How we made claude.ai 3x faster in two weeks
SCALING HORIZONTALLY Once the loop worked on one thread, running it on more was just a matter of opening them. Instead of closing a thread once its original request had been fulfilled, Claude would keep going. An individual thread would put up fifty, sometimes a hundred, optimization PRs.
- ▪SCALING HORIZONTALLY Once the loop worked on one thread, running it on more was just a matter of opening them.
- ▪Instead of closing a thread once its original request had been fulfilled, Claude would keep going.
- ▪An individual thread would put up fifty, sometimes a hundred, optimization PRs.
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Record
| Original publisher | Hacker News (AI / LLM) |
| Canonical URL | https://claude.dev/blog/how-we-made-claude-ai-faster/ |
| Publication time | Wed, 23 Sep 2026 19:23:40 +0000 |
| Retrieval time | 2026-09-23T19:39:30.832Z |
| Last seen | 2026-09-23T19:39:30.832Z |
| 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 | JMfbcoDgmBwb · 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
SCALING HORIZONTALLY Once the loop worked on one thread, running it on more was just a matter of opening them. Instead of closing a thread once its original request had been fulfilled, Claude would keep going. An individual thread would put up fifty, sometimes a hundred, optimization PRs. Increasingly, it was Claude, not one of us, opening new threads to chase opportunities it had found on its own, as part of a separate investigation or nightly job. Shelley, one of the engineers in the channel, observed, “[This model] is a numbers demon.” Every measurement found something to improve. Claude ran a React hook census and found 6,900 hooks and 900 store subscriptions in the composer’s typing path, re-rendering on every keystroke.
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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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