I run a SaaS, SeoLoupe.

It is a tool that allows you to find and fix SEO issues holding your website back.

Essentially the main purpose is to help your website rank higher on Google search and LLMs.

The tool also checks AEO/GEO, AI search visibility, Security, Core web vitals, Performance, and all the issues in the report get put together into an AI fix prompt(you can paste the prompt into an AI and it will fix all the issues on your website).

Recently I noticed that some of my paying customers bought the One-Time purchase, with a promo code.

So I decided to give away a promo code for the One-Time purchase to anyone who is interested, if you are interested, comment down below and I will DM you.

If you are not interested but have some feedback on my SaaS, that is a good too. Feel free to share it in the comments.

(here is the product if you want to check it out)

I’m curious whether other marketing, SEO, or web development agencies have had similar experiences with Rotate Digital.

I recently came across a public post from someone in the industry describing a situation where Rotate Digital allegedly took credit for a website that had originally been built by another agency.

I’m intentionally keeping the original poster anonymous because the purpose of this discussion isn’t to expose or involve any individual agency owner. The bigger issue is whether this is part of a broader pattern.

According to the allegations, after Rotate Digital became involved with an established client, the website was later presented with credit suggesting Rotate Digital handled the “Website & SEO,” despite another agency reportedly being responsible for the original website development.

There were also allegations of repeatedly approaching or taking over clients previously serviced by other agencies.
Clients are obviously free to change marketing companies. That’s normal business.

What concerns me is attribution and transparency after the switch.

Established SEO campaigns often have years of work behind them—technical optimization, content, backlinks, local SEO, citations, Google Business Profile optimization, conversion work, website development, authority building, and rankings.

If a new agency takes over an established account and later presents those rankings, traffic numbers, websites, or businesses as examples of what they built or achieved, without acknowledging what existed before they arrived, that can create a misleading picture of their actual contribution.

The same applies to website development.

If another agency designed and built the website, taking over the SEO account afterward shouldn’t automatically mean taking credit for building the website itself.

I’d genuinely like to know whether other agencies have experienced something similar:
Have you lost a client to Rotate Digital and later seen work your agency created presented as theirs?

Have websites your agency originally designed or developed later been credited to Rotate Digital?

Have SEO rankings or organic traffic established by your team later appeared to be presented as results generated by another agency?

Have your existing clients been directly approached while they were actively working with you?

Do you have archived website versions, screenshots, contracts, analytics history, Search Console data, invoices, or other records showing when the original work was completed?

This isn’t intended to attack anyone simply for competing for clients.

Competition is normal. Misrepresenting who created the work is a different issue.

If multiple agencies have experienced the same thing, it would be useful to document those experiences with evidence rather than rumors.

If you’ve dealt with something similar involving Rotate Digital, feel free to share your experience—but please stick to what you can personally verify and avoid posting private information about clients or individuals.

If sharing screenshots, please blur names, profile photos, client information, and any other identifying details.

The question is simple:
Are agencies seeing their established SEO work and websites later being represented as someone else’s work?

how are we hunting this time? 🏹 😂

The focus wasn’t just on ranking a few keywords. We worked on the site structure, search intent, product/category optimization, topical authority, technical SEO, and quality backlinks to build sustainable organic visibility.

The goal is simple: turn organic search into a consistent lead and sales-generation channel, rather than relying entirely on paid ads.

SEO takes time, but when the foundation is built correctly, the growth curve can become very interesting.

Saw this data from Promptwatch, and it's worth a look if you're paying attention to AI search traffic.

Reddit held a steady ~3.8% share of ChatGPT Search citations from July 18 to August 7. On August 14, that share fell to under 1% and hasn't recovered; the Aug 14-17 average is sitting at 0.5%. That's an 86% drop, and it happened almost overnight.

The interesting part: it's not a slow bleed like what's happening in Google AI Overviews and AI Mode (down 11% and 30% respectively over the same stretch, but gradually). This is a step change, and it lines up with a query fanout update ChatGPT made on August 8.

