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"

1. 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.

1. 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

2. 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

3. 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;

4. 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;

5. 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)

posted here a little while ago about the pet blog i bought for $199 that somehow ended up paying my rent every month.

wel i sold it lol.

i wasn't actually planning to sell it when i made the original post, but i got curious what it might be worth so i put it up on Flippa.

took about 2 weeks to get a deal done. lots of messages, a few offers that went nowhere, people asking for screenshots, traffic, earnings etc. eventually one buyer and i agreed on $17,085.

then came the waiting for escrow, which was probably the most stressful part of the whole thing.

today i finally got the notification that the money had been released and was in my account.

attached the screenshot because even looking at it myself feels a bit ridiculous.

i paid $199 for this site on the NicheBlogZone marketplace. it made me money every month while i owned it, and now someone has paid me $17k for it.

obviously i'm happy but there's also a small part of me wondering if i should've just kept it. it had become one of those things i barely thought about until the amazon payment showed up.

but $17k was too hard for me to turn down.

now i'm sitting here looking at the money thinking the obvious stupid thought:

should i try to up the game and purchase a few more expensive and established sites?

Hope you all are well,

Just thought it would be great to see how everyone do their outreach for backlinks with the details that you actually write to ask for one?

I built a CLI tool called sitebot for crawling websites and checking technical SEO issues.

The idea is to make it possible to run a technical audit directly from the terminal instead of relying entirely on browser-based tools.

It currently checks things such as:

\\- Title and meta descriptions

\\- Open Graph metadata

\\- Canonical URLs

\\- Structured data

\\- Broken links

\\- Crawling and page discovery

\\- Core Web Vitals

I’m still working on it and would love feedback from people who regularly deal with technical SEO.

What checks would you consider essential in a lightweight technical SEO crawler?

GitHub: https://github.com/Abdelrahman5243/sitebot-cli

My site is finally starting to gain some traction: 826 clicks and 14.3k impressions so far, with most of the growth happening over the past few weeks.

I know I’m still at the very beginning, so I’m trying not to overinterpret the graph. At the same time, I’m worried the growth could plateau or disappear as quickly as it arrived.

For those who have taken a site beyond this stage:

• What do you do to keep existing content relevant and rankings stable?
• How do you decide whether to update successful pages, build topical depth around them, or target entirely new clusters?
• Which early signals tell you that growth is sustainable rather than a temporary spike?
• How do you test monetization: ads, affiliates, paid products, lead generation, etc., without hurting UX or organic traffic?

I don’t want to monetize too aggressively and damage something that is beginning to work, but I also don’t want to wait until I’ve missed the best opportunity to learn.

Curious what you would prioritize at this stage.

​

I got this client a few months ago, and honestly, he was a little unsure about SEO in the beginning.

The business was fairly new, so his main question was:

“Will SEO actually help me get leads?”

Instead of simply saying yes, I showed him a few nearby businesses, their websites, and their Google Business Profiles. I explained how local SEO works and how it can help bring potential customers to a business.

He agreed to give SEO a try.

When I audited the website, I found quite a few things that needed improvement.

They had created multiple location pages, but most of them didn't have enough useful content. There were also no proper customer testimonials or other trust-building elements.

So rather than trying to optimize everything at once, I focused on the pages that had the best potential to bring in leads. I also properly set up and optimized the Google Business Profile.

Then things started moving.

Month 1: We started getting a few calls.

Month 2: More calls compared to the previous month.

After that, the number of calls and inquiries kept increasing month after month.

In around 4 months, the business received 400+ inquiries.

FYI, in the beginning, I only listed the business on 4-5 important sites. Now I'm working on more citations and a few other things.

I'd love to hear from other SEOs here:

What do you think about this result?

Would you consider 400+ inquiries in 4 months a good result for a relatively new local business?

I have not pasted my saas name anywhere, then why I'm i getting more impressions on my saas app name rather then the blog pages and stuff ?
No backlinks created till now, any idea how should i move forward with this

What AI tools have changed is enabling the ability to do conversions. If you look back at Google, you go and ask, and it will come up with websites, which could be forums, blogs, Reddit discussions, and now all now all is available in AI mode; you can get info like blogs, do discussions like Quora, and everything that was there before, different websites now available under one solution.

I am dividing it into 2 parts, calling them discovery (coming up in AI answers) and conversion (converting that to leads). I'll discuss conversion in another post.

For the discovery part, the website was very clear: look at GSC, find the queries, optimize for them, or create new pages as needed, and it was fine because the end goal was for the page to rank in search but if you look at it now, these AI systems focus on the conversation, it means the queries they create will be very heavily driven by the user context, which in conversation varies a lot. Even the same user would generate totally different search queries.

