How I Automate SEO With AI — No Engineers, No Expensive Tools

TL;DR: I lead growth and sales at camelAI and I'm not technical. I use camelAI to handle all of our SEO — from AI-powered keyword research using real Google Search Console data, to automated blog publishing with proper meta tags and structured data, to a live analytics dashboard connected to Google Analytics. I used to think I needed an engineer, technical experience with HTML, or an expensive tech stack. But all I needed was plain-English conversations with an AI agent. If you've been looking for a way to do SEO without a developer, this is how I actually do it.

I'm Isabella, COO of camelAI. I'm not technical. I don't write code. And for a long time, SEO felt like something I couldn't do without either hiring a growth engineer or paying for a stack of SaaS tools.

If you've ever Googled "how to use AI for SEO" and gotten a bunch of vague advice about how AI will "transform your workflow," this post is the opposite of that. I'm going to walk through exactly what I do, what I say to the AI, and what it gives me back.

Why SEO Is Hard If You're Not Technical

When I first started doing SEO for camelAI, I thought it was mostly about writing good blog posts. You write something useful, you publish it, people find it. That's not how it works.

The writing is the easy part. Google ranks pages based on technical signals that have nothing to do with how good your content is. Things like:

• Canonical tags that tell Google which version of a page is the "real" one
• Sitemaps that list every page on your site so Google knows what to crawl
• Meta descriptions that control what shows up in search results
• Structured data that helps Google understand what your page is about

These are all code-level changes to your website's HTML. If they're missing or wrong, Google won't rank your page no matter how good the content is. This is what makes technical SEO without coding so difficult for non-technical founders — you know what you want to write about, but you can't touch the infrastructure without pulling an engineer off product work.

That was my problem. I knew our audience and I had the content ideas. But every blog post required someone else's time to handle the technical SEO plumbing.

What I Tried Before AI: SEO Tools That Didn't Solve the Problem

We spent money on three different SEO automation tools trying to fix this.

Athena HQ was supposed to help us show up in AI search results. OnTap SEO generated AI blog posts, but the content was generic, and it didn't handle any of the metadata or technical structure. You'd get a blog post and still have to figure out the HTML yourself.

We also tried a fancy AI tool that touted doing everything, at $2,000/month. It generated copy from competitive research, and I did learn useful SEO concepts from it (like the fact that "How to..." and "X vs Y" titles get more clicks than generic ones). But the tool itself was just giving me text. None of these products touched the technical side. They'd hand you a blog post and leave you on your own for everything that actually makes SEO work — the meta tags, the structured data, the sitemap, the deployment.

This is the gap I see with most AI SEO tools for small businesses: they help you write content, but they don't help you ship it properly.

How I Actually Automate SEO With AI

I use camelAI for all of my SEO work. camelAI is an AI coding agent with a persistent workspace. You chat with it in plain English, it writes and runs code, and everything it builds is automatically live at a URL you can share. I don't see or touch the code. I just describe what I need.

Here's my actual workflow for automating SEO, step by step.

Step 1: Build a Blog With SEO Built In

I started by telling camelAI: "Build me a blog site." It set up a full blog with proper HTML structure, metadata fields, canonical tags, automated sitemap generation, and all the technical SEO scaffolding that I used to need an engineer for. I didn't have to specify any of those things. The AI agent understands what a blog needs to rank on Google and includes it by default.

This is what no-code SEO looks like in practice — not a drag-and-drop page builder, but an AI that handles the technical SEO infrastructure so you can focus on content.

Step 2: Connect Google Search Console and Google Analytics With AI

This is where the workflow gets powerful, and it's also where I thought I'd get stuck.

Google Search Console is a free tool that shows you what search terms people use to find your site (or sites like yours). Google Analytics shows you traffic, signups, and where visitors come from. Both are essential for any SEO strategy, and both require technical setup to connect to your tools.

I told camelAI: "I want to connect Google Search Console so I can do keyword research based on real search data."

It walked me through creating a service account in Google Cloud Console — step by step, including where to click and what to name things. When I got confused ("I don't see the button you're telling me to click"), I told it what I could see on my screen, and it adjusted its instructions. The whole setup took about 5 minutes. I connected Google Analytics the same way.

If you've been searching for how to use AI with Google Search Console or how to connect AI to Google Analytics — this is it. You don't need to understand the technical details ahead of time. You just follow the steps.

