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Remove every em dash and banned phrase and congratulations: you may now have slop with cleaner punctuation.

Here’s my attempt at defining what AI slop is:

AI slop is content published without enough human understanding, judgement, evidence, or original contribution to justify the reader’s attention.

In short, slop transfers effort from the creator to the reader.

The publisher skips the difficult parts: investigating the topic, verifying claims, developing an opinion, and deciding what matters. The reader then has to work out what is trustworthy, relevant, or written by someone who understands the subject.

The creator saves time. Everyone else pays for it.

At Ahrefs, using AI-first does not mean abandoning the practices that made content worth reading before AI. It means finding ways to preserve them even when AI takes on more of the work.

For most writers, writing used to be the doing. It was where the hours went. AI has made that part incredibly cheap, so more of our effort has to move upstream: deciding what deserves to be written, how to structure the post, and what we can contribute.

Before I ask AI to write prose, I want a rough premise that answers:

You can see these are not new. They exist before AI and should exist even with AI.

AI can help to answer those questions. I can ask it to map the SERPs, challenge my angle, find counterarguments, or point out missing evidence. But it shouldn’t make those decisions for me.

Planning is only half of it. The model also needs something interesting to work with.

Give it the same internet everyone else has, and it will give you a version of the same article everyone else has. A detailed style prompt won’t fix that. You need raw material it could not have produced by itself: interviews, internal knowledge, proprietary data, real demonstrations, failed experiments, and specific examples from your work.

This is where you need things like a Source of Truth for your work. For example, my colleague Mateusz built a Source of Truth app in Letaido: a searchable library for the information that his agent and he rely on when making content.

His tool stores four types of content: facts and stats, explanations, product details, and how-to guides.

Personally, the biggest practical change I’ve made is to talk instead of type.

When I type, I edit as I go. I turn the mess in my head into a tidy summary before AI sees it. Unfortunately, the mess often contains the useful part: uncertainty, caveats, opinions, and half-formed connections.

So I dictate using Wispr Flow. I walk around my room or sit at my desk and talk. I rant, trying to offload as many things as possible from my head so I can give AI more raw material to work with.

Yes, I basically run a podcast episode with myself. Unedited.

Or I ask AI to interview me, find the gaps, and pull out possible claims before proposing an outline. It is no longer being asked to invent the substance. It is organising and interrogating substance I’ve supplied.

AI is very good at hiding decisions inside polished prose.

A one-shot prompt chooses the research, angle, structure, claims, examples, and tone all at once. By the time you see those choices, they have been packaged as an article. They feel more settled than they are.

That is why Ryan’s pipeline mirrors a human editorial workflow instead of producing one mysterious final file. The research, content gaps, outline, and draft are saved separately. He can inspect any stage, fix the output or instruction that caused the problem, and restart from the last acceptable point.

You do not need a 23-skill Claude Code pipeline to copy the principle. Break the work into stages and put a decision between them:

At every gate, the writer has to pass judgement. That might mean asking for more research, deleting a section, changing the angle, or abandoning the article altogether.

This matters because cheap output creates a strange kind of sunk cost. The moment AI gives you 2,000 polished words, you want to improve them rather than question why they exist.

Sunk-cost fallacy, if you will. Except AI can create the sunk cost every six minutes.

Or if you’re not making a pipeline and are using AI for a single article, break the work into stages. Start by brainstorming first. No drafting. Then, once you’re happy with the angle after the back-and-forth, move to the next stage. Ask it for an outline. Keep working and reworking it with AI until you’re happy, then move to the next stage. You could even ask it to steelman your arguments along the way.

The point is to make better decisions, not to watch the word count go up.

Otherwise, AI turns you into an editor before you’ve finished being a thinker.

I think this is where Ahrefs differs from many companies using AI for content.

The obvious cost-saving play is to produce roughly the same article for less, then spend the savings on volume. More articles. More keywords. More pages for Google to crawl.

To be clear, we use AI to automate tedious work so we can save time too. It would be silly to pretend otherwise.

For example, the Data Refresh Hub I built saves at least a day of manual work each month by fetching, cleaning, and preparing updates for 12 datasets. Work that used to happen quarterly, irregularly, or not at all can now happen every month.

So yes, AI does help us publish and update more.

But volume is not the only possible return on efficiency.

