SEO is changing, some notes on it which i found from internet:
Find a frontier concept:
LLMs favor the first or clearest explanation of a concept. If you’re early, your version may become the default. If not, aim to be the most definitive.
Identify low-competition, high-opportunity topics where you can become the source.
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Monitor Twitter/X, Reddit, GitHub, Discord, and forums for emerging questions
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Find gaps where competitors are shallow or absent
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Find topics that match your company or product strengths
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Share original data, benchmarks, customer stories, or insights that are hard to copy
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Start with what your users are already asking for
Publish the definitive, evidence-based source:
Once you’ve found your angle, go deep. Generic summaries are often skipped. LLMs prefer substance and infer authority from depth. Include original data, code, expert quotes, or stories that others can’t easily copy.
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Go beyond surface-level coverage
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Include metrics, code blocks, tables, lists, quotes, and diagrams
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Use precise, consistent terminology. Fuzzy synonyms weaken embeddings
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Write for extraction. Short, self-contained insights are more likely to be cited
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Aim to be the canonical source in your niche
The litmus test: Ask yourself, “Could a competitor easily replicate this tomorrow?” If the answer is yes, dig deeper.
Structure for machines:
Structure helps models understand what your content is and when to surface it. Even if indexed, a page may be skipped if meaning isn’t clear or layout is hard to parse.
Make intent obvious in both markup and layout:
- Use consistent terminology and clean heading hierarchies (H1 → H2 → H3)
- Add Schema.org or JSON-LD markup to reinforce meaning
- Use semantic elements where possible. Callouts, glossary terms, nav sections with clear class names or ARIA labels
- Use semantic HTML like definition lists and tables for structure
- Confirm indexability in Bing and Google
- Most AI crawlers fetch but do not execute JavaScript. Use Server-Side Rendering (SSR), Static Site Generation (SSG), or Incremental Static Regeneration (ISR) to expose static HTML
- With Next.js and Vercel, serve pages on demand without full rebuilds to keep content fresh and accessible
The goal isn’t to trick the system. It’s to make your intent as clear to machines as it is to humans.
Seed authentic citations
LLMs learn from the web. Guide the conversation. For training influence, community mentions matter. They help models associate your brand with a concept. If people cite you, models often follow. For retrieval, backlinks and indexability still remain critical.
- Share in threads, AMAs, changelogs, and product demos
- Create open-source resources or real examples others can reference
- Build topic clusters with interlinked articles to reinforce relationships
- Focus on high-signal, indexable channels: Reddit, GitHub, Hacker News, Twitter/X, LinkedIn, Stack Overflow
- Avoid paid links. Organic citations carry more weight in training data
Set a refresh cadence:
Models re-crawl the web regularly. Over time, stale content becomes less useful. To both people and AI systems. Even if a page is indexed, it may stop being retrieved or referenced if it’s no longer accurate or relevant.
In retrieval-based systems, newer, higher-ranking content is more likely to be included. Keeping content fresh improves your chances of being surfaced and cited.
Regular maintenance matters:
- Fix 404s, update
lastmod, and keep your sitemap clean - Review content at 30, 90, and 180 days
- Refresh what’s stale, expand what’s working
- Archive outdated pages (with redirects)
- Close gaps as competitors catch up
Consistent upkeep keeps content relevant and signals to both users and models that your information can be trusted.