I ran 20 prompts through the Perplexity API and manually cross-checked 60 answers against the cited pages. Here's what I found
AI Release 💡 I ran 20 prompts through the Perplexity API and manually cross-checked 60 answers against the cited pages. Here's what I found: the model doesn't read the source in full — it picks out individual chunks of text. And often it's not the first paragraph or the most obvious spot — the algorithm assembles the answer like a mosaic from different fragments. To get featured, you need to structure the page so that the key idea is a self-contained block. That way Perplexity can extract it without losing meaning. But if the text is spread across paragraphs, the model will simply rewrite someone else's conclusion. Essentially, this is a new kind of SEO: not optimized for queries, but for quote extraction. 🔗 Read on habr.com #PerplexityAI #AI #SEO #ИИ #нейросети 24 views 22:21
🤖 AI summary
- Date: 2026-09-19
- Source: t.me
- Key facts:
- AI Release 💡 I ran 20 prompts through the Perplexity API and manually cross-checked 60 answers against the cited pages.
- Here's what I found: the model doesn't read the source in full — it picks out individual chunks of text.
- And often it's not the first paragraph or the most obvious spot — the algorithm assembles the answer like a mosaic from different fragments.
- To get featured, you need to structure the page so that the key idea is a self-contained block.
- That way Perplexity can extract it without losing meaning.
- But if the text is spread across paragraphs, the model will simply rewrite someone else's conclusion.
- Essentially, this is a new kind of SEO: not optimized for queries, but for quote extraction.
- 🔗 Read on habr.com PerplexityAI AI SEO ИИ нейросети 24 views 22:21
Source: t.me · post in Telegram