I am putting together a Link Building Scheme (I posted a few days about it looking for feedback but didn't receive any, presumably because it was too long). I've made a shorter pitchdeck and would love to hear your feedback on whether you think it has legs.
The pitchdeck is here. Happy to answer any questions!
Thank you in advance!
I run an AI content system for SEO clients. Before anyone dismisses this as AI slop linking to AI slop, the content layer is the part I've spent most time on, so I'll cover that first. The network sits on top of it and would be worthless without it.
What goes into each article
Keyword research. Real search demand and intent analysis. Targets terms the business should rank for, not whatever was easy to write.
Competitor content research. For every target keyword the system pulls what's currently ranking and analyses it. Subtopics covered, structure, depth, angle, what's missing. The article is built to compete with what's actually in the SERP rather than against a template.
Length set by the SERP. No house word count. If the ranking pages for that term average 900 words, the article is around 900. If they're 3,000, it's 3,000. The competing results decide.
Semantic phrasing research. Related entities and terms search engines expect alongside the primary keyword. Covers the topic properly rather than repeating a phrase.
Deep research into the site it's publishing on. Reads the actual website. What they sell, which services they lead with, coverage areas, positioning, what they've dropped. Only current offers, pricing and testimonials get referenced. This is the thing most automated content gets wrong, and clients spot it instantly when an article mentions a service they stopped offering two years ago.
Tone of voice matching. Analyses how the business already writes. Formal or conversational, technical or plain. Article matches so it reads as part of the site.
Narrative perspective. First or third person, singular or plural. A sole trader and a national contractor don't write about themselves the same way.
Internal linking. Every article links to the relevant service and location pages. An article that ranks in isolation does nothing commercially. The point is passing authority through to pages that convert.
These rank without any external links pointed at them. That's measurable and it's the bit I'd defend hardest.
The network on top
With enough clients running this, linking them together is the obvious thought. Equally obvious problem is that it's a link network and those get caught. So I worked through why they get caught and built against each reason.
Networks normally fail because the sites are obviously link sites, because they link to each other and almost nowhere else, and because they sell volume, which forces placements that shouldn't happen.
Entry
Only real trading businesses. Organic traffic floor, evidence of an actual company, Wayback check for rebuilt expired domains, registration history, outbound linking pattern, spam score, infrastructure overlap.
Rule: if a site's value comes from its backlink profile rather than its business, it's out. That includes clean-looking PBN domains, since Google may have quietly discounted them already and they'd bridge my network into theirs.
Earning placements
One network link earned per 12 genuine external links published to the wider web.
I think this is the part that matters most. Dense clusters get detected, and density is just the ratio of internal to external linking. At 1 in 12 network links are a rounding error in each site's outbound profile.
New sites give nothing for 90 days or 50 external links, whichever comes later.
Loop prevention
Every site holds a position number. A site can only link to a higher number.
Loops become impossible rather than policed. Follow any chain and numbers only increase, so nothing returns to where it started. Reciprocals can't happen either.
Positions reshuffle quarterly, weighted so sites that have sat low move high. New joiners start high since they can't give anyway.
Connection blocking
No placement between sites sharing IP, host, nameserver, analytics container, footer credit, ownership, or the agency that introduced them. If someone brings 100 clients, none link to each other regardless of hosting.
Placement
Hard-coded relevance threshold. Failures are fine and expected.
Where two businesses genuinely relate but no linkable page exists, a real article gets commissioned on the target site. Full research, meant to rank on its own, left 90 days before anything points at it, internal links to the service page. Capped at half of placements, otherwise every incoming link landing on a three month old page is its own pattern.
Anchors mostly branded and naked URL.
Logging
Source site, source article, target page, anchor, date. Powers the pairing check and means anything can be pulled.
No volume promise
Placements happen when something genuine fits. Several in a month or none in a quarter. Selling a number is what forces bad placements.
What's unverified
One system produces content across all sites. I don't think it clusters stylometrically, since research inputs, length, tone, structure and perspective all vary per site, but I haven't measured it. Plan is 60 of mine against 60 comparable blogs, mixed, see if a classifier separates them.
If that fails, none of the rest matters.
What I'm asking
Where does this break? Particularly whether 1 in 12 is enough dilution, and whether anyone's actually observed velocity-based detection rather than theorised it.
I've had this idea for a Link network, but I want your opinions on where this can break:
I run an AI content system for SEO clients. Before anyone dismisses this as AI slop linking to AI slop, the content layer is the part I've spent most time on, so I'll cover that first. The network sits on top of it and would be worthless without it.
