The new reporting option appears in the dropdown menu beside any post in the LinkedIn feed. The label reads: Seems like AI slop. Users can now flag content they believe to be machine-generated spam, and the platform will route those reports through backend classifiers designed to detect automated posting patterns.
LinkedIn announced the feature on July 31, 2026. The same announcement confirmed the retirement of the platform's AI-driven post enhancement feature, the tool that offered to rewrite user drafts with polished, professional language. The enhancement tool launched in 2024. It is now gone. A new proofreading tool will replace it, one that LinkedIn says will preserve the original author's voice rather than overwriting it.
The sequence is notable. LinkedIn built a feature that encouraged users to generate AI-assisted posts. The feed filled with content that sounded similar, read similar, and triggered the same recognition response in users scrolling past. The company then built a second feature that lets users report exactly that content as low-quality spam. The tool that created the problem and the tool that addresses the problem arrive from the same organization, separated by roughly two years.
The platform's internal data showed spikes in automated posting volume over the past eighteen months. LinkedIn has not disclosed the exact figures, but the company's announcement referenced reports showing massive increases in machine-generated posts since the enhancement tool's introduction. The new backend classifiers and profile verification rollouts are responses to that volume, not preemptive measures.
The proofreading replacement is the quieter detail. The enhancement tool rewrote drafts entirely; the proofreading tool will suggest corrections without altering the author's phrasing. The distinction matters because it shifts responsibility back to the user. If the feed fills with identical-sounding posts now, the platform can point to the preserved voice as evidence that the user chose to sound that way. The AI slop button becomes a user-to-user enforcement mechanism rather than a platform admission.
The shift from enhancement to proofreading reveals a strategic reframing of accountability. When the original tool launched, LinkedIn positioned itself as an active collaborator in content creation, offering to transform user drafts into polished professional prose. The replacement tool positions the platform as a passive assistant, one that catches errors but leaves authorship untouched. This is not a minor semantic adjustment. It is a legal and reputational firewall. The enhancement tool made LinkedIn a co-author of the content flooding its feed; the proofreading tool makes LinkedIn a bystander. The AI slop button completes the pivot by deputizing users themselves as content moderators, distributing the labor of identifying machine-generated spam across the very audience that produced it.
The backend classifiers add another layer to this architecture of deniability. By routing user reports through automated detection systems, LinkedIn inserts algorithmic judgment between the accusation and the consequence. A colleague who flags a post as AI slop does not directly harm the poster's standing; the classifier does, or does not, depending on pattern matches the user never sees. The platform becomes an intermediary twice over, first enabling the content and then adjudicating complaints about it through systems opaque to both parties. The reputation economy now runs on infrastructure that neither the reporter nor the reported fully controls.
LinkedIn runs on professional reputation. The feed is where users build that reputation, post by post, engagement by engagement. A reporting button that lets colleagues flag each other's content as machine-generated spam introduces a new variable into that reputation economy. The cost of sounding like a bot is now visible, surfaced by the same platform that spent two years encouraging users to sound exactly like one.