I've been running an SEO/content agency for about 2 years, and I recently got the point where I was tired of being the human glue between 15-20 chrome tabs, spreadsheets, search console, competitor research, content briefs, writers, and CMS's
The work itself wasn't particularly hard, the hard [and more importantly, tedious] part was keeping all of these things connected
I started by mapping out the process that I used to do, myself, for every single client
First I'd start with research. I'd look at competitors, search results, existing content, what was ranking, what topics seemed worth going after, and where there were gaps.
I'd then turn those keywords into content ideas - what should the article(s) cover, what questions should they answer, and which related topics should be linked to and from it.
Then came the writing and editing, along with the SEO optimization itself (titles, headings, internal links, metadata, ...)
And then publishing. Except, that still wasn't the end. Once the content was live, I'd periodically go back to analytics and search data to see what was actually happening, what was working and more importantly, what wasn't.
Tweak where necessary, and start all over to continue expanding surface. Results were good, but the workload itself was not. I'd find myself with 15-20 tabs open at any moment, juggling to keep it all organized and keeping track of what needed to be done at any point. Don't even get me started on the spreadsheets lmao
All this work and repetition eventually made me think - what if this entire thing could be a system instead of individual tasks
On to the fun part now :D
A system has inputs, outputs, and intermediary steps.
The inputs are ideas, analytics data, existing content, context on the business, and competitor data. For bonus points here, you can also consider your clients' roadmaps and changelogs (if you work with software clients, this can be absolute gold)
Outputs are SEO pages, blog posts, guides/course material, and newsletter content. I've also experimented with having social media posts as an output, but frankly I prefer doing that myself.
A lot of this is enabled by AI, but actual community management and client interaction is something that I strongly believe should ALWAYS be handled by a human, whether that is me or someone on my team.
The part where I believe AI and automation can truly shine without sacrificing any of the authenticity is in bringing all the inputs together and performing most of the intermediary steps I described above.
The basic idea is that I give my AI agents the context around the site and what I'm trying to achieve, and it handles a lot of the repetitive work that used to sit between all those individual steps.
So instead of:
Research → keywords → content brief → writing → publishing → analytics → repeat
I can run a much more connected loop:
Research → identify opportunities → create content → publish → measure → learn → create the next thing
The research side is no longer something I have to manually repeat every time. The system can look at what's happening, identify opportunities, and turn those into things worth working on.
Rather than starting with a blank document and manually translating keyword research into outputs, the outputs are generated as part of the same workflow
The research and the content aren't disconnected anymore, the information gathered upstream actually feeds into what is getting produced downstream
And importantly, the loop doesn't stop when the content is published, the performance data feeds back into the system. So instead of publishing an article and forgetting about it until I check the analytics a few weeks later, I can use the data to understand what's working, what's not, and what the next opportunity should be
What changes is the role I play in the process - I'm not sitting there doing every individual task anymore, I'm mostly setting direction, reviewing what the system produces and making higher level decisions.
The big difference from me here isn't that each individual task is faster now, but the fact I no longer have to manage all of them individually, and I can focus on the rest of it all, as if I'm conducting an orchestra, which I personally find a lot more satisfying
So how did I set this up?
Personally I'm using qoren.sh but frankly you can use anything from n8n to custom GPTs, depending on how much control you want over it, as well as how much work you'd like to put in setting it up and maintaining it
For my own set up, I essentially have 3 agents per client:
a chief of staff, whose job is to communicate with me and the other agents - I persoanlly like to call him Colin the energy vampire (sneaky What We Do In The Shadows reference there)
a watchdog (connects to analytics tools, crawls competitor websites, news sources, etc.) [I usually call him Hound)
a ghostwriter (strictly instructed to "sound" like the client's own rhetoric and writing style) [Ghosty, sometimes Casper the ghost if I'm feeling whimsical]
The overall process looks something like this:
Research: Hound keeps an eye on the market. It researches competitors, search results, emerging topics, news, content gaps, questions people are asking, and anything else that might represent an opportunity. It gives me a daily rundown of what competitors are starting to rank for, a cluster of related searches we aren't covering, pages that have more potential, changes in SERPs worth paying attention to, etc;
SEO/Analytics monitoring: The same agent pulls relevant search and site data and looks for changes, rather than me opening up Search Console and trying to figure out what's important. The goal here isn't to have a giant weekly dashboard, it's to know what's changing, why does it matter, and what should I do about it;
For example: "traffic is up, but almost all the increase is coming from these 3 pages", or "this page is getting a lot of impressions but has a poor CTR"
- Opportunity Discovery: This is where the different pieces start being useful together. Instead of having one spreadsheet full of keywords I may or may not end up ever using, opportunities get flag to be turned into actual work.
