We Analyzed 4 Expert Reports on LinkedIn. Here Are the 5 Most Surprising Truths for 2025.

If you’re a professional using LinkedIn, you know the feeling. You spend valuable time crafting what you believe is an insightful post, only to see it vanish into the digital void with minimal reach and even less engagement. For years, the conventional wisdom was to master a set of “hacks” and “tricks” to game the algorithm by sending the right signals. That era is over.LinkedIn’s algorithm has undergone a fundamental revolution. The incremental changes of the past have been superseded by a new, centralized intelligence that has rendered most old advice obsolete. The game is no longer about sending signals to a complex machine; it’s about communicating effectively with an AI that reads and understands language. This represents a seismic shift from a signal-based system to a narrative-based one.This article distills the most impactful takeaways from recent expert analysis, revealing the new rules for success. We’ll explore the theoretical new AI-driven architecture and how older, signal-based tactics still fit into this evolving ecosystem.

1. The Algorithm Isn’t a Machine to Hack—It’s an AI to Persuade

According to a deep-dive analysis in the Fall 2025  Unofficial LinkedIn Algorithm Guide  by Trust Insights, the single most significant shift is the nature of the algorithm itself. The old system was a “feature factory”—a complex pipeline of models that processed thousands of numerical signals like the number of likes, comment counts, and keywords. Success was about optimizing these signals.That system has reportedly been replaced. The new architecture, as described by the guide, is centered on a reasoning engine called “360Brew,” a massive foundation model that reads and understands natural language, context, and nuance, much like a human would. It doesn’t count your keywords; it comprehends your argument. The new game is not about sending the right signals but about crafting a compelling narrative for an intelligent reader—the AI. It’s important to note this analysis is explicitly unofficial and is not endorsed, approved, or reviewed by LinkedIn.The old game of “sending signals” is over. The new game is about having a conversation. There is no “hack” for a system that is designed to understand language, context, and reasoning in a way that mirrors human comprehension.

2. Your Profile Isn’t a Resume—It’s a Daily Briefing for the AI

This same unofficial analysis highlights a fundamental change in the purpose of your LinkedIn profile, driven by how this new AI engine reportedly functions. It’s no longer a static resume for human recruiters. Instead, think of it as the “Executive Summary” of a dossier that the AI reads every single time it decides whether to rank your content for your network.This process is subject to a critical limitation known as the “Lost-in-Distance” challenge. Just like a human reader, the AI pays the most attention to information presented at the very beginning of a document. This makes your profile headline the single most important line of text on your entire profile. It sets the context for how the AI interprets everything else you post and do. Your prose—in your headline, “About” section, and experience descriptions—is now a direct, primary input for the ranking engine.

3. Video Is for Awareness, Text Is for Relationships

Within this new landscape, the choice between video and text is no longer about which format is “better,” but about your strategic goal.A specific, single-expert study by marketing expert Caroline Giegerich revealed a crucial nuance in how LinkedIn distributes content. Her analysis found that even her lowest-performing video posts nearly tripled the impressions of her top-performing text posts, demonstrating video’s power for broad reach. Video is significantly more effective for building brand awareness and reaching audiences  outside  your immediate network.However, the same study found that written posts dominate for engagement (likes and comments)  within  your existing network. The conclusion is strategic: use video to reach new people and expand your audience. Use text to build deeper connections and foster conversation with the audience you already have.

4. The ‘Share’ Button Is a Trap (Unless You Do This)

Hitting the “Share” button to simply amplify someone else’s content is one of the worst-performing actions you can take on LinkedIn. This penalty on simple amplification is a clear example of the platform’s older, signal-based rules, which prioritize original contribution over curation—a principle that the new AI-driven system appears to be amplifying.Observational research from the  LinkedIn Algorithm Report v8  shows that sharing a post without adding significant original commentary results in a reach reduction of -85% to -90% compared to a normal post.However, a simple but effective technique discovered by researcher Richard Bliss can counteract this effect. To make a shared post perform effectively, you must do two things:

1. Add 150 words of your own description to the shared post.
2. Add 3 unique hashtags that are different from those in the original post.This workaround demonstrates a core principle of LinkedIn: the platform is designed to prioritize and reward original contribution and thoughtful commentary, not just content curation.

5. Your Desktop and Mobile Feeds Live in Separate Universes

Another artifact of the platform’s complex, signal-based architecture is that LinkedIn uses two different sub-algorithms to power your mobile feed and your desktop feed. Your activity on one platform does not directly translate to the other.Data from the same observational report reveals that actions you take on the mobile app—such as connecting with someone or engaging with content—primarily affect what you see in your mobile feed. The same is true for desktop. The feeds are not mirror images; they are curated by separate behavioral inputs.The weighting of actions also differs. Mobile shares are described as “worthless,” while a “like” on mobile has more algorithmic impact than a “like” on desktop. Comments, however, are considered equally strong on both platforms. This means the user experience and the value of your engagement are not identical across devices.

Conclusion: From Algorithmic Hacks to Authentic Conversation

The overarching theme of these changes is clear. The era of chasing simple algorithmic hacks is being replaced by an era where clear, valuable, and context-rich communication is rewarded. The system is moving from a machine to be gamed with signals to an intelligent engine that understands and prioritizes expertise, coherence, and genuine conversation.While specific tactics like optimizing shares and understanding mobile versus desktop still show marginal benefits, the larger strategic imperative is clear: the platform is moving toward rewarding comprehensive, coherent professional narratives. The question is no longer just  what  signals to send, but  what story  you are telling the AI that reads them.