In a recent LinkedIn post, Dan Sherrard-Smith delves into the significant shifts in the platform’s algorithm, addressing a common concern among users regarding declining reach. Sherrard-Smith, a consultant who has analyzed extensive data, highlights a fundamental change in how LinkedIn prioritizes content distribution, moving from a numbers-based system to one driven by artificial intelligence and contextual understanding.
Understanding the Shift: From Numbers to Context
Sherrard-Smith explains that the previous LinkedIn algorithm largely favored posts that garnered a high volume of likes and comments, regardless of the engagement’s quality. However, the platform has reportedly introduced a new AI system, which he terms ‘360Brew,’ that re-evaluates content distribution strategies. This new system, according to Sherrard-Smith, is far more sophisticated in its assessment.
As Dan Sherrard-Smith notes:
“THE NEW algorithm prioritises context. It reads your BIO, your posts, your comments, who you engage with… …and then decides who you’re “for”.”
This emphasis on context means that actions previously considered effective might now be detrimental. Sherrard-Smith points out that the algorithm now analyzes a user’s entire profile and engagement history to determine their intended audience. This includes interactions with other users, the content of their posts, and information within their profile biographies.
The Pitfalls of Old Strategies
The consultant argues that many traditional LinkedIn strategies are now counterproductive. Practices like reposting content, tagging more than five people, and participating in engagement pods can inadvertently train the AI to associate users with the wrong network. This can lead to content being shown to peers or competitors rather than the intended target audience of potential clients or customers.
Sherrard-Smith illustrates this with a specific example:
“So if’s a marketing consultant who mostly engages with other consultants, LinkedIn thinks: “Your people are consultants.” And your posts go to your competitors. Not to the CEO’s who’d actually pay you.”
This shift has significant implications for professionals aiming to expand their reach and generate leads. If the algorithm misinterprets a user’s network, their content may become effectively invisible to the decision-makers they wish to influence.
Adapting to the New AI: A 90-Day Retraining Process
Despite the challenges posed by the new algorithm, Sherrard-Smith offers a path forward. He suggests that it is possible to retrain the algorithm to work more effectively for individual users, though this process takes time, estimating around 90 days.
According to Dan Sherrard-Smith:
“The good news: you can fix it. It takes about 90 days to retrain the algorithm to work in your favour… …if you know what you’re doing.”
Sherrard-Smith has developed a guide, “The 2026 LinkedIn Growth Blueprint,” and is hosting a virtual workshop to detail these strategies. He emphasizes that understanding the nuances of the new AI, such as its method of building a ‘dossier’ on users and the concept of ‘cluster effects,’ is crucial for successful adaptation. He also plans to share data-backed insights on current content formats that are performing well and the application of an ’80/20 engagement rule’ to optimize interactions.
By understanding and adapting to these algorithmic changes, professionals can potentially reverse declining reach and improve their visibility on the platform, as highlighted by Sherrard-Smith’s analysis.
📝 About This Content
This article is based on insights shared by Dan Sherrard-Smith on LinkedIn.
📅 Originally posted on January 9, 2026 | View original post on LinkedIn →