My experience is the same. There are modest gains compensating for lack of good documentation and the like, but the human bottlenecks in the process aren't useless bureaucracy. Whether or not a feature or a particular UX implementation of it makes sense, these things can't be skipped, sped up or handed off to any AI.
If you don't want to or can't install a Sustainiac pickup, you can get a much cheaper handheld one-string "E-Bow" that does the same thing. It's not as easy to use as a Sustainiac and you can't also be playing with the whammy bar unlike with a Sustainiac, but you can get it to do tricks a Sustainiac can't do: see the "spiccato" section in https://www.youtube.com/watch?v=b0V3pzxma-8
I've also managed to make an E-Bow work with a steel-string acoustic guitar (but only on one string IIRC).
Happy for you, but GitHub has plenty of webcam feed URLs, webcam viewers, Roku code etc. You "built" it for some value of 'building' but it certainly doesn't seem the same kind of 'building' as described in the first three sentences of your post.
It's nice you got something out of it in just two hours. If the LLM companies are doing their caching right, the next person to ask for this set of apps with prompts close enough to yours can get it in five minutes.
The inching-towards-acceptance of crappy processes is quite influencer-driven as well, with said influencers if not directly incentivised by LLM providers, then at least indirectly incentivised by the popularity of outrageous exhortations.
There's definitely a chunk of the developer population that's not going to trade the high-craft aspects of the process for output-goes-brrr. A Faustian bargain if ever I saw one. If some are satisfied by what comes down to vibe-testing and vibe-testing, I guess we wish them well from afar.
> I was careful to say "Good code still has a cost" ...
Misleading headline, with the qualifier buried six paragraphs deep. You have a wide enough readership (and well deserved too). Clickbait tactics feel a little out of place on your blog.
This is the chapter title for a sort-of book I'm working on, and it's the central philosophy I'm building the book around.
I'm not going to change a good chapter title (and I do think it's a good chapter title) just because people on Hacker News won't read a few paragraphs of content.
A dishonest title would be "Code is cheap now" or "Programming is cheap
now". I picked "Writing code is cheap now" to capture that specifically the bit where you type code into a computer is the thing that's cheap.
Fairly esoteric and self-serving definition of "writing code" if it represents just the typing part. I wouldn't call it a dishonest title, but perhaps not a fully honest one either.
This is related to why current Babelfish-like devices make me uneasy: they propagate bad and sometimes dangerous translations along the lines of "Traduttore, traditore" ('Translator, traitor'). The most obvious example in the context of Persian is of "marg bar Aamrikaa". If you ask the default/free model on ChatGPT to translate, it will simply tell you it means 'Death to America'. It won't tell you "marg bar ..." is a poetic way of saying 'down with ...'. [1]
It's even a bit more than that: translation technology promotes the notion that translation is a perfectly adequate substitute for actually knowing the source language (from which you'd like to translate something to the 'target' language). Maybe it is if you're a tourist and want to buy a sandwich in another country. But if you're trying to read something more substantial than a deli menu, you should be aware that you'll only kind of, sort of understand the text via your default here's-what-it-means AI software. Words and phrases in one language rarely have exact equivalents in another language; they have webs of connotation in each that only partially overlap. The existence of quick [2] AI translation hides this from you. The more we normalise the use of such tech as a society, the more we'll forget what we once knew we didn't know.
[2] I'm using the qualifier 'quick' because AI can of course present us with the larger context of all the connotations of a foreign word, but that's an unlikely UI option in a real-time mass-consumer device.
> in the context of Persian … "marg bar Aamrikaa". If you ask the default/free model on ChatGPT to translate, it will simply tell you it means 'Death to America'. It won't tell you "marg bar ..." is a poetic way of saying 'down with ...'.
All this time the Persian chants only signified polite policy disagreement? Hmmm, something fishy about this….
Edit: isn’t the alleged double-meaning exactly how radicalized factions drag a majority to a conclusion they actively disagree with? Some in the crowd literally mean what they say, many others are being poetic and only for that reason join in. But when it reaches American ears, it’s literally a death wish (not the majority intent) and thus the extremists seal a cycle of violence.
> isn’t the alleged double-meaning exactly how radicalized factions drag a majority to a conclusion they actively disagree with? Some in the crowd literally mean what they say, many others are being poetic and only for that reason join in. But when it reaches American ears, it’s literally a death wish (not the majority intent) and thus the extremists seal a cycle of violence.
This is plausible, and again a case for more comprehensive translation.
In Hindi and Urdu (in India and Pakistan) we have a variant of this retained from Classical Persian (one of our historical languages): "[x] murdaabaad" ('may X be a corpse'). But it's never interpreted as a literal death-wish. Since there's no translation barrier, everyone knows it just means 'boo X'.
> معلوم هم هست که مراد از «مرگ بر آمریکا»، مرگ بر ملّت آمریکا نیست، ملّت آمریکا هم مثل بقیّهٔ ملّتها [هستند]، یعنی مرگ بر سیاستهای آمریکا، مرگ بر استکبار؛ معنایش این است.
"It is also clear that 'Death to America' does not mean death to the American people; the American people are like other nations, meaning death to American policies, death to arrogance; this is what it means.
Translation by Claude; my Persian is only basic-to-intermediate but this seems correct to me.
Don't think that is a fair point, the manipulation was done on a topic of which there are hardly any other sources (hot dog eating competition winner). If you want to manipulate what an AI tells you is the F-150 street price, you will complete with hundreds of sources. The AI will unlikely pick yours.
The marketing game is already moving to game LLMs. Somehow you have to get what you want to have into the training data or the context window.
Currently it is probably just mostly quantity that does the trick w.r.t. training data. So e.g. spam the Internet with "product comparisons" featuring your product as the winner.
Shifting the balance on training data seems like the wrong approach vs focusing on showing up in agent search tool results and swaying them there.
It’s been a long time since agents couldn’t even conduct web search and could only riff off their model. But the examples in this thread are things an agent would search for immediately, and agents are leaning harder on tool calls and external info over time, not less.
r/macapps is also putting new requirements in place [1], requiring among other things a statement of what your app solves, how it's better than existing solutions and even a changelog/roadmap.
I would bet just the first two text fields would be enough to catch out vibecoders.
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