Search is just a means to an end.

People don’t search for fun. They search because they want to solve a problem. And increasingly, they’re solving that problem without ever leaving the LLM interface.

We’re entering an era of generative intent and generative engine optimization; where users don’t just want to find information, they want the system to do something for them. And that shift is redefining how we think about content.

Two studies illustrate the trend...

• Semrush (Feb 2025): 70% of ChatGPT queries don’t map to traditional search intent categories (navigational, informational, transactional, commercial). Non-search-enabled prompts average 23 words, nearly 6x longer than search-enabled prompts.

  
  

• Profound (June 2025): Over one-third of ChatGPT prompts are directly generative, meaning they ask for a specific output: "Write X," "Summarize Y," "Create Z."

In other words: generative AI isn’t stealing traffic. It’s providing actions. Every successful generative task would’ve been multiple Google searches before.

LLMs vs. search engines

Search engines retrieve documents and ask users to decide. LLMs synthesize answers and ask users to trust.

That’s a fundamental UX shift.

And the implications go beyond interface design. With search, users are trained to evaluate credibility, context, and click targets. With LLMs, they're prompted to accept synthesis as answer. That changes how we build trust, how we present expertise, and how we differentiate.

LLMs are exploding in adoption for a reason: they collapse the gap between intent and output. Instead of navigating links, users get an answer. Or an outline. Or a poem. Or a product description.

It’s not that Google is dead. Similarweb data shows nearly all ChatGPT users still use Google. The interfaces coexist. But every generative session is one fewer reason to search.

Also: Google is evolving. AI Overviews, AI Mode, and Search Generative Experience (SGE) are all reactions to the LLM shift. We're already in the "AI Overviews as default" world. The search engine is becoming a language model interface.

So, what does this mean for your content strategy?

How to adapt your content strategy for LLMs

Generic “what is X?” posts are over. If a default LLM can answer it, why would anyone come to you?

The only way forward is to create content that can’t be auto-generated; content that’s irreplaceable. In the era of generative intent, the winners will be the brands that create content so unique, so useful, and so human that no model can replace it.

Some ways to adapt your content strategy for LLMs:

1. Abandon easy answers

2. Add something new to the conversation

3. Monitor and optimize for AI visibility

4. Let users solve tasks onsite

5. Build moats beyond search

01. Abandon easy answers

If a generic LLM can instantly answer a query, don’t waste time trying to rank for it. Especially if it’s low-stakes, low-differentiation content.

Avoid:

• “What is X?”

• “Top 10 tools for Y”

• “How to reset your password”

  
  

Instead:

• Identify content that requires judgment, context, or proprietary data

• Turn generic content into expert decision-making frameworks or interactive tools

• Focus on topics where your brand adds a unique signal: experience, process, data, or perspective

  
  

You’re not competing against other brands. You’re competing against default competence.

02. Add something new to the conversation

LLMs compress. They summarize. They remix. So the only way to stand out is to give them something they can’t infer.

Feed the model:

• Original research (benchmarks, surveys, internal studies)

• 1st-party data: "We analyzed 12B emails and found..."

• SME quotes, complete with name, title, and credentials

  
  

When you publish net-new data or frameworks, you create the raw material LLMs train on. That’s how you influence future outputs.

Is there still room for informational content? Yes. If it’s net-new information. Not if it’s another warmed-over listicle.

03. Monitor and optimize for AI visibility

Classic SEO and AI visibility have tactical overlap, but different outcomes. Structured data, crawlability, and E-E-A-T still matter. But so do answer shape, sentence clarity, and whether a model can confidently quote you.

Action:

• Monitor AI Overviews, LLM citations, and prompt completions

• Structure content to be easily lifted into answers (clear sections, concise takeaways, quote blocks)

• Track whether your brand appears in generative interfaces, not just search engine results (Related: The 13 best tools to track brand visibility in AI search)

  
  

Think beyond rankings. Think extractability.

04. Let users solve tasks onsite

If users are looking to get something done, make it easy for them. Instead of providing a manual for how to do it, let them do it right then and there.

Embed utility with:

• Calculators

• Templates

• Prompt builders

• Interactive workflows

These aren’t just content upgrades, they’re defenses. If your site can help users complete a task faster than an LLM can, you win.

And by embedding tools inside your content, you turn static pages into generative endpoints. That’s a better conversion path—and a better user experience.

05. Build moats beyond search

LLMs answer the “what” and the “how.” Humans ask: “Who can I trust?”

Authority is still human. And still earned.

Invest in:

• Owned channels (newsletters, private Slack/Discord, forums)

• Community engagement (Reddit threads, UGC, testimonials)

• Surfacing real voices inside your content

These trust signals compound over time, and they show up in LLM outputs. Even if your name isn’t the answer, your quote or framework might be.

Where should marketers focus today?

Stop competing with AI on its terms. Instead, focus on what machines can't replicate: irreplaceable content. That means creating work that's hard to auto-generate, rich with original thinking or data, and connected to real humans. Don't just inform: equip, guide, and resonate.

This means it's wise to double down on...

• Original research, proprietary data, and case studies with metrics and lessons

• First-hand expertise and experiences

• Behind-the-scenes looks at decision-making processes

• Unique perspectives that challenge conventional wisdom

• Community insights and collective knowledge

To determine if your content is replaceable, ask yourself:

• Could ChatGPT generate something similar?

• Is this just aggregating existing knowledge?

• Does it lack unique insights or original data?

• Are real humans and their experiences missing?

Generative intent changes the SEO playbook. But it also creates a new advantage for brands that create utility, show authority, and feed the model new signals. It’s not about ranking anymore. It’s about resonating, being useful, and offering insights that are uniquely yours.