Traditional SEO agencies still operate like dinosaurs. They pay junior executives to pull Google Search Console data into spreadsheets, manually rewrite title tags, and stare blindly at Screaming Frog crawls for hours on end. They then package these basic observations into a 50-page PDF audit that takes four weeks to deliver and another six months for the client’s engineering team to implement.
It is slow, it bleeds capital, and the latency kills your growth velocity. The era of the manual technical read-out is dead. I no longer write PDF audits. I use Claude Code instead.
Claude Code is an agentic CLI tool built by Anthropic. Unlike traditional LLM interfaces like ChatGPT where you have to manually copy and paste code into a browser window, Claude Code operates natively inside your terminal. You give it access to your machine, hook it into your local repository, and let it autonomously read, write, execute, and refactor structural architecture in real time.
Most marketers think LLMs are strictly for writing SEO content. They use AI to pump out average blog posts, which is the fastest way to invite a manual Google penalty. Using AI to write fluffy human copy is the least interesting thing you can do with it. I use Claude Code to execute massive technical SEO changes across thousands of files simultaneously.
Use Case 1: Autonomous Next.js Refactoring
When an enterprise client asks me why their Next.js site is failing Core Web Vitals on mobile, the old process involved running manual Lighthouse tests, tracking down Layout Shifts in Chrome DevTools, identifying the offending un-sized images, and submitting a massive Jira ticket to the dev team.
Today, I just point Claude Code at the repository. I instruct it to run a local Lighthouse CI audit, identify the heavily loaded React components that are causing the LCP (Largest Contentful Paint) delays, and execute the fix. The agent uses grep to scan the entire codebase, finds every instance of a raw `` tag missing explicit height and width attributes, and autonomously rewrites them to use the optimised Next.js `
It doesn't just suggest the code—it edits the files, runs `npm run build` to verify there are no compilation errors, and stages the git commit. A process that used to take weeks of back-and-forth is completed in twelve minutes.
Use Case 2: Programmatic Entity Schema at Scale
LLMO (Large Language Model Optimisation) relies heavily on strict JSON-LD schema markup. SearchGPT and Claude do not read your CSS; they ingest your raw structured data.
If an iGaming client needs highly complex, nested Entity Schema deployed across a 5,000-page programmatic cluster, relying on a developer to write a custom Python script or battling with a bloated WordPress plugin is inefficient.
Instead, I provide Claude Code with the exact JSON-LD architecture rules. I instruct the terminal agent to recursively walk through the directory structure, parse the frontmatter metadata from every single markdown or JSX file, format that specific location/odds data into my strict JSON-LD template, and inject it cleanly into the `
` of the page structure. It executes thousands of file writes flawlessly and provides a verified diff summary.Use Case 3: The "Executioner" Pruning Script
Massive enterprise websites—whether e-commerce brands or tech publishers—are drowning in index bloat. They have thousands of zombie pages receiving zero clicks, which cannibalises their crawl budget and dilutes their domain authority.
Before agentic AI, Content Pruning was a nightmare of VLOOKUPs, matching Search Console data to Screaming Frog exports. Now, I ask Claude Code to build a local Python environment. I instruct it to hit the Google Search Console API, download the last 16 months of impression data, and identify every URL that has received zero clicks.
But the real magic is the next step. The agent uses local semantic embeddings to compare the dead URLs to the high-performing URLs. If a dead page matches the topical intent of a live page, Claude Code autonomously writes the Nginx 301 server redirects mapping the dead URL to the live one. Finally, it generates a neat Nginx configuration file ready for immediate server deployment.
Building the Infrastructure, Not Selling Hours
The traditional SEO agency model charges clients for the manual friction of execution. Agencies justify £10,000 monthly retainers by hiding behind the sluggishness of manual audits and Jira tickets.
I charge for the architecture. Setting up the pipeline is where the actual value lives. Once the local agent environment is active, technical execution takes seconds. The client achieves absolute zero-latency updates, and I spend my time actually mapping competitive growth strategies rather than fixing broken title tags.
If you are an SEO consultant, spending your time on manual technical execution is a mistake. Stop managing spreadsheets. Deploy Claude Code, orchestrate the architecture, and move faster than the agencies you compete against.