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Gulf Press > Technology > X copies Bluesky with a ‘Starterpacks’ feature that helps you find who to follow
Technology

X copies Bluesky with a ‘Starterpacks’ feature that helps you find who to follow

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Last updated: 2026/01/22 at 4:46 PM
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X, formerly Twitter, is rolling out a new feature called “Starterpacks” designed to help users discover relevant accounts to follow. This move comes after the decentralized social network Bluesky gained traction with its own, user-created starter packs, which curate lists of suggested accounts based on interests. X’s version, announced by its head of product Nikita Bier, will offer curated lists across categories like News, Technology, and Gaming, aiming to improve user onboarding and content discovery.

Contents
A History of Suggested Users on XBeyond X: The Spread of Starter Pack ConceptsImplications for User Discovery and Algorithm Influence

The company plans to launch Starterpacks to all users in the coming weeks. Unlike Bluesky’s approach, X’s lists are being compiled internally, based on the platform’s data regarding “top posters” in various niches and countries. This decision highlights a continuing trend of feature replication among social media platforms.

X Copies Bluesky’s Popular Starter Pack Feature

Bluesky’s starter packs quickly became a popular method for new users to find communities and engaging content on the platform. The ability for anyone to create and share these lists fostered a sense of organic discovery and personalized recommendations. X’s adoption of a similar feature suggests recognition of this successful strategy for user engagement.

However, there’s a key difference. Bluesky’s packs are community-driven, while X’s are centrally controlled. According to Bier’s post, X’s team has spent months identifying influential users to include in these pre-made lists. This approach gives X more control over the suggested accounts but potentially sacrifices the personalized touch of user-generated recommendations.

A History of Suggested Users on X

X is not new to the concept of suggesting users. Back when it was known as Twitter, the platform utilized suggested user lists to help new users build their networks. These lists were initially curated by editors, but the system proved controversial.

Early iterations of suggested users were criticized for disproportionately boosting the follower counts of those included, raising concerns about fairness and algorithmic manipulation. In 2010, Twitter shifted to an algorithm-driven system for generating these suggestions in an attempt to address these issues. The reintroduction of curated lists with Starterpacks represents a return to a more editorial approach.

Beyond X: The Spread of Starter Pack Concepts

The success of Bluesky’s starter packs hasn’t gone unnoticed by other social media companies. Meta’s Threads began testing a similar feature in December 2024, also relying on user-created lists to guide new users. This indicates a broader industry interest in leveraging curated recommendations to enhance the user experience.

Additionally, the decentralized social network Mastodon is currently developing its own version, referred to as “Packs,” further demonstrating the appeal of this onboarding and discovery method. The widespread adoption suggests a potential shift in how social platforms introduce users to relevant content and communities.

Reverse engineer Jane Manchun Wong has already published details of the accounts included in X’s initial Starterpacks, providing a preview of the platform’s selections. This early access allows observers to analyze X’s criteria and assess the potential impact of the feature.

Implications for User Discovery and Algorithm Influence

The introduction of Starterpacks could significantly impact how users discover content and build their networks on X. By highlighting specific accounts, X is directly influencing the information users are exposed to. This raises questions about the platform’s editorial choices and the potential for bias.

Furthermore, the feature could affect the organic reach of accounts not included in the curated lists. While X maintains that the algorithm will continue to play a role in content discovery, the prominence of Starterpacks may shift some attention away from algorithmic recommendations. The impact on overall social media marketing strategies remains to be seen.

The move also reflects a broader trend of social platforms attempting to combat declining engagement by improving user onboarding and content relevance. Competition in the social media landscape is fierce, and platforms are constantly seeking ways to attract and retain users.

Looking ahead, the success of X’s Starterpacks will depend on user reception and the platform’s ability to maintain the lists’ relevance. It remains uncertain whether X will eventually allow users to create their own Starterpacks, mirroring the approach taken by Bluesky and Threads. Monitoring user feedback and engagement metrics will be crucial for X as it refines this new feature and assesses its long-term impact on the platform.

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