine maybe in 5 years we'll see more clearly if there is some noticeable impact or not, and... not to be a doomer / pessimist, but we may have some very negative experience from AI development that seems to negate the gains that we'll have to account for, too.

Among the various ways this analysis is flawed,

two that are drawn from my own experience are:

- meaningful software still takes meaningful time to develop

- not all software is packaged for everyone

I've seen a lot of examples shared of software becoming narrow-cast, and/or ephemeral.

That that doesn't show up in library production or even app store submissions is not interesting.

I'm working on a large project that I could never have undertaken prior to contemporary assistance. I anticipate it will be months before I have something "shippable." But that's because it's a large project, not a one shot.

I was musing that this weekend: when do we see the first crop of serious and novel projects shipping, which could not have been done before (at least, by individual devs)... but which still took serious time.

Could be a while yet.