From Search Engines to Answer Engines: SEO in the LLM Era

Introduction: The SEO Paradox

Search engine optimisation (SEO) never stops evolving—but in 2025, it feels more like a revolution than an evolution.

With the rapid rise of large language models (LLMs) like ChatGPT, Claude, and Gemini, and the emergence of AI-powered search interfaces such as Google Overviews and Google’s upcoming AI Search Mode (already available in the US), marketers are asking the big question:

Is my SEO strategy about to change completely?

The answer? Everything has changed. Nothing has changed. While AI-driven search is revolutionising how users find and consume information, the main SEO principles remain the same:

Content, Authority, and Technical SEO.

These pillars still form the foundation of successful optimisation — but how we approach them must evolve to thrive in this new landscape. In this post, we’ll unpack that paradox and explore how to adapt—without abandoning the core principles that have always worked.

Part 1: Everything Has Changed

1. The Search Landscape Is Evolving

For the past 25 years, the web operated under a simple agreement:
You create content, search engines send you traffic, and users visit your site.
But  Google AI Mode and other LLM-driven platforms aim to solve the query directly—without necessarily sending the user to a publisher’s page.

That shift poses an existential threat to traditional organic traffic models. But it also presents a major opportunity:

To become the trusted source that AI systems cite, quote, and surface.

The brands that win in this new landscape will be the ones that embrace content quality at the paragraph level, multimodal delivery, and deep intent alignment—not just keyword targeting.

You can access Google AI Overview using this link: google.com/aimode in your web browser (with a US VPN).

 

2. Search Engines Are Morphing

Search isn’t just about keywords anymore. LLMs analyse meaning, intent, and context.

AI-powered search blends classic algorithms with generative summaries. If your content isn’t semantically rich, it might get left behind.

This transformation is also powered by query fan-out, where LLMs  break down a single user query into multiple related sub-queries.

For example, a search for “sensitive skin cream” might trigger related searches for pricing, specific product attributes such as gentle, fragrance-free, or hypoallergenic options, reviews, brand comparison...

If your content doesn’t align with this expanded intent landscape, you won’t be included in the answer set—even if you rank for the original keyword.

 

Part 2: Nothing Has Changed

Despite the AI-powered shifts, the fundamentals of good SEO remain as important as ever—arguably more so.

1. Good Content Still Wins

Creating helpful, original, and insightful content still sits at the heart of successful SEO.

If you’ve always focused on genuinely helping users, you’re already ahead.

If you’re an e-commerce brand, talk about the fields you're an expert in—so your products and product categories gain topical authority.

LLMs thrive on content that is:

• Well-structured
• Easy to interpret
• Deeply informative
• Answering real questions and anticipating follow-ups

Well-Structured Content Means:

• Clear, descriptive headings (H1–H3 hierarchy)
• Bullet points and short paragraphs
• Logical flow
• Rich context without unnecessary fluff

Content Refresh Is Essential

Updating existing content regularly is crucial. Refresh your pages to:

• Keep facts, stats, and references current
• Add new insights or developments
• Remove outdated or irrelevant information
• Improve clarity, structure, or user experience

Best Practices:

• Use references and citations to credible sources
• Provide up-to-date, verifiable facts
• Avoid speculation; back up points with data
• Conduct and share original research or findings
• Present insights in a quotable, summarised format for AI systems

2. User Intent Still Rules

Whether typed into a search bar or asked aloud to a chatbot, the why behind a query is what matters.

SEO has always been about understanding that intent and meeting it head-on. That principle hasn’t changed.

 

3. Technical SEO Still Matters

The foundation still holds—and it’s more important than ever now that AI is part of the equation.

Crawlability & Indexability

Search engines and AI models need to access your content. A well-structured sitemap, clean URL structure, and proper use of canonical tags ensure your site is discoverable.

JavaScript: A Known Limitation

Although Google has improved its rendering capabilities, most LLMs still struggle to parse JavaScript-heavy websites.

Recommendation: Avoid building important content and navigation exclusively in JavaScript. Use server-side rendering (SSR) or static HTML when possible.

Part 3: Authority, Relevance & LLM Optimisation

Authority Still Drives Visibility

Trust and credibility remain central to visibility in both traditional SEO and AI-generated responses.

Link Earning Still Matters

• High-quality backlinks remain a top authority signal
• Domains with strong link equity are more likely to be summarised or cited by LLMs
• Traditional PR and media mentions still carry weight

Brand Mentions Matter (Even Without Links)

• Citations in forums, podcasts, and communities like Reddit, Wikipedia, and Quora contribute to LLM awareness
• These unlinked mentions act as soft trust signals

Branded Search Reflects Trust

If people are searching for your brand by name ("Your Brand", "Your Brand reviews"), it signals authority and user trust.

According to a study from Ahrefs, brand mentions and branded search volume show the strongest correlation with inclusion in AI Overviews.

Topical Authority & Semantic Similarity

Building topical authority is no longer optional.

LLMs assess semantic proximity between your content and user prompts—not just keyword usage.

• To build true authority:
• Focus on depth, not just breadth
• Cover subtopics thoroughly
• Interlink meaningfully
• Use semantic markup and reinforcing headings
• Low-relevance content confuses LLMs and dilutes your topical strength.

Part 4: How LLMs Retrieve and Rank Content

Modern language models, including those powering AI Overviews or chat-based search, rank and prioritise information based on relevance and quality.

Without ranking, you'd get the same chaotic mess we saw in the early days of search.

How It Works Today

Traditional search engines like Google rank content based on:

• Relevance
• Authority
• User behaviour
• Context

LLMs still use these principles—but in new ways:

• Embeddings capture meaning beyond keywords
• Passage-level retrieval finds relevant paragraphs, not pages
• Multi-turn conversations shape topic coherence

The Rise of Query Fan-Out

When a user submits a prompt, the system breaks it into multiple sub-queries targeting different facets of intent:

• Definitions, comparisons, summaries
• Specific examples or statistics
• Counterpoints or FAQs

So your content must be:

• Semantically rich
• Covering multiple angles
• Structured for retrieval

Paragraph-Level Optimisation

Every paragraph must:

• Stand alone as a complete, clear answer
• Be easily cited in isolation
• Offer distinct value

Comprehensive but rambling content won’t perform. Clean structure and clarity win.

How 30acres Can Help You

Navigating the evolving SEO landscape can be challenging—but you don’t have to do it alone. At 30acres, we combine deep expertise in traditional SEO with cutting-edge knowledge of AI-driven search to help your brand thrive in 2025 and beyond.

We offer:

• Comprehensive SEO audits that uncover opportunities and gaps
• Strategic content planning focused on topical authority and semantic relevance
• ‘Search everywhere optimisation’
• Citations and brand awareness strategies that build lasting authority
• Tailored guidance on optimising for AI search features and LLM ranking factors
• Technical audits

Let us help you unlock growth in the new SEO era—reach out today to learn how

 

Sources:

Engineering Relevant Content: Tips to Get Your Content into LLMs by Francine Monahan

Query Fan-Out: A Data-Driven Approach to AI Search Visibility by Andrea Volpini

How AI Mode Works and How SEO Can Prepare for the Future of Search by Mike King

Writing and optimizing content for NLP-Driven SEO by Jan-Willem Bobbink