Ask HN: What will happen if AI is mature and people have little work to do?
The author argues that large language models have become valuable intelligence resources, making it difficult to deny their impact despite the lack of AGI. While fields like mathematics and art may remain human-centric, practical disciplines such as engineering face significant disruption as AI offers faster and cheaper solutions. This shift could reduce the intrinsic enjoyment of work, potentially relegating professional tasks to the status of hobbies or specialized crafts.
- ▪Recent open-source LLMs are considered valuable intelligence resources even by AI skeptics.
- ▪Fields where the output is the human expression, such as math and art, are considered less vulnerable to AI replacement.
- ▪Engineering and other practical fields are at risk of being automated, which may strip away the fun from the profession.
- ▪The author suggests that professional work might degrade into activities similar to sports or handcrafts as AI takes over functional tasks.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Hacker News (AI / LLM) |
| Canonical URL | https://news.ycombinator.com/item?id=49659652 |
| Publication time | Fri, 11 Sep 2026 15:01:33 +0000 |
| Retrieval time | 2026-09-11T15:02:50.591Z |
| Last seen | 2026-09-11T15:02:50.591Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | rsw-fzXTy_p- · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Three years ago I asked the same question (https://news.ycombinator.com/item?id=35327092), and the landscape has changed since then. Just say that even the most AI skepticism people will have to admit that with recent models, even open source ones, LLM is already a valuable intelligence resource, at least in the right hands. Of course we are nowhere near AGI yet, but no theorem can assert that AI will not be at least as good as human; neuro-networks can fit arbitrarily complex function. If human thought, based on the physical structure of brain, is computable, then some computer program can certainly take advantage of that.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Hacker News (AI / LLM).
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