For years, the SEO equation appeared to be a fixed and unchanging landscape: optimizing for Googlebot on one side, and creating content for human users on the other. This outdated binary vision is now a thing of the past.
In the current business environment, a new generation of actors is causing significant changes to the online visibility landscape. AI agents such as ChatGPT, Perplexity, Claude, and Gemini are no longer merely processing information; they are exploring, synthesizing, choosing sources to cite, and significantly influencing traffic flows.
For those who are skeptical about the impact of AI agents, I would invite you to consider the concept of Zero Moment of Truth (ZMOT), which was developed by Google over 10 years ago. The principle is straightforward: Prior to any purchase, consumers undertake an extensive research phase. They consult customer reviews, compare across different sites, scrutinize social networks, accumulate information sources, and now use their favorite AIs for final validation.
A New Paradigm
We are currently experiencing a fundamental reconfiguration of the digital ecosystem. In the past, we have identified two or three main engines. However, a new paradigm is emerging.
Google continues to be a leading search engine, utilizing sophisticated algorithms to index and rank content. Humans act as a virality engine, sharing and amplifying information via their social networks and interactions.
It is becoming increasingly apparent that AI agents are assuming the role of an autonomous traffic engine. These intelligent systems are capable of navigating information independently, establishing their own selection criteria, and directing users to sources they deem relevant.
This transformation necessitates a wholly new approach to content creation, which I will be sharing imminently. I will be sharing concepts and case studies that have been successfully implemented with several major accounts.
Agentic SEO
Quick reminder following my two previous articles on the subject: “Agentic AI In SEO: AI Agents & Workflows For Ideation (Part 1)” and “Agentic AI In SEO: AI Agents & Workflows For Audit (Part 2).”
Agentic SEO involves the creation of structured and dynamic content that is designed to appeal not only to Google, but also to conversational AIs.
The approach to content generation is founded on three key pillars:
1. Data Enrichment: Schema.org data, microformats, and semantic tags are becoming important as, when grounding data, they can facilitate understanding and information extraction by language models.
2. Content Modularity: Concise and “chunkable” responses are perfectly suited to Retrieval-Augmented Generation (RAG) ingestion processes utilized by these agents. Content should be designed using autonomous and reusable blocks.
3. Polymorphism: Each page can offer variants adapted according to the type of agent consulting it. It is essential to recognize that the needs of a shopping agent differ from those of a medical agent, and content must adapt accordingly.
If your content isn’t optimized for AI agents, you’re already experiencing considerable strategic lag.
However, if your site is optimized for SEO, you’ve already taken a significant step forward.
The Foundations: Generative SEO And Edge SEO
To understand this evolution, it is important to consider the concepts that have prepared the ground: generative SEO and Edge SEO.
Generative SEO
Generative SEO facilitates the creation of substantial and insightful content through the utilization of language models. This approach automates the process of creating content while ensuring its relevance and quality.
Generative SEO has always existed in primitive forms, such as content spinning and all derived techniques. In today’s digital landscape, we are witnessing a paradigm shift towards unparalleled quality, as evidenced by the preponderance of AI-generated or co-written content across various social networks, including LinkedIn.
Edge SEO
Edge SEO leverages CDN or proxy-side deployment capabilities to reduce deployment latency and enable large-scale content testing from both content and performance perspectives.
These two approaches are naturally complementary, but they still represent a 1.0 vision of automated SEO. It is important to note that traditional A/B testing and content freezing, once generation is complete, limit the potential of the project.
The true revolution lies in the adoption of dynamic and adaptive systems that surpass these limitations.
Agentic Edge SEO
Edge SEO had already revolutionized the very notion of static content. The system now has the capability to modify content in real-time according to the following three variables:
- Firstly, user intention is detected and used to guide content adaptation. The system is able to analyze behavioral signals in order to adjust the message in real-time.
- Next, let us consider the impact of SERP seasonality on modifications. When Google prioritizes certain trends on a given query, content automatically adapts to capitalize on these evolutions.
- Finally, the instant technical optimizations triggered by Core Web Vitals signals ensure that performance is maintained.
Let us consider a product page as a case study. If Google highlights “sustainable” or “economical” trends for a particular search, this page automatically adapts its titles, metadata, and visuals to align with these market signals.
At Draft&Goal, we have developed connectors with the Fasterize tool to facilitate the deployment of AI workflows. These workflows are compatible with all the most recent proprietary or open-source LLMs.
We anticipate that in the future, the system will continuously test these variants with search engines and users, collecting performance data in near real-time.
The most effective version is then selected by the algorithm, in terms of click-through rate (CTR), positioning, and conversion, with results continually being optimized.
For example, imagine a “Running Shoes” landing page, existing in seven distinct versions, each oriented towards a specific angle: price, performance, comfort, ecology, style, durability, or innovation. The polymorphic system automatically highlights the most effective variant according to signals sent by Google and user behaviors.
Three Concrete Applications
These concepts are immediately applicable to several strategic sectors. Allow me to provide three examples of the products currently under active testing.
In ecommerce, product pages are self-evolving. These systems adapt to search trends, available stock, and detected behavioral preferences.
1. To illustrate this point, consider a peer-to-peer car rental platform that manages 20,000 city pages.
Each page automatically adapts according to Google signals and local user patterns. During the summer months, the “Car rental Nice” page automatically prioritizes convertibles and highlights family testimonials. During the winter season, the fleet is transitioned to 4×4 vehicles, with a focus on optimizing the “mountain car rental” service.
2. Another example of technological innovation in the media industry is the ability of major news outlets to deploy “living” articles.
These articles are automatically updated to include the latest breaking news, ensuring that content remains fresh and relevant without the need for human editorial intervention. We continue to prioritize content creation by human professionals, with AI playing a supportive role in maintaining currency.
3. Finally, the promo codes website has successfully managed 3,000 merchant pages, which adapt in real-time to commercial cycles and breaking deals.
Amazon’s Prime Days announcement is met with the automatic enrichment of contextual banners and temporal counters on all related pages. The system is designed to monitor partner APIs in order to detect new offers and instantly generate optimized content. Three weeks before Black Friday, “Zalando promo codes” pages automatically integrate dedicated sections and restructure their keywords.
Toward A New Era Of SEO
The future of SEO lies in publishing dynamic content that can adapt to the ever-changing algorithms of Google’s index. This transformation requires a fundamental paradigm shift, and many SEO agencies we support have already made the switch.
Marketing experts must abandon the “page” logic to adopt that of “adaptive systems.” This transition necessitates the acquisition of new tools and skills, as well as a re-evaluation of our strategic vision.
It is important to note that Agentic SEO is not merely a passing trend; it is the necessary response to an ecosystem undergoing profound mutation. Organizations that master these concepts will gain a significant competitive advantage in tomorrow’s attention economy.
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