JoseOSAF

6 ms·

1.
by JoseOSAF 7mo ago
That's... exactly the insight? The speed of disappearance is what most builders underestimate. The interesting part is in sections 4-6: what the survivors did differently. Happy to hear what would make it more useful to you.
2.
by JoseOSAF 7mo ago
Yeah the headline oversells it a bit. The part I actually found interesting was that 500+ point posts die just as fast as 50 point posts. HN's algorithm doesn't care how popular you are. Sections 4-6 have the more useful stuff if
3.
by JoseOSAF 7mo ago
interesting, that actually explains a lot. If HN rewrites the timestamp on resubmission/boost, that's exactly why powera saw "14 days ago" for a post our scraper first picked up Dec 8. We were just grabbing whatever hit
4.
by JoseOSAF 7mo ago
I don't use gpt.
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by JoseOSAF 7mo ago
Fair point — and you're partially right. The "44 days" outlier (Grov) appeared in our snapshots on 12 unique dates spread across 47 calendar days, not continuously. Our methodology measured time between first and last appeara
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Show HN: LocalCoder – Tell it your hardware, get the exact local AI model to run(localcoder.xyz)
1 points by JoseOSAF 7mo ago|0 comments
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We tracked 605 Show HN posts for 63 days(asof.app)
18 points by JoseOSAF 7mo ago|15 comments
8.
by JoseOSAF 8mo ago
Fair point, so you think it would be more useful to keep it developer centric? I do like the idea and actually might shift it in that direction. Thank you for the input.
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Show HN: 8of8 – A trend radar for developers (17 sources, scored 0-100)(8of8.xyz)
2 points by JoseOSAF 8mo ago|2 comments
10.
by JoseOSAF 8mo ago
My projects: https://asof.app - AI-powered intelligence platform for market analysis and content generation Happy to get feedback from the HN community.
11.
by JoseOSAF 8mo ago
Yeah fair point on the medical MLLM stuff. FDA and modular approaches have never been best friends. That's actually why I'm most curious to see how it plays out - the ArXiv activity around safety grafting has been picking up but w
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Show HN: I made 25 tech predictions and mass-published them
2 points by JoseOSAF 8mo ago|3 comments
13.
by JoseOSAF 8mo ago
Interesting, would love to see the results. I'll be checking back here if you care to share them.
14.
by JoseOSAF 8mo ago
Lol fair. I chickened out on the rage-bait title because it felt too meta. If this dies in /new, at least I proved my own point.
15.
by JoseOSAF 8mo ago
You're right that most voting is headline-driven - that's definitely a limitation worth calling out. I went with full article text because I wanted to capture what the content actually delivers, not just what the headline promises
16.
by JoseOSAF 8mo ago
Here's the raw dataset: https://asof.app/static/hn_viral_dataset.json 159 stories that hit score 100 in my tracking, with HN points, comments, and first-seen timestamp. Methodology: - Snapshots every 30 minutes (1
17.
I analyzed 159 viral HN posts – negative sentiment outperforms positive 2:1
1 points by JoseOSAF 8mo ago|11 comments