# How to avoid AI slop on LinkedIn when posting for a brand

> LinkedIn is reducing views of generic content. If you post for a brand, review your next post before scheduling it.


Published: 2026-09-22. Original source: [LinkedIn Pressroom, How LinkedIn is Continuing to Tackle AI Slop](https://news.linkedin.com/2026/how-linkedin-is-tackling-ai-slop).

## What changed on LinkedIn

Before changing your LinkedIn calendar, look at what the platform announced. From the three-dot menu on a post or comment, a LinkedIn member can select “Seems like AI slop” to flag AI content they find generic or repetitive.

LinkedIn uses that feedback to improve its classifiers. If a post receives enough of it, the author may see a private tip in that post's analytics. The platform is also changing its writing tools to help proofread and clarify text without replacing the author's voice.

Our reading is that the problem starts before anyone opens an AI tool: a team publishes an idea before it has anything specific to say. “AI is transforming how we communicate” sounds finished. It leaves out what the brand saw, decided, or learned. Before scheduling the next post, ask whether another brand could sign its name to the same sentence. If it could, add an observation your team experienced and can verify.

## Review your next post

Mark one claim that only your team can support. It might come from a customer question, a product change, or something you learned from a campaign. Check that the opening explains what happened and that the rest says why it matters. If AI helped draft the post, keep those real observations and edit the language to sound like your brand.

This is where HeyMark can be your team's working space. For example, if a customer asked why a campaign brought in clicks but few conversations, save that question with the draft and add the answer your team could verify. You can ask Mark for a draft informed by your brand's context, review it with the team in the post comments, and schedule it once the person closest to the case approves the facts. Later, the draft and the post's performance are there to inform the next decision.

## What to watch afterward

Compare the post with older posts on a similar topic. Read the replies and assess each post's performance alongside reach. A reach change alone does not prove LinkedIn labeled your post as AI slop.

If you need more brand context before prompting an AI tool, start with [connecting Claude to your brand's data through HeyMark](/en/guides/connect-claude-heymark/).

## Plan your next post in HeyMark.

Keep the idea, review the draft with your team, and see how it performed in the accounts you connected.

[Start free](https://app.heymark.ai) · [See how it works](https://heymark.ai/en/#product)

## Developer and agent resources

- [HeyMark MCP documentation](https://heymark.ai/en/mcp/)
- [llms.txt](https://heymark.ai/llms.txt)
- [Full site content for language models](https://heymark.ai/llms-full.txt)
- MCP protocol endpoint: `POST https://mcp.heymark.ai`
- OAuth protected-resource metadata: [/.well-known/oauth-protected-resource](https://mcp.heymark.ai/.well-known/oauth-protected-resource)
- MCP server card: [/server-card](https://mcp.heymark.ai/server-card)