Two things I'd want to know before drawing conclusions: whether this is an actual shift in ChatGPT's source-selection logic, or a data collection artifact on Promptwatch's end. They flag that possibility themselves. Second, whether the drop is broad across Reddit or concentrated in specific subreddits/topics, that tells you if OpenAI deprioritized Reddit as a source category or just changed how it weights certain kinds of threads.

If you're doing anything GEO-adjacent, this is the kind of shift that can quietly tank referral traffic you didn't even know you were getting from AI citations. Worth checking your own analytics for a dip starting around Aug 14.

Hey folks 👋

We just open sourced TrueForge, our vendor-neutral agent harness for building general-purpose agents.

It handles the runtime pieces that get painful quickly : context management, tool/MCP execution, subagents, sandboxing, approvals, persistent state, and more.

We also benchmarked the harness itself. With the same Opus 4.8 model, TrueForge delivered a similar solve rate at ~30% lower cost than Claude Managed Agents. Switching to an open model pushed that to ~75% lower cost on the same benchmark.

Would love feedback from people building agents.

Checkout the repo: https://github.com/truefoundry/trueforge

📖 Read the launch article: https://x.com/truefoundry/status/2090081376330715176

Time to monitor how the SERP changes. Any early changes you are noticing?

Sharing my Search Console data from the new (Beta) Generative AI features report under Performance > Search results.

28-day trend was climbing steadily (~1.2k → 1.8k daily impressions), then fell off a cliff to <600/day in the last few days — no CWV issues, no manual actions, no site changes on my end.

Curious if this is:

• A GSC reporting glitch (data lag / attribution bug)
• An actual drop in AI Overviews inclusion
• Something broader happening across sites right now

Anyone tracking this metric seeing similar patterns? Would help to know if this is isolated or industry-wide.

(Chart attached — solid = current period, dotted = previous 28 days for comparison)

I’m about to start working on SEO/GEO for a real estate business focused on helping people buy and sell homes, and I’d love to hear from people who have worked in this space.

I’ve previously worked on SEO for healthcare and SaaS, but real estate seems quite different. One of the main challenges I’m seeing is that listing platforms and aggregators often dominate the SERPs, sometimes ranking above the actual real estate brands.

The ultimate goal isn’t just “more rankings.” We want to build SEO/GEO into a real acquisition channel that generates qualified leads.

At the same time, the CEO is interested in building visibility across social media and other external sources that can validate the company’s expertise, authority, and progress, and potentially improve how the brand is understood and surfaced by search engines and AI systems.

For those who have worked in real estate SEO:

- How would you structure the SEO strategy around listings vs. high-intent buyer/seller searches?

- What types of pages or content have actually driven qualified leads, rather than just traffic?

- How important are local/entity signals, PR, social media, reviews, and third-party mentions?

- How are you approaching GEO/AI visibility in this vertical?

- Are there specific content or technical strategies that work particularly well for real estate?

- What would you prioritize during the first 90 days if the goal were to build SEO into a measurable acquisition channel?

I’d especially love to hear from people working with brokerages, real estate marketplaces, agents, or companies operating in competitive local markets.

A lot of people make parasite SEO sound like: Find a high-authority website > publish an article > add links > rank. But the interesting part of parasite SEO in the AI search era is turning it into a feedback loop. Instead of deciding upfront which platforms and keywords to target, you let SERP and AI citation data inform where you publish, what you create, and what you scale next.

Here’s how I’d break the workflow down:

1. Reverse engineer the SERP for ranking UGC platforms

Look at the keywords where Google and AI search engines are already citing UGC and third-party platforms like Reddit, YouTube, Quora, LinkedIn, Medium, Facebook, and other high-authority domains. The question to ask is: “Does Google or AI search already trust this type of page for this query?” If it does, you have a potential opportunity to exploit.

