For Founders, Operators, Marketing leads · Intermediate · Informational · Solves: AI overviews cannibalizing traffic, Content not legible to LLMs, Declining organic reach
Key takeaways
- The web is splitting into an agentic layer and an experience layer.
- Most teams over-invest in the experience layer and ignore the agentic layer.
- Machine-legible pages, structured data, and JSON-LD still matter. llms.txt is optional and does not rank you in Google.
- Founders who treat both layers as one system will own the next decade.
For most of the last decade, a website was the destination. You built it, you drove traffic to it, you optimized the funnel inside it. That model is breaking apart.
The two layers of the new web
The new web has two layers. The agentic layer is what machines read: structured data, JSON-LD, predictable endpoints, and content modeled for retrieval. An llms.txt file can sit in that layer as an optional courtesy map. It is not a ranking switch. The experience layer is what humans experience: motion, hierarchy, taste, the parts that convert.
Most teams are still optimizing the experience layer and ignoring the agentic layer. That works until a ChatGPT query replaces a Google search, or a Perplexity answer replaces a click. Then the team that invested in machine-legible content wins the impression before the human ever lands.
What founders should build for
For founders, the practical move is to ship for both at once. Make the experience layer better than your competitors. Make the agentic layer legible to the models that are now answering questions about your category. Neither layer is optional anymore.
The founders who treat this as one system, not two, will own the next decade of distribution.
What to do this quarter
Audit your content for machine-legibility. Add structured data. Model your content for retrieval. If you keep an llms.txt, treat it as a maintained index, not a Google ranking lever. Then make the human experience better than anything else in your category.
The agentic layer still needs pages that models can cite. I wrote generative engine optimization without the product pitch for what that actually means on a marketing site.
If you are about to treat llms.txt as a distribution channel, read whether llms.txt actually helps AI search visibility. Google Search does not use that file for ranking. Some non-Google crawlers may use it as a courtesy map.
Implementation table
| Fix | Problem | What to change | Metric | Tool |
|---|---|---|---|---|
| Add JSON-LD to every page | AI engines cannot parse your content into answers | Ship BlogPosting, Article, FAQPage, and BreadcrumbList schemas | Appearance in AI Overviews and Perplexity citations | schema.org + Next.js Metadata API |
| Publish llms.txt at the site root | LLMs have no summary of what your site is about | Write a plain-language brief of your offering, audience, and URLs | Model recall in brand queries | llmstxt.org |
Sources & references
- Google AI Overviews and the future of searchGoogle
Primary source for AI Overviews rollout and behavior.
- llms.txt: a proposal for LLM-friendly sitesllmstxt.org
- Optimizing for AI features in Google SearchGoogle Search Central
Google says you do not need special AI files such as llms.txt for ranking.
