In a recent LinkedIn post, former LinkedIn employee Alicia Teltz addresses the widespread concern among users about declining post impressions, working to debunk common myths and explain what has truly changed on the platform.
Teltz, who has insider knowledge from her time at LinkedIn, emphasizes that the exact workings of the LinkedIn algorithm remain opaque, even to those within the company. She states:
“Nobody knows *exactly* how the LinkedIn algorithm works. Yes, that includes me. Anyone claiming to know either works on LinkedIn’s engineering team, is married to or related to them, or is outright lying.”
This assertion immediately sets the stage for her analysis, differentiating between speculation and informed insight. Teltz then systematically tackles several popular theories for the drop in reach.
Debunking Common LinkedIn Reach Myths
Alicia Teltz identifies and refutes several prevalent myths that users often cite as reasons for their declining impressions. One of the most common theories, that LinkedIn deliberately lowered reach to encourage the use of its “Boost” feature, is dismissed by Teltz as unlikely.
According to Teltz, damaging user trust would ultimately harm the platform itself. She also addresses the concern that LinkedIn is intentionally silencing women, stating that while the platform’s Large Language Model (LLM) may exhibit biases, as do all AI models, there is no commercial motivation for LinkedIn to suppress women’s reach.
Another myth Teltz tackles is the idea that increased content volume due to AI is the sole cause of reach dips. While acknowledging the rise in AI-generated content, she points out that this alone wouldn’t account for an overnight, platform-wide drop. However, she does note that LinkedIn has announced efforts to combat generic AI-produced content.
Teltz also clarifies the role of posting times and SSI scores. She argues that while early engagement is no longer the primary algorithm signal, it still holds importance, and the optimal posting time is audience-dependent. Furthermore, she explains that the SSI (Social Selling Index) score is not a distribution control but rather a spam-prevention metric.
“Your SSI Score is low. → SSI doesn’t control distribution. → It’s a spam-prevention score.”
The notion of being “shadow-banned” is also addressed, with Teltz suggesting it’s often an easy excuse and encouraging users to raise a ticket with LinkedIn Support if they suspect an issue. Similarly, she confirms LinkedIn’s stance that external links do not inherently harm reach, suggesting that posts with external links that underperform might be too salesy and lack sufficient value.
Understanding the Algorithm’s Actual Shift
Shifting from debunking myths, Teltz explains what she believes are the actual drivers behind the changes in content distribution. She highlights a significant shift in how LinkedIn analyzes and distributes content, driven by its new LLM.
As Alicia Teltz notes, the user feed has evolved from being strictly network-based to becoming more persona-based, functioning similarly to a “For You” page. The system, she explains, now considers factors like user identity, content posted, and engagement patterns to group users with similar profiles.
“The system looks at who you are, what you post, and who/what you engage with. Then it groups you with people “similar” to you. Your content gets shown to them, not just your network.”
This means that content is shown to individuals deemed similar to the poster, rather than primarily to their direct network. Teltz explains that this fundamental change has led to the observed drop in impressions, as users’ audiences may have shifted without their immediate realization.
The Implications of Persona-Based Feeds
Teltz outlines both the potential advantages and disadvantages of this new system. On the positive side, users may connect with more like-minded individuals, creating a more tailored feed. However, the significant downside is the risk of becoming disconnected from the ideal customers or the established network relationships built over time.
To navigate these changes, Alicia Teltz offers actionable advice:
- Ensure your profile accurately reflects your Ideal Customer Profile (ICP) and aligns with your content.
- Actively engage with and connect with individuals within the desired “persona bubble.”
- Maintain clarity about your target audience and the core message of your content.
Teltz concludes by referencing a more in-depth analysis she has provided elsewhere, guiding users on how to regain their reach on the platform.
📝 About This Content
This article is based on insights shared by Alicia Teltz on LinkedIn.
📅 Originally posted on May 28, 2026 | View original post on LinkedIn →