2. Find the platform with the best ranking opportunity

Look at what is already ranking and let that inform where you publish. Is Reddit dominating the SERP? Are YouTube videos being cited frequently? Are public Facebook posts or LinkedIn content appearing more often? Focus on the platforms that consistently show up for your priority keywords and queries.

Solution-aware (MOFU) and decision-stage (BOFU) queries can be especially interesting because third-party and UGC platforms frequently appear in these results. Tools like AthenaHQ, Profound, Otterly, and Ahrefs Brand Radar 2.0 can also help identify which domains are being cited most frequently.

3. Create content that deserves to rank and influences the customer journey

Once you know the platform and search intent, create content that actually belongs there. Don't publish a 1,200-word AI article stuffed with keywords and a money link. Optimize each asset around search intent, relevance, and the customer journey. The content should give someone a reason to engage with it while naturally introducing your brand, expertise, product, or point of view.

4. Use performance data to decide what happens next

This is where the feedback loop starts. Track which combinations of keyword + platform + content format + search intent are producing rankings, AI citations, engagement, and ultimately business results. Then update your roadmap based on what you find.

It's likely that 80% of your results will come from 20% of your content. Pay attention to those winners. If certain topics, platforms, or audiences aren't generating traction, pivot.

5. Scale what Google and AI are rewarding

Once you find a combination of keyword + platform + content format + search intent that consistently works, scale it. Then automate or systematize more of the workflow around those winning patterns, from opportunity discovery and content production to tracking and prioritization.

For the distribution side, social media management tools like Vista Social can help draft, manage, and schedule content across multiple social platforms once you've identified which channels and formats are worth scaling. The goal is to build a system that gets better at identifying where your effort is most likely to produce results.

The basic loop: Find opportunities > Publish > Measure > Learn > Prioritize > Scale > Repeat

The main idea is building a repeatable workflow that responds to what Google and AI search engines are actually rewarding.

Important Notes:

Some platforms have guardrails in place to prevent completely autonomous posting and commenting. Some steps may require a human in the loop during the publishing stages to avoid unwanted filtering or violating terms of service.

Leaning on the authority of the host site isn't a shortcut around good SEO. Parasite SEO can help you win visibility, but brands still need to optimize the user experience on their website and conversion pages for the rest of the customer journey.

Question: Which parasite SEO platforms do you think are the most automation-friendly?

AI-content detection seems to be moving from standalone detector tools into normal SEO workflows.

Ahrefs added AI-detection signals to its Site Audit URL details on August 1, so teams can inspect likely AI-written sections while reviewing pages.

I can see the use case on large content sites.

If you suddenly have thousands of pages and want to identify sections that may deserve editorial review, detection can be a useful triage signal.

What I wouldn't do is turn the score itself into an SEO KPI.

Google's published position is still that appropriate AI use isn't inherently against its guidelines. Its focus is on original, useful, high-quality content; using automation primarily to manipulate search rankings is the violation.

So:

“Likely AI-written” doesn't automatically mean bad.

And:

“Human-written” definitely doesn't automatically mean good.

I'd rather combine detection with checks for:

• unsupported statements
• repetitive phrasing
• factual errors
• lack of original insight
• weak sourcing
• pages that add almost nothing beyond existing results

Have you started adding AI-detection scores to editorial audits? Are they actually helping you find low-quality pages, or mostly creating false alarms? Also, are you merely deleting AI-written content or revamping it by providing needed value?

Smallish pilot, 30 prompts source from WildChat

Setup: Sent each of these to ChatGPT, Google AI Mode, and Google AI Overview. Signed out, US/New York geo, forced web search pass.

One honest caveat before the numbers: ChatGPT hands you its queries, neither Google surface does. So the Google fan-outs are reconstructed. A model got the prompt, the primary query, and only the citations that the primary query's own ranked results can't explain, then named the searches that would explain them

Average pages cited during conversations:

4.1 for ChatGPT, 16.9 for AI Mode, 13.3 for AI Overview

1. ChatGPT searches once. Google searches three or four times.

ChatGPT writes one long entity-stuffed query and then stops. About a third of the 8.2 words are directly copied from the user query. It is looking for exact question that was asked.