Drafting and publishing were never the only constraints on our content. Often, the bigger constraint was everything we wanted to add around an article but couldn’t justify or invest in.

For example, if we wanted to do simple data analysis (not a large scale data study), we might need the help of a data scientist. If we wanted to make a free tool, we needed a developer. A more interactive article needed design and engineering help. A large research project might simply be too manual for one content marketer.

AI lowers those barriers. A writer can now analyse a dataset, prototype a tool, build an interactive element, improve a post’s UI, or automate part of a research project. Not perfectly, and not without specialists when the stakes demand them. But the threshold for trying is much lower.

Or how a content marketer can make a quiz, free tool, or data visualisation without waiting for a rare pocket of developer time. Like our free LLMs.txt generator:

This is the distinction we care about. You can use AI to remove the work behind each article, or you can use it to attempt work you previously could not afford to do.

Don’t just ask how many more articles AI lets you publish. Ask what you can now put inside an article that used to be impossible.

The capability to scale still needs restraint. We are not trying to turn every writer into a content factory. The goal is to expand what each writer can make without lowering the standard for what deserves to go live.

AI may execute much of the process, but a specific person still has to own the result.

The person running the workflow should understand the topic well enough to validate its claims, correct misinformation, explain where the evidence came from, and decide whether they are happy attaching their name to it.

This is why Ryan doesn’t publish hundreds of articles overnight, even with his pipeline.

As the Director of Content Marketing, he’s also the editor of all our content. In short, he reads every word of every article that reaches the Ahrefs blog.

And as a thought leader in the industry, Ryan also has the ability to read a piece and be able to challenge the premise, question the evidence, identify generic sections, and ask whether the article actually fulfils its promise to the reader.

A human in the loop means very little if the human only rubber-stamps the output. They need the knowledge, authority, and willingness to say no.

And yes, even if a piece is AI generated or AI assisted, we still put enough man hours (the writer and the editor) to make sure it’s worthy of being published.

The most prominent domain was Reddit.com, which showed up in 87.8% of SERPs (83.9% worldwide), with an average of 1.29 link appearances.

Along with Ahrefs’ data scientist Xibeijia Guan, I set out to uncover how prominent other sites were, whether young forums appeared, and the impact backlinks might have on results.

When the Discussions and forums SERP feature was present, it included a link to Reddit 83.9% of the time, regardless of country.

We’re still collecting data for August, but early results show it has grown to appear in 86.1% of results so far.

The popular discussion platform was the most prevalent domain in 34 countries, and ranked highly elsewhere, in countries like India (#2) and South Africa (#2).

In those instances, Quora and Facebook are more prominent, respectively.

I also looked at the top 100 most prevalent subreddits, curious whether a new or inactive community has shown up in more Google search results than might be expected.

Their average age was 16 years and 1 month. The youngest overall was r/ScienceBasedParenting, created 8 years ago.

The subreddit with the fewest members was /r/backpain, with 81,027.

The subreddit with the fewest weekly visitors at the time of checking was /r/wichita, with 42,000. It describes itself as the subreddit “for residents of Kansas’ largest city”.

Nothing surprising broke through to the top 100. I know from researching niche topics that smaller, newer communities can appear, but they aren’t among the most prominent communities across all of Reddit.

Using Ahrefs Keywords Explorer, you can easily find the most prominent communities and subreddits most relevant to the industry you’re in.

The Discussions and forums SERP feature can include multiple sites and multiple links from the same site.

The top 10 domains accounted for 84.87% of all links in our research, while the top 100 domains accounted for 91.51%.

Domains ranked from 501 to 1,000 contribute only 1.49% of the overall visibility.

The top 1,000 domains overall accounted for 96.81% of mentions, with just 2.19M additional links remaining across all additional names, in all countries.

In the US, Facebook appeared in 38.3% of all instances of the SERP feature, and that stat stays the same across all countries.

Posts in public Facebook Groups, which officially launched in October 2010, were responsible for all Facebook URLs that appeared.

While it’s possible they’re also being rewritten based on my search query, it’s interesting to see Google picking up the exact AI-generated page headline directly from Facebook:

The top 10 posts appeared for a combined 4,936 queries.

The top 10 Groups accounted for 2.82% of all Facebook’s link placements, and the top 100 for 9.27%.

It wasn’t until January of this year that Facebook overtook Quora for how many search results each shows up in.