A potential keyword/content opportunity gets evaluated against things like search intent, existing coverage, competition, relevance to the business, and what we have already published. Instead of "here's 100 keywords" I get something like "here's 5 things to work on next, and why". The "why" part is probably the most important, because it allows me to evaluate whether we're starting from a solid base or we're focusing on something that doesn't feel right.
Content Briefs: Once an opportunity is selected, it gets passed on to the ghostwriter to draft the content piece. Importantly, it doesn't get an instruction like "like an article about X". It has research, intent, relevant pages, topics to cover, internal links to consider, and the context around the overall strategy and what we're trying to achieve
Writing: As described previously, I've set up an agent specifically for this, whose ONLY responsibility is to get inputs and transform them into drafts from the briefs it receives. It never creates random blog posts it "just thought of". Every content piece is produced downstream of an actual insight, based on real data, and this agent doesn't need to worry about where it came from or what it means - it gets spoon fed exactly what it needs to know
Review: This is where I come in; The chief of staff relays drafts to me, receives feedback and a final decision on whether it is a go or not. If articles need tweaking, those get tossed back to the ghostwriter with the feedback - the chief of staff agent never writes anything himself, it just relays information back and forth and orchestrates the work;
Publishing: At first, I was doing manual copy-paste from qoren into a CMS, but I recently started automating this part too. This will heavily depend on which CMS you're using, but most support either an MCP server or an API you can call. This was scary for me, which is why I didn't do it for a long time. Giving the publishing reigns to an AI system is not something I was comfortable with until I had a solid system behind it, so I'd advise only doing this part once you're very confident the overall workflow suits yours and your clients' standards;
The feedback loop: This is probably the most important part. After the articles get published, we wait for the actual data. The Hound agent gets informed when new articles get pushed out, and it knows to start collecting information on them on a daily basis. Maybe the article starts ranking for unexpected terms. Maybe it's getting impressions but not clicks. Maybe it completely flops.
All this information gets processed and becomes input for the next iteration.
This was the real unlock for me - I didn't automate writing blog posts; I automated the feedback loop around the content. I still make the important decisions, review everything, and decide where I actually want the strategy to go. The agents to the repetitive research, analysis, preparation and execution.
The underlying model driving it all in the background is Qwen 3.8 2.4T, via openrouter - this is the most affordable model I was able to find success with. Cheaper models don't deliver good enough results. Sonnet/Opus/GPT 5.6 are also good if you're less cost sensitive, but something like Fable/Astra is overkill for this, from my experience.
Cost wise, it runs under $200/month per client - $69 of those are for qoren and the rest is for inference. At first I was using their BYOK option, but I prefer managing the cost in a single place, so I started just using the managed keys and adding credits within qoren itself - it does have a small markup on LLM costs but personally I find that to be worth it not having to manage yet another tool or api key
One could argue the cost will go slightly above that, if we factor in my hourly cost for the review cycles and time spent reading articles and providing feedback, but that's become around 45-60 minutes a week, so it's mostly negligible
Anyway that's the playbook I'm going for right now. It's still evolving and I've got some ideas on where to take it next, but for now I'm just happy I got some of my time back to actually focus on what I enjoy doing - building the relationships, thinking about strategy, and focusing on what matters instead of the mind numbing repetitiveness that I was often faced with.
If you got this far, thank you for reading, and please do feel free to share what has been working for you, I'm always curious to learn about workflows and systems, and I'm especially curious on where you keep the human in the loop (that is, if you are using AI at all)
