There's no point at which turning your brain off will work
In early 2025, I started seeing people turn off their brain as they use LLMs1. They would have an LLM take an action (summarize text, write some code, etc.), and just assume that it worked2. This generally didn't work in early 2025 and the result was often quite silly.
- ▪In early 2025, I started seeing people turn off their brain as they use LLMs1.
- ▪They would have an LLM take an action (summarize text, write some code, etc.), and just assume that it worked2.
- ▪This generally didn't work in early 2025 and the result was often quite silly.
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Record
| Original publisher | Danluu |
| Canonical URL | https://danluu.com/brain-off/ |
| Publication time | Fri, 18 Sep 2026 17:02:52 +0000 |
| Retrieval time | 2026-09-18T17:13:48.419Z |
| Last seen | 2026-09-18T17:13:48.419Z |
| 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 | --UXtFijNZw7 · 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)
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| 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
In early 2025, I started seeing people turn off their brain as they use LLMs1. They would have an LLM take an action (summarize text, write some code, etc.), and just assume that it worked2. This generally didn't work in early 2025 and the result was often quite silly. As LLMs have gotten better, I've seen more of this. Sometimes, people will try to get the LLM to write some code for them and basically just assume that it works3. Sometimes there's a human in the loop and, if the thing doesn't work, they'll ask the LLM to figure out the problem and solve it. Niklas Gruhn calls some variants of doing this being a meat proxy.4 Being a for loop meat proxy works better than it did in early 2025 and the software I've tried that's developed like this sometimes actually sort of works.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Danluu.
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