seinvak

> https://nokku.localhost/interview-prep/dsa/graphs

Works on your machine, doesn't work on mine :(

> We find that post-graduation employment, earnings, and job switching patterns among the most AI-exposed college majors began to diverge immediately following the introduction of ChatGPT in late 2022

If ChatGPT in 2022 caused a large recession, what's the impact now? Graduating like if in the Great Depression?

Well oil is definitely the reason countries like Iraq or Venezuela have been held hostage by America.

Education doesn't imply intelligence. 90% of humanity that has ever lived has probably never read a word.

Past threads :

2012 : https://news.ycombinator.com/item?id=3987566

2014 : https://news.ycombinator.com/item?id=7367258

2021 : https://news.ycombinator.com/item?id=26837152

> mastering the agentic process

It would have been worth it if the frontier models were open weight. Right now, if you invest time in mastering tools like Claude Code or Google’s Antigravity, there is no guarantee that you won’t be removed from their ecosystems for any reason, which would make your efforts and skills useless.

It was an easy project, but managed to hit frontpage here :

https://news.ycombinator.com/item?id=46345897

Who said employees in India are unaffected by these layoffs?

AI is definitely a solid reason. Even a 10% increase in developer efficiency translates to roughly 9% fewer workers needed to do the same job. For AI to be cost effective, it must reduce headcount.

Probably the same happening for websites being built or apps being published.

By searching in all categories, I can see it's mentioned once : https://news.ycombinator.com/item?id=42659243#42662874

For a cult, this is some remarkably low-effort proselytizing though :/

> I expect two of the listed to have very positive sentiment, and one generally negative in 2025.

You are quite correct! Crafting Interpreters actually has the highest average sentiment score across all books with more than 10 comments. This is the average sentiment score of all three( range being -10 to 10) :

Crafting Interpreters(7.8) > SICP(4.3) > Clean Code(-3.2)

Just missed by a day I guess. Cutoff is 15th December.

Thanks for the love.No need to scrape, just use this json containing all the data used in making the site :

https://storage.googleapis.com/globalhnbucket/normalized_boo...

> Would love to learn more about how this is built. I remember a similar project from 4 years ago[0] that used a classic BERT model for NER on HN comments

Yes, I saw that project pretty impressive! Hand-labeling 4000 books is definitely not an easy task, mad-respect to tracyhenry for the passion and hardwork that was required back then.

For my project, I just used the Gemini 2.5 Flash API (since I had free credits) with the following prompt:

"""You are an expert literary assistant parsing Hacker News comments. Rules: 1. Only extract CLEARLY identifiable books. 2. Ignore generic mentions. 3. Return JSON ARRAY only. 4. If no books found, return []. 5. A score from -10 to 10 where 10 is highly recommended, -10 is very poorly recommended and 0 is neutral. 6. If the author's name is in the comment, include it; otherwise, omit the key. JSON format: [ {{ "title": "book title", "sentiment": "score", "author" : "Name of author if mentioned" }} ] Text: {text}"""

It did the job quite well. It really shows how far AI has come in just 4 years.

Thanks! I used OpenLibrary's API to get the book IDs, and then Gemini 3 to generate the Amazon links.

Specialist doctors are one of the highest paid professions in almost all countries. There are hardly any jobs more important than those of say a heart surgeon or a neurosurgeon.

Quite possible regular flossing causes microplastic contamination in the gums which quite readily then enters the bloodstream.