Agentic SEO: The Future of SEO
For more than two years, a new concept has been emerging called Agentic SEO. The idea is to perform SEO using agents based on language models (LLMs) that perform complex tasks autonomously or semi-autonomously to save time for SEO experts. Of course, humans remain in the loop to guide these agents and validate the results.
AI Agents and Workflows
Before presenting detailed use cases regarding ideation, it is essential to explain the concept of an agent.
AI Agent
AI agents need at least five key elements to function:
- Tools: These are all the resources and technical functionalities available to the agent.
- Memory: This is used to store all interactions so that the agent can remember information previously shared in the discussion.
- Instructions: Which define its limits, its rules.
- Knowledge: This is the database that contains the concepts that the agent can use to solve problems; it can use the knowledge of the LLM or external databases.
- Persona: Which defines its “personality” and often its level of expertise, including, in particular, its way of interacting.
Workflow
Workflows allow complex tasks to be broken down into simpler subtasks and chained together logically. They are useful in SEO because they facilitate the collection and manipulation of data needed to perform specific SEO actions. Furthermore, in recent months, AI providers (OpenAI, Claude, etc.) have moved from simply offering the model as such to enriching the user experience.
Use-Case: Ideation
Let’s start with ideation. As you know, AI excels at opening up possibilities. With the right methods, it is possible to push AI to explore every conceivable idea on a topic. An SEO expert will then select, refine, and prioritize the best suggestions based on their experience. Numerous experiments have demonstrated the positive impact of this synergy between human creativity and artificial intelligence.
Agentic SEO
Agentic SEO is the use of AI agents to optimize SEO productivity. It differs from Generative Engine Optimization (GEO), which aims to improve SEO to be visible on search engines powered by LLMs such as SearchGPT, Perplexity, or AI Overviews.
No-Code Agent Workflow Tools
Here is an example of a no-code tool called Dng.ai. We use a CSV file provided by Moz, which we analyze using an agent capable of processing the data, generating Python code, and extracting all the necessary information.
Conclusion
I leave you to appreciate the results of a tool that is built from the SEO data of any tool. I think I could have made more than two hours of video on YouTube just on the ideation aspect, as there is so much to say and test. I now invite you to explore the full potential of these tools and experiment with them to optimize your SEO strategy, and next time, I will cover audit use cases with Agentic SEO.
FAQs
- What is Agentic SEO?
Agentic SEO is the use of AI agents to optimize SEO productivity. - How does Agentic SEO differ from Generative Engine Optimization (GEO)?
Agentic SEO uses AI agents to optimize SEO productivity, while GEO aims to improve SEO to be visible on search engines powered by LLMs. - What are the key elements of an AI agent?
An AI agent needs at least five key elements to function: Tools, Memory, Instructions, Knowledge, and Persona. - What is a workflow?
A workflow allows complex tasks to be broken down into simpler subtasks and chained together logically. - What is the purpose of a no-code agent workflow tool?
A no-code agent workflow tool allows users to create complex workflows without coding knowledge, simplifying the process of automating specific SEO tasks.