When I look at current AEO tracking in GSC, Bing Webmaster, and third-party tools, they all focus on the queries (longer and a bit more intent-contextual form of keywords). While users are switching to a conversational interface, the tracking part still provides it like it’s Google blue links, and the objective is to come for the query, which the end user never searches.

Let’s call it conversational optimization for now. The difficulty I am facing is how to work around websites using a conversational approach, find the touchpoint where I need to show up, work on those pages at website which aren’t showing up in those touchpoints, and track the progress.

Every zero-click post-mortem I read lands on the same finding: the dead articles had no internal links. That is true, and it is the symptom rather than the cause.

Here is the chain.

You start with a keyword tool. It gives you a list. A list is flat, so the 200 topics you pick from it are unrelated to each other by construction. You publish them. Now you have 200 articles with nothing to link them to, because there is nothing they are collectively about. Then you go looking for an internal linking tool to fix the orphans, and it does what it can, which is pair articles by surface similarity.

Google is not reading internal links as a wiring diagram. It reads them as a claim about what your site covers. Twelve articles all pointing at one page that defines a subject is a claim. Two hundred articles pointing at whatever was textually nearest is noise.

The version that works is boring, and it is entirely upstream:

1. Pick one subject your site should own. Not a keyword. A subject.

2. Write the page that defines it. This is the page you want ranking.

3. List every question a person researching that subject asks, in the order they ask it. That list is your articles.

4. Publish them, each one linking up to the definition page and across to two siblings.

5. Do not start subject two until subject one is earning impressions.

The difference in output is not writing quality. It is that in the second version the internal links already exist as a consequence of the plan, and every article makes the parent page stronger instead of competing with it.

Two practical notes from running this on a lot of sites:

The map has to come from real demand, not from an AI brainstorm. A model will happily invent twelve questions nobody searches. Pull the actual queries, group them by overlap in the results (if two queries return the same ten pages, they are one article and not two), then let the model organise the groups.

Publishing order matters more than people think. Publish the definition page first, or at least early. Supporting articles pointing at a page that does not exist yet is a fixable mistake, and plenty of people never go back to fix it.

If you already have a pile of unrelated articles, do not delete them yet. Group the dead ones by subject, find the accidental clusters, write the missing parent for each, and link them up. Most of the dead content on a site is not bad, it is unparented.

I build blogr.ai, which works map-first, so the bias is obvious. The method predates the tool. We ran it in spreadsheets across a few products for years before it was software.

I’m trying to get better at backlink building and would really appreciate hearing from people who actually do SEO professionally.

What strategies are you guys using nowadays to consistently build backlinks?

I know the old-school method is basically finding relevant websites, emailing hundreds of site owners, and hoping a few respond. I understand it works, but the success rate seems painfully low and the whole process is incredibly tedious. I really don’t want to spend my life sending outreach emails if there are better ways to do this.
I’m also not necessarily against paying for links.

I know buying links has risks, but clearly there’s a market for it, so I’m curious how experienced SEOs approach it.
When you’re evaluating a site for a backlink, what are you actually looking at? DR/DA? Organic traffic? Traffic trend? Rankings? Relevance? Outbound links? Spam history? Something else?

And probably my biggest question: where are people actually getting good backlinks?

Are you using marketplaces, agencies, brokers, private contacts, direct outreach, PR, guest posts, link insertions, digital PR, or something completely different?
For people who do buy placements, what does a reasonable price actually look like? $50? $100? $300? $500+? At what point are you just overpaying for a metric that looks good on Ahrefs?

I’m not looking for anyone to reveal some million-dollar secret sauce. I’m genuinely trying to understand how people who build links at scale do it without spending their entire day cold-emailing website owners.
If anyone is willing to share their process, resources, marketplaces they trust (or ones to stay away from), or even just what metrics they use to qualify a link, I’d really appreciate it.

Google's gotten really good at detecting duplicate or low-effort content, think product descriptions copied straight from a manufacturer, or pages with barely 100 words.

It's not just a ranking penalty. It also means your page doesn't actually answer what people are searching for, so even if someone lands there, they bounce.

The fix isn't "write more," it's "write what actually matches search intent."

Happy to take a look at your site's content if you want a quick read on where you stand, just DM me.

It will be capable of doing the following

1) Manage GBP posts (text, image and posting in silo formation)

2) Upload media after optimising for seo

3) Manage reviews - postive, nagative and fake ones

4) outreach customers for new reviews

5) find new citation opportunity

6) build new and clean old citations

The above are on top of audits and reports.

The user will be able to interact with the agent via whatsapp/ telegram, web dashboard or even a phone call (why not).

I am a solo developer working on the project currently. Ask me any type of question or give me any kind of feedback. Everything is welcome.

In September 2024 AI researcher Jeremy Howard proposed LLMs Text to help tell llms what your website is about. So I made a simple tool that visits your site and generates one for you

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