massagedpelican

Over half, apparently. https://www.salahadawi.com/hacker-news-ai-detector/49947472

Out of curiosity, I ran the PDF through pangram and it seemed to flag nearly the entire thing as AI. I recognize these aren't perfect detectors, but they can give signals if nothing else. Perhaps it needs more soul injected!

https://www.pangram.com/history/93f9ec71-f7b3-4680-86b1-ff12...

20% more expensive than stripe, no?

the main purpose of that data is for fraud detection, anything downstream (i.e. selling it to advertisers) is just the cherry on top. Merchants are always financially incentivized both implicitly and explicitly to do anything that would reduce fraud and increase the rate of successful authorizations.

I think "the engineer themselves" is much closer to the abstraction layer I'm referring to.

Imagine for a moment that, rather than using a compiler to translate c++ into assembly, that it instead has to be done by a person on the team. If that were the case, the resulting assembly code would certainly have to be reviewed and assessed before it was accepted.

Why?

Because people can also be leaky, non-deterministic abstraction layers. The only reason that the output of a compiler isn't regularly reviewed (in 99% of cases) is because it's extraordinarily reliable and consistently correct, or correct enough for most cases.

It's not terribly dissimilar from delegating engineering tasks to other engineers. When I ask someone else to develop one component of a larger application, I'm not telling them exactly what lines to write, I'm giving them some kind of structure and they're filling in the rest. The communication to them is above the implementation layer.

Agents are increasingly letting us work at that same boundary. Just because the current state of LLMs requires engineering knowledge to review the result doesn't mean an abstraction hasn't occurred. It speaks more to the current quality of that abstraction than the absence of one.

I think that if LLMs were able to achieve the same consistency as a compiler, most people wouldn't ever bother to check the underlying code it produced. I also think it would be difficult to not acknowledge that LLMs have gotten better at converting natural language into functioning software. The abstraction is certainly not perfect, but it is clearly improving.

I think this expresses what I've been trying to form in my mind.

I've been trying to map the LLM advancements and the current state of software development onto prior technological improvements. History is littered with similar cases where the abstraction layer ends up getting lifted, and people struggle with getting accustomed to working at that higher abstraction level.

For the people that fall in love with a single abstraction layer or don't have an interest in learning new paradigms, when their known pattern is abstracted away, they're condemned to being left behind, either unwilling or unable to adapt.

I don't think any industry is free from this, any person in any industry/profession over a period of 20 years or more has likely had to undergo massive adjustments as technology changed their field.

We're not unique, but that doesn't stop it from feeling so jarring when it happens to us

How would one go about determining what effect to add for each cassette type? I don't know much about cassettes, I'm curious if this was something that could be done by ear or if these are commonly held opinions about the sound of each tape.

Again knowing nothing about tape, if I were tasked with this I would probably try to record the same audio to each of the tapes and then compare it with the original.

I truly hate to suggest this, but the meta vanguard nails this to a tee.

https://www.dcrainmaker.com/2025/10/oakley-meta-vanguard-rev...

I've been chewing on this for a while, but I don't think the thought is fully formed. I'll rough it out here anyways, it certainly isn't a novel or unique one.

I think my main issue with vibe coded apps is that the signal to noise ratio got flipped upside down.

Things that may have been positive signals in the past aren't really great indicators anymore. Maybe they shouldn't have been positive in the past, but they certainly aren't now. Broadly, things like polished website design, punchy language, clean branding, slick landing page, etc were all indicators. At a minimum, they at least meant that time and effort was put into it. It didn't really mean anything about the product, but it would display at least some level of time and effort.

Now, the outward appearance of a project no longer conveys anything about effort or durability, I can easily spin up a home page that would have taken me weeks pre-AI, then never touch it again.

The site states that it took roughly a hundred hours to develop. I have no real way of verifying that and I don't even think that it matters. The most evident signal that I feel I can still get a pulse on is when something is clearly, heavily AI written. All other signals that would supersede it require additional time to evaluate. Things like reading the docs, skimming the codebase, testing the product etc.

With a project like this, the ask made to the end user is to spend the time to, at a minimum, read the docs to see if it's a good fit. If they think it's a good fit, the next ask is to spend the time to integrate it with their current inventory. Then learn the workflow. Then learn the idiosyncrasies. All of these things involve, real human, time.

When an end user is asked to invest this time, there are only so many signals available to them to help decide if it's a good use of their time, energy and resources. For better or for worse, it seems like that list of signals is shrinking and right now, something that appears vibecoded is still one of the clearest visible signals.

I think it's hard to say one way or another. My guess is the latter, or perhaps the audience isn't even aware it's vibe coded.

I (like many other software folks) are aware of AI-isms in writing, so when I see something that it so obviously AI generated in a project, it's equivalent to a giant red waving flag.

For someone who doesn't interact with LLMs regularly? I have no idea, maybe it sounds great to them. Most non-tech folks I interact with to don't seem to have as well-tuned AI sense, whether it be image, video or text

Effective altruism. A lot of the folks working on AI at large tech companies are disproportionately represented in the movement. There's a lot of overlap between EA and the rationalist community as well. The wikipedia page is a good place to start https://en.wikipedia.org/wiki/Effective_altruism

On a recent trip to Japan, my partner and I visited the Kyoto Railway Museum (https://www.kyotorailwaymuseum.jp/en/ ), which features many of the trains and predecessors listed in the OP.

Seeing it at the end of the trip after riding so many different trains made it especially impactful. Two highlights were the massive 100ft-wide railway diorama and the working vintage steam trains, which they drive (run?) out onto a turntable before rotating and returning to their stalls.

Well worth a visit if you’re ever in Kyoto.