Step 3: AI-Powered Keyword Research Using Real Search Data

This is the part that used to feel like it required either deep SEO expertise or an expensive keyword research tool.

With Search Console connected, I have a conversation with camelAI about what keywords to target. Here's an example of what I actually say:

"I want to target small business owners who sell physical products. Think companies like a furniture retailer with eight stores in Australia. What keywords should we be going after?"

camelAI pulls from the Search Console data and finds terms that are high intent but low competition. "High intent" means the person searching is likely looking for a solution, not just browsing. "Low competition" means there aren't already hundreds of established pages ranking for that term. It identifies long-tail keywords — longer, more specific search queries — that we have a realistic chance of ranking for on the first page.

This is AI keyword research with real data, not guesswork. And it happens in the same conversation where I'll eventually ask for the blog post.

Step 4: AI Content Generation Optimized for SEO

From the keyword research, camelAI Googles the top-ranking terms, pulls up the posts that are already performing well, reviews what they cover and where they fall short, and writes a blog post that fills the gaps. The AI-generated content is modeled after what's already working in search results, but written around our specific angle and audience.

This is the part that used to take me hours of manual research: reading competitor posts, taking notes, trying to figure out what angle to take. Now it's part of the same conversation.

The blog posts come with proper meta tags, structured headings, Open Graph data, and everything a Google crawler needs to index the page correctly. The content is published directly to our site through automated blog publishing — I don't have to copy-paste into a CMS or ask an engineer to deploy.

Step 5: Keep Content Fresh With AI Content Optimization

One of the scarier things I learned about SEO: Google prefers content that gets updated regularly. If your blog posts go stale, Google will stop indexing them, which means all the work you put into that content stops contributing to your rankings.

I ask camelAI to review our existing content and tell me what needs updating based on staleness and performance. It flags posts that are losing rankings or haven't been touched in a while, and suggests specific changes. This ongoing AI content optimization is the kind of maintenance that I didn't even know I was supposed to be doing until camelAI told me.

For new content ideas, I tell camelAI about new audiences or use cases we want to reach. If I want to target TikTok creators who need landing pages for their bio links, I say that, and it builds a keyword strategy around it.

The AI Analytics Dashboard: SEO Monitoring Without Google Analytics Complexity

I also asked camelAI to build me a live analytics dashboard. My exact prompt was something like:

"I'm head of growth and I'm in charge of monitoring traffic. Show me a dashboard that's going to help me with that. Make sure it's live and filterable by dates."

It built a dashboard that shows traffic sources, page performance, and signup attribution across all our landing pages, free tools, and blog sites. When we get spikes in signups, I go straight to the dashboard to figure out where they're coming from.

If you've ever tried to use the actual Google Analytics interface, you know it's overwhelming. Having an AI-built analytics dashboard — designed around my specific questions — saves me from navigating dozens of menus and filters. This is what AI for Google Analytics looks like when it's actually useful.

Two More Things That Matter for SEO Automation

Automated sitemap generation. camelAI regenerates the sitemap for my blog site whenever I publish or update a post. Sitemaps tell Google what pages exist on your site. If Google doesn't know a page exists, it can't rank it. This used to be something I'd have to ask an engineer to handle.

Custom domains. Everything I build in camelAI, I can publish to our actual website using a custom domain. The blog, the dashboards, and the free tools all live at our real domain, not on a separate platform. This means I'm not just building internal tools — I'm shipping live pages to our production site without an engineer deploying anything.

Before and After: What Non-Technical SEO Actually Looks Like

Before camelAI, my SEO workflow was: write a blog post, ask an engineer to make sure the metadata was right, manually check Google Analytics when I remembered to, and hope for the best.

Now I have AI-powered keyword research connected to real search data, AI content generation that accounts for competitive gaps, automated sitemap management, a live analytics dashboard, and the ability to publish directly to our site — all without writing a single line of code.

You don't need to be technical to do SEO well. You don't need to hire a growth engineer or pay for a stack of expensive SEO automation tools. But you do need a tool that handles the technical parts for you and explains the rest as you go. That's what camelAI does for me, and it's how I run SEO for a startup as a non-technical cofounder.

Want to see the technical architecture behind how our blog handles SEO automatically? Read How to Build a Blog Site That Automates SEO (With AI).

Ready to stop paying for SEO tools that don't handle the technical side? Start doing SEO with camelAI now →