LinkedIn opened Collaborative Posts to every member and Company Page worldwide on July 23, 2026, letting a single post carry up to five named co-authors. Around the same time, the company confirmed it had blocked billions of automated comment attempts, and a week later it shipped a button letting any user flag a post as “Seems like AI slop.” Read those three moves together and a strategy appears that no single announcement stated outright: LinkedIn is trying to make authorship expensive to fake and cheap to prove, at the exact moment its own feed is drowning in AI-written posts.
How bad the slop problem actually got
Data from AI detection firm Pangram, reported by TechCrunch, found that more than 40% of long-form LinkedIn posts are now fully AI-generated, and that LinkedIn accounts for roughly 62% of all AI content flagged across the major social platforms Pangram scanned. That is the backdrop for the new “Seems like AI slop” button, reachable from the three-dot menu on any post. Flagging a post hides it from your own feed immediately and feeds a signal into LinkedIn’s internal classifiers. LinkedIn is also quietly scaling back its own writing assistant, replacing the old “Enhance your post” rewrite tool with a more conservative proofreading feature built to preserve a person’s actual voice instead of smoothing it into the same voice as everyone else’s.
What Collaborative Posts actually changes
Collaborative Posts is the other half of the strategy. According to LinkedIn’s own documentation, only the account that created the post can edit it or manage who is listed as a co-author, and every invited collaborator has to actively accept before their name appears. Posts have to be public to qualify, and Company Pages added as collaborators do not receive any engagement metrics at all, only the individual profiles do. That last detail matters more than it sounds: a brand can co-author a post with an employee or executive, reach that person’s network through it, and still not be able to see how it performed. The Page’s own analytics dashboard is the only place that data shows up.
The out-of-network metric nobody is using yet
LinkedIn added an in-network versus out-of-network breakdown to post analytics back in June, splitting impressions between your existing audience and everyone reached beyond it. AJ Wilcox, writing for Social Media Examiner, recommends tracking which topics and formats consistently travel past your own follower base rather than staying contained within it. That is a more useful optimization target than raw engagement, because it tells you which content is actually earning new reach instead of just getting liked by people who already follow you.
A workflow worth trying, and where it breaks
A small agency running a founder’s personal LinkedIn presence could reasonably start co-authoring one post a month with a client executive using Collaborative Posts, then check the out-of-network number a week later to see whether the joint post reached further than either account does alone. Do this for a quarter and you will have real data on whether co-authorship earns reach or just adds names to a post that would have performed the same either way. Where this breaks down is scale. The five-collaborator cap and the requirement that every collaborator actively accept make this a slow, deliberate format, not something you can run across twenty client accounts at once. If your LinkedIn strategy depends on volume, this feature will not help you, and trying to force it will look exactly like the kind of manufactured authenticity the AI slop button was built to catch.
Editor’s note: This area changes quickly, so check LinkedIn’s current help documentation before building a workflow around Collaborative Posts, since parts of the rollout were still marked early access in LinkedIn’s own support pages after the global announcement.
If you are also cleaning up AI-generated content across other platforms, we covered the wider crackdown when Snapchat, Substack, and LinkedIn all started flagging AI content in the same week.