While Facebook doesn’t reveal official figures, reports online estimate there are anywhere from 10M-70M active groups on the platform.

Our research found Facebook was the most prominent domain in 4 countries: South Africa, Zimbabwe, Zambia, and Samoa.

It was the second most prominent domain in 23 countries, including the USA, UK, Canada, Australia, Singapore, and Sri Lanka.

Appearing in 8.22M search results, Quora shows for everything from questions about the cost of plastic surgery to questions about unsending emails in Gmail, and everything in between.

Three of its four most prominent threads were discussing where to watch movies online.

In a number of threads, you’ll find the top answer provided by Quora’s AI Assistant, which appears to have launched around the beginning of 2023.

Like other platforms, I was able to find top comments which had little to do with the query itself, or were overly self-promotional.

It points to a challenge all similar communities will face: Some people will interact in good faith, while others will try to get users’ attention for personal gain.

Across all queries in which the SERP feature was present, here are the top 25 domains overall and how many search results each was found in.

Across the top 1,000 domains overall, I was able to get registration dates for 984. Those missing use a .com.au extension, whereby registration dates are not officially published.

(I checked each of the remaining 16 domains in archive.org to make sure none would potentially be the youngest overall.)

Ranking 190th overall, XDAforums.com was technically the most recently registered domain, at under three years old.

That said, it’s the product of a redirect from forums.xda-developers.com, so that’s not when the forum first launched.

At just under four years old, guitar community The Gear Forum does not appear to have been the product of any redirect.

It ranked 748th worldwide, appearing for 1,200 separate search results.

The average domain age was 21 years and 8 months.

It’s important to note that these ages do not account for forums which may have been built on the domain at a later date, or redirected from elsewhere.

If you’ve been thinking of launching a new forum primarily to have a chance of appearing in this SERP feature, do it because you want to launch a forum and see opportunity in that. Whether or not you might appear.

As we’ve seen from companies like Apple and Microsoft, they can also make sense from a customer support perspective.

While we looked at data across dozens of countries, the Discussions and Forums SERP feature didn’t appear in all of them.

In the countries where we found it showing for at least 10,000 individual queries, it was most prevalent in the United States.

Almost all keywords where the Discussion and forums SERP features appear are informational intent. 40.9% have commercial intent, and just 0.6% have navigational intent.

It’s rare for the SERP feature to appear for queries with just one word, matching just 0.3% of appearances.

The feature’s presence scales with query length. It’s roughly three times more likely to appear on an eight-word search than across all queries.

Of the top 1,000 domains overall, 27 have a single URL that accounts for at least 10% of all times their domain appears in the Discussions and forums SERP feature.

768 of the top 1000 domains rely on a single URL for at least 1% of their overall presence.

A health question on the Gleneagles Hospital website accounted for 67% of all times the site showed up.

A single post in 2020, without any replies, accounted for 30% of the overall presence of the domain skill.jobs in the SERP feature.

Domain Rating, also known as DR, is Ahrefs’ score given to the strength of a site’s backlink profile compared to other domains in our database. It works on a logarithmic scale, meaning the leap from 80 to 81 is much larger than the leap from 50 to 51.

The average domain rating of the top 1000 sites prominent in this SERP feature was 58.3.

We saw a moderate Spearman correlation (ρ=0.38) between prominence and DR, but that was driven almost entirely by the top of the list. The bottom half still has domains with a DR of 90+ alongside those with a DR of <10.

The top 100 domains averaged a DR of 78, while the bottom 100 domains averaged a DR of 48.

I also checked the URL rating of the top 1,000 individual discussions, but found no correlation between rankings and backlinks to a specific URL.

In the top 100 URLs, just 6 had a UR score, and none was higher than 5.

I’ve monitored the Discussions and forums SERP feature for years, so analyzing it at this scale was really exciting.

I wasn’t surprised to see how dominant Reddit is, but I was fascinated by Facebook’s growth and just how reliant some sites are on a small number of URLs to appear.

As this research looked at such a large dataset, my recommendation would be to use Ahrefs Keywords Explorer to find the subreddits, groups, and niche forums that are best represented in your industry.

Never go into these communities looking to spam or solely promote yourself. Take the time to learn the general etiquette of how members interact.

As is often the case with Ahrefs, people may already be discussing your products and services, which creates natural opportunities to get involved.