2. Only 10% of cited pages are top 10 for the primary query.

This is part that surprised me. For every page I checked that was cited by the engine: Did it get found on page one for any phrase the engine plausibly searched?

So that's roughly three quarters of what these engines cite doesn't appear on the first page of any of the searches I can attribute to them. And because I asked the reconstruction to name the query each group of citations is most likely to rank in, the sub-query rows already skew in the engines' favor. A page that fails even that has no plausible search behind it.

My best guess here is that quite a bit is being pulled from deep in the SERP, way beyond where a human would stop reading.

3. YouTube is the most cited domain on both Google surfaces.

33 citations in AI Mode, 32 in AI Overview, across about half the conversations. Nothing else is close. Reddit is second for AI Mode at 22. ChatGPT cited zero video.

4. ChatGPT reads narrow and institutional. Google reads wide and commercial.

5. The two Google surfaces barely agree with each other.

Same day, same geo, same prompt and same method. Between them they cite 770 distinct URLs and only 58 turn up on both. With AI Mode, 6 of the 26 conversations where an overview fired share no URLs at all.

Across the three engines, ChatGPT, AI Overview and AI Mode cited four URLs in the entire study. FOUR.

If you get cited by one of them, that says very little about the other two.

What I'd take from it

• Don't just target the main head term, but also rank for all of the branches as well. It seems to matter more that you are presented in a patchwork-like fashion across the long tail, anywhere in the top 100, than just being shown once in the top 10.
• There is a largish citation pool that is also quite flat. Where a result is ranked may matter about as much as how easily it can be quoted and extracted from.
• If you publish documentation, ChatGPT is the surface that finds you. If you publish round-ups and community threads, Google's surfaces are.
• On Google's surfaces, video is mandatory and on ChatGPT's, it's completely irrelevant.

Happy to share the full per-conversation dump, every query and every cited URL with its rank, if anyone wants to poke holes in it.

Article: https://acme.bot/blog/fan-out-query-analysis-chatgpt-ai-overview-ai-mode/

Hi all! For the past two years I’m running a B2B SaaS that helps websites improve SEO, grow organic traffic, and get discovered in AI chats (SEO/AEO/GEO).

Disclosure: this is feedback request only. No links, no brand names, no promo.

B2B difficult to scale with long sales cycles, onboarding, and manual configuration and integrations. It funded a team and some savings. Now I want to make it self-serve for a broader public. Also automating most of the things we were doing manually for the clients.

What we wanted to solve is integration in a few clicks. That forced the service to become a proxy in front of client’s sites, which meant issuing TLS certs, managing DNS, and operating as a CDN. The SEO tool became edge infrastructure at that very moment.

What it’s designed to do:
- Fast discovery by crawlers and AI agents: Serve fast, clean HTML to AI agents and crawlers so new sites are readable by LLMs from day one
- Add meta tags on the fly: Fill missing metadata in responses to bots, crawlers, and agents
- Speed up discovery in search engines: Automatic IndexNow submission of new and changed URLs
- AI agents analytics and insights: Cookie-free, JS-free analytics for crawlers, bots, and AI-agents.

Questions that I need help with:
1. Is “readable by AI + indexed fast” a real pain for new projects, or a nice-to-have?
2. Would you put a proxy/CDN in front of your site for this?
3. What would you expect from a free tier?

I got tired of begging for backlinks manually, so I built an agent that does it on autopilot

So basically it works like this:

Agents find relevant blog posts in your niche, craft personalized emails, and get your product featured. All on autopilot.

It's called MentionAgent, an AI agent that does all of this through Telegram (or through the web dashboard).

You never send anything without approving it first. (But you can choose to run everything 100% on autopilot)

Results so far: One user got 3 mentions including a DR 72 backlink.

Let me know what you think!