What goes into each article
Keyword research. Real search demand and intent analysis. Targets terms the business should rank for, not whatever was easy to write.
Competitor content research. For every target keyword the system pulls what's currently ranking and analyses it. Subtopics covered, structure, depth, angle, what's missing. The article is built to compete with what's actually in the SERP rather than against a template.
Length set by the SERP. No house word count. If the ranking pages for that term average 900 words, the article is around 900. If they're 3,000, it's 3,000. The competing results decide.
Semantic phrasing research. Related entities and terms search engines expect alongside the primary keyword. Covers the topic properly rather than repeating a phrase.
Deep research into the site it's publishing on. Reads the actual website. What they sell, which services they lead with, coverage areas, positioning, what they've dropped. Only current offers, pricing and testimonials get referenced. This is the thing most automated content gets wrong, and clients spot it instantly when an article mentions a service they stopped offering two years ago.
Tone of voice matching. Analyses how the business already writes. Formal or conversational, technical or plain. Article matches so it reads as part of the site.
Narrative perspective. First or third person, singular or plural. A sole trader and a national contractor don't write about themselves the same way.
Internal linking. Every article links to the relevant service and location pages. An article that ranks in isolation does nothing commercially. The point is passing authority through to pages that convert.
These rank without any external links pointed at them. That's measurable and it's the bit I'd defend hardest.
The network on top
With enough clients running this, linking them together is the obvious thought. Equally obvious problem is that it's a link network and those get caught. So I worked through why they get caught and built against each reason.
Networks normally fail because the sites are obviously link sites, because they link to each other and almost nowhere else, and because they sell volume, which forces placements that shouldn't happen.
Entry
Only real trading businesses. Organic traffic floor, evidence of an actual company, Wayback check for rebuilt expired domains, registration history, outbound linking pattern, spam score, infrastructure overlap.
Rule: if a site's value comes from its backlink profile rather than its business, it's out. That includes clean-looking PBN domains, since Google may have quietly discounted them already and they'd bridge my network into theirs.
Earning placements
One network link earned per 12 genuine external links published to the wider web.
I think this is the part that matters most. Dense clusters get detected, and density is just the ratio of internal to external linking. At 1 in 12 network links are a rounding error in each site's outbound profile.
New sites give nothing for 90 days or 50 external links, whichever comes later.
Loop prevention
Every site holds a position number. A site can only link to a higher number.
Loops become impossible rather than policed. Follow any chain and numbers only increase, so nothing returns to where it started. Reciprocals can't happen either.
Positions reshuffle quarterly, weighted so sites that have sat low move high. New joiners start high since they can't give anyway.
Connection blocking
No placement between sites sharing IP, host, nameserver, analytics container, footer credit, ownership, or the agency that introduced them. If someone brings 100 clients, none link to each other regardless of hosting.
Placement
Hard-coded relevance threshold. Failures are fine and expected.
Where two businesses genuinely relate but no linkable page exists, a real article gets commissioned on the target site. Full research, meant to rank on its own, left 90 days before anything points at it, internal links to the service page. Capped at half of placements, otherwise every incoming link landing on a three month old page is its own pattern.
Anchors mostly branded and naked URL.
Logging
Source site, source article, target page, anchor, date. Powers the pairing check and means anything can be pulled.
No volume promise
Placements happen when something genuine fits. Several in a month or none in a quarter. Selling a number is what forces bad placements.
What's unverified
One system produces content across all sites. I don't think it clusters stylometrically, since research inputs, length, tone, structure and perspective all vary per site, but I haven't measured it. Plan is 60 of mine against 60 comparable blogs, mixed, see if a classifier separates them.
If that fails, none of the rest matters.
What I'm asking
Where does this break? Particularly whether 1 in 12 is enough dilution, and whether anyone's actually observed velocity-based detection rather than theorised it.
I've had this idea for a Link network, but I want your opinions on where this can break:
I run an AI content system for SEO clients. Before anyone dismisses this as AI slop linking to AI slop, the content layer is the part I've spent most time on, so I'll cover that first. The network sits on top of it and would be worthless without it.
What goes into each article
Keyword research. Real search demand and intent analysis. Targets terms the business should rank for, not whatever was easy to write.
Competitor content research. For every target keyword the system pulls what's currently ranking and analyses it. Subtopics covered, structure, depth, angle, what's missing. The article is built to compete with what's actually in the SERP rather than against a template.
Length set by the SERP. No house word count. If the ranking pages for that term average 900 words, the article is around 900. If they're 3,000, it's 3,000. The competing results decide.
Semantic phrasing research. Related entities and terms search engines expect alongside the primary keyword. Covers the topic properly rather than repeating a phrase.
