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.

Jevon's Paradox will show up too though. When employees get more efficient companies just demand more of them.

You really have to be in "the room where it happens" to know the motivations behind any one layoff.

I have noticed this while working in a startup, how efficiency gains impacted work in the last 3 months with better coding models coming in. If you have someone senior that is effective at using these tools and can own the outputs and be capable of correcting things that are sloppy, you are immensely more valuable than 2-3 more developers in the same area of work. It's actually faster to empower fewer people than try to have 3 fast guys where there would be coordination overhead, which would become a bottleneck and bring down a lot of the efficiency gains. A good full stack engineer who can work with these tools at speed with caution is more valuable similarly as it requires less coordination. 3 junior devs shipping 90% good code and 10% slop would make the senior who is reviewing everything the bottleneck.

To help us use your anecdote, could you tell us what product area is your startup is working in?

Amazon is mostly laying off managers, however, not developers.

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

Thanks for the heads up. Corrected it.

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 :/

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

I think we take for granted having dang as a member and it makes us apathetic.

> 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.