We often talk about AI for content generation (writing articles, finding ideas), but for an SEO consultant, there is another revolution: in the execution of repetitive and structural tasks that are good for SEO.
Recently, I integrated a new workflow using Cursor (an AI-powered code editor) coupled with Google's AI Gemini. This duo allows me to audit and improve the SEO of my website (my Local SEO SaaS to help small businesses be more visible online) at breakneck speed.
Here is how I transform hours of manual maintenance into minutes of supervision.
The Problem with Technical SEO: Friction
SEO is not magic. It is often a list of small, time-consuming tasks:
- Ensuring articles link to each other (internal linking).
- Verifying that every image has alternative text (Alt).
- Writing JSON-LD code for structured data (Schema.org).
- Etc.
It is necessary for Google, but tedious for humans. This is where contextual AI changes the game.
The Secret: "Codebase Awareness"
The real revolution is not having a chatbot, but having an AI integrated directly into my development tools that possesses what is called Codebase Awareness.
My site content is in Markdown files (Thanks Nuxt Content), which allows Cursor to index my entire website. The AI therefore "understands" its complete architecture:
- It can read the 50 articles on my blog to keep the global semantic context in mind.
- It knows how my files are named and organized. It deduces the URLs.
- It identifies reusable layout components.
I don't simply ask it to analyze text; I ask it to act on an interconnected structure. This is what allows moving from simple writing assistance to true automation of technical tasks.
5 Concrete SEO Use Cases I Use Today
1. Automated Internal Linking 🔗
Instead of rereading all my articles to find where to place a link to my new post, I ask the AI:
Analyze all blog posts. Identify opportunities to create a relevant link to this new article.
It scans the content and inserts the links directly into the code, where it is semantically logical.
2. Contextual FAQ ❓
To enrich a page, nothing beats an FAQ. The AI analyzes the content of my page, identifies gray areas or logical questions a reader might ask, and writes the complete FAQ section in HTML, ready to be published.
3. Schema.org Implementation 🤖
Writing JSON-LD for "Rich Snippets" is a frequent source of errors (one forgotten comma and everything breaks). Now, I simply ask: "Generate the 'Article' and 'FAQPage' Schema for this file."
The code is generated without syntax errors and validated instantly.
4. Metadata Audit 🏷️
I can launch a mass audit:
Check all Titles and Meta Descriptions. Flag those that are too long or do not contain the file's main keyword, and propose an optimized version.
5. Accessibility and Alt Attributes 🖼️
The AI can also analyze image filenames and the context of the surrounding text to write descriptive and relevant alt attributes where they are missing. A plus for SEO.
Result: Time Freed Up for Strategy
The tool doesn't replace the expert, it "super-charges" them. The time I no longer spend writing HTML tags or looking for internal links, I spend on:
- Refining content strategy.
- Analyzing real user needs.
- Improving the product experience.
Technical SEO is moving from "ant" work to "conductor" work.
If you manage a website or a web product, integrating AI via a code editor into your SEO workflow will save you time and take you further!
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I can help you implement this SEO strategy with AI.
With my dual skills as an SEO Consultant and Product Manager Consultant, I help you implement high-performance, automated, and sustainable acquisition levers.