The LinkedIn Algorithm Changed Again. Here's What It Means for Your Writing.

The algorithm reads your content now

LinkedIn replaced its legacy content distribution system with 360Brew, a 150-billion-parameter foundation model. This isn't a tweak. It's a rebuild.

The old system relied heavily on engagement signals — likes, comments, shares — to decide what to distribute. 360Brew actually reads your post. It evaluates meaning. It can distinguish substantive insight from engagement bait. And it checks your profile to see if you have the authority to write about the topic you're covering.

Think of it like Google's E-A-T framework (Expertise, Authoritativeness, Trustworthiness) — but for your LinkedIn feed.

The numbers tell the story

According to the Algorithm InSights 2025 report, the impact was immediate and sharp:

• Views dropped by 50% • Engagement fell by 25% • Follower growth declined by 59%

These numbers look alarming until you understand what they actually mean. The people losing reach are the ones who were gaming the old system. Engagement bait. Hashtag stuffing. Repackaged platitudes. The algorithm stopped rewarding that, and reach corrected.

If your content has substance, the new system is better for you. Less noise competing for the same attention.

Comments matter more than anything else

The weighting has shifted dramatically. Comments are now 15x more impactful than likes and 5x more impactful than shares.

This makes sense. A like costs nothing. A comment requires someone to stop, think, and type a response. The algorithm is using that as a proxy for quality — if people are responding to your ideas, you're probably saying something worth distributing.

This is also why engagement bait questions ("What's your hot take? 👇") are counterproductive. The algorithm can tell the difference between genuine responses and people reflexively answering a prompt.

Subject matter expertise is a ranking signal

This is the biggest shift. LinkedIn now performs a 360-degree check of your profile when deciding how to distribute your content. It looks at your job history, headline, about section, and posting history to evaluate whether you actually have expertise on the topic you're posting about.

A marketing director writing about campaign strategy will get more distribution than a random account posting the same content. The algorithm is trying to surface knowledge from people who actually have it.

This kills the "thought leader" playbook of posting generically about everything. You need to write about what you know. Your profile needs to reflect it. And your posting history needs to be consistent.

What this means for how you write

Stop writing posts that could've been written by anyone. The algorithm is explicitly designed to detect and suppress generic content.

Posts with your face outperform corporate graphics. Personal experience outperforms abstract advice. Specific details outperform vague inspiration.

The formula is straightforward: write about what you actually know, include details only you would have, and say something that takes a position. The algorithm will reward you for it because that's exactly what it was built to find.