Comment by rdslw
14 days ago
Congrats on the app.
I'm seeing that "great-ai-unlock" is happening. I see in last month a lot of new software being codeveloped with claude/codex/gemini/you-name it.
Before, it was too costly to do sth like the Posture app: here, you would have to know Swift and apple apis to write such tool. Would you be C# (very good) programmer with free weekend, and an idea: no cookie for ya.
These days, due to "great-ai-unlock" your skills can be easily transferred and used to cross platforms boundary and code such useful app in a weekend or so.
Jevons paradox is indeed working (https://en.wikipedia.org/wiki/Jevons_paradox).
Maybe this is a naive take, but I don't really think LLMs have done that much to change the actual situation around ability/outcomes. If you are actually a very good C# programmer, knowing Swift and searching some Apple documentation seems very reasonable.
It might help "unstick" you if you aren't super confident, but it doesn't seem to me like it's actually leveling up mediocre programmers to "very good" ones, in familiar or unfamiliar domains.
> I don't really think LLMs have done that much to change the actual situation around ability/outcomes
from my own experiences and many others I have seen on this site and elsewhere, I'm not sure how anyone could conclude this.
> it doesn't seem to me like it's actually leveling up mediocre programmers to "very good" ones
Oh well then if this is your metric then maybe your take is correct, but not relevant? From the top level comment I thought we were talking about the bar being lowered for building something thanks to AI and you don't need to become any better at being a programmer to do so.
I don't care how good of a programmer you are, if you don't know Apple stuff (Swift, Xcode, all the random iOS/Mac app BS) you aren't making an Apple app in a weekend. Learning things is easy but still takes time, and proficiency is only earned by trying and failing a number of times — unless you're an LLM, in which case you're already proficient in everything.
No I can confirm this. I am at least an average C# dev, with 16 years of experience.
I have built a very nicely responsive real-time syncing iOS app in what amounts to a weekend of time. (I only have an hour here and there, young kids) I had zero iOS/Swift development experience prior to it.
I can also confirm that this wouldn't have been built if it weren't for Claude Code. It's "just" an improved groceries app, that works especially well for my wife and me.
Without LLM's, and with just an hour here and there, I wouldn't have done the work to learn the intricacies of iOS and Swift dev, set up the app, and actually tweak and polish it so it works well -- just to scratch the itch of a bit better groceries handling.
Thanks rdslw. I mentioned something similar on my blog post about this app here: https://tomjohnell.com/posturr-a-macos-app-that-blurs-your-s...
I love coming up with fun ideas and only having to worry about the fun part - not the toil. I would never have made this app without llm support.
Neat app. Any tips on how you used Claude Code to develop this?
My first prompt was:
"Help me develop a MacOS app that blurs my screen the closer my mouse is to the top of the monitor"
That was my PoC to see if there's APIs Claude could find that would make this easy to do. Once I proved that worked, I asked it to instead help me devise a way to adjust that blur based on my posture. It suggested the vision framework and measuring head height.
Just kept iterating, one step at a time. Any toil I experienced, I asked it to remove or automate.
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I don't see how the Jevons paradox would apply here. Code being cheaper and faster to produce obviously causes the demand for apps such as this one to grow. That's just supply and demand.
An example of where I think the paradox would apply might be one where LLMs made software engineers more efficient yet the demand for SWEs would grow.
What a stupid thing to call a paradox. When infrastructure is better, you'd expect it to be used more.
It's because they're misusing the term. Jevons' paradox doesn't apply to the simple idea that "cheaper code leads to more demand for code", that's just the concept of price curves.
Instead, Jevons' paradox refers to a counterintuitive rebound effect: AI tools make engineers more productive, which you'd expect to reduce the marginal demand for additional engineers (since the same output requires fewer people). In reality, this efficiency lowers the effective cost of software development, sparking even greater overall demand for new features and projects, which ultimately increases total spending on engineering talent.
Jevons paradox is a failure mode, not something that "works".