Deep research into the site it's publishing on. Reads the actual website. What they sell, which services they lead with, coverage areas, positioning, what they've dropped. Only current offers, pricing and testimonials get referenced. This is the thing most automated content gets wrong, and clients spot it instantly when an article mentions a service they stopped offering two years ago.
Tone of voice matching. Analyses how the business already writes. Formal or conversational, technical or plain. Article matches so it reads as part of the site.
Narrative perspective. First or third person, singular or plural. A sole trader and a national contractor don't write about themselves the same way.
Internal linking. Every article links to the relevant service and location pages. An article that ranks in isolation does nothing commercially. The point is passing authority through to pages that convert.
These rank without any external links pointed at them. That's measurable and it's the bit I'd defend hardest.
The network on top
With enough clients running this, linking them together is the obvious thought. Equally obvious problem is that it's a link network and those get caught. So I worked through why they get caught and built against each reason.
Networks normally fail because the sites are obviously link sites, because they link to each other and almost nowhere else, and because they sell volume, which forces placements that shouldn't happen.
Entry
Only real trading businesses. Organic traffic floor, evidence of an actual company, Wayback check for rebuilt expired domains, registration history, outbound linking pattern, spam score, infrastructure overlap.
Rule: if a site's value comes from its backlink profile rather than its business, it's out. That includes clean-looking PBN domains, since Google may have quietly discounted them already and they'd bridge my network into theirs.
Earning placements
One network link earned per 12 genuine external links published to the wider web.
I think this is the part that matters most. Dense clusters get detected, and density is just the ratio of internal to external linking. At 1 in 12 network links are a rounding error in each site's outbound profile.
New sites give nothing for 90 days or 50 external links, whichever comes later.
Loop prevention
Every site holds a position number. A site can only link to a higher number.
Loops become impossible rather than policed. Follow any chain and numbers only increase, so nothing returns to where it started. Reciprocals can't happen either.
Positions reshuffle quarterly, weighted so sites that have sat low move high. New joiners start high since they can't give anyway.
Connection blocking
No placement between sites sharing IP, host, nameserver, analytics container, footer credit, ownership, or the agency that introduced them. If someone brings 100 clients, none link to each other regardless of hosting.
Placement
Hard-coded relevance threshold. Failures are fine and expected.
Where two businesses genuinely relate but no linkable page exists, a real article gets commissioned on the target site. Full research, meant to rank on its own, left 90 days before anything points at it, internal links to the service page. Capped at half of placements, otherwise every incoming link landing on a three month old page is its own pattern.
Anchors mostly branded and naked URL.
Logging
Source site, source article, target page, anchor, date. Powers the pairing check and means anything can be pulled.
No volume promise
Placements happen when something genuine fits. Several in a month or none in a quarter. Selling a number is what forces bad placements.
What's unverified
One system produces content across all sites. I don't think it clusters stylometrically, since research inputs, length, tone, structure and perspective all vary per site, but I haven't measured it. Plan is 60 of mine against 60 comparable blogs, mixed, see if a classifier separates them.
If that fails, none of the rest matters.
What I'm asking
Where does this break? Particularly whether 1 in 12 is enough dilution, and whether anyone's actually observed velocity-based detection rather than theorised it.
I’m using an iPhone as a webcam with Continuity Camera on a Mac mini. It works well overall, but the image flickers/pulses while recording.
The office lighting is fixed, so I can’t change the bulbs or turn the lights off. I’m in the UK, and I’ve already enabled PAL video formats and selected 1080p at 25 fps on the iPhone—but that doesn’t seem to affect the Continuity Camera feed.
Having had a look online I understand this is probably caused by the lights’ Hz frequency and the camera’s automatic exposure/shutter speed. Is there any way to set anti-flicker, frame rate, or manual exposure for Continuity Camera itself on macOS/iPhone, without using a third-party webcam app such as Camo?
Any built-in workaround would be appreciated.
One of the AI workflow tools I use has recently just posted that they are closing and as a result I am looking for an n8n expert to take the workflows and rebuild them.
Please DM me if you’re a wiz with n8n. I will send project specs during a quick off call. It would be about 3 or 4 workflows, but replicated numerous times for our clients - approximately 90 clients.
Looking for an immediate start.
In line with the community rules - we are https://3rive.ai
One of the AI workflow tools I use has recently just posted that they are closing and as a result I am looking for an n8n expert to take the workflows and rebuild them.
Please DM me if you’re a wiz with n8n. I will send project specs during a quick off call. It would be about 3 or 4 workflows, but replicated numerous times for our clients - approximately 90 clients.
Looking for an immediate start.