Elon Musk’s social media platform X (formerly Twitter) announced on Tuesday, September 9, 2025, that it has released the latest version of the code powering its ‘For You’ timeline. This move is part of Musk’s larger vision of ensuring transparency and community involvement in shaping the platform’s future.
The company first made headlines in 2023 when it released a significant portion of its algorithm code, calling it a “work in progress.” With this latest step, X is reaffirming its commitment to refining its content recommendation system.
In a post on its official engineering account, the company stated:
“Today, as part of our effort to make our platform transparent, we are open-sourcing the latest code used to recommend posts on the ‘For You’ timeline. Our algorithm is always a work in progress. We will continue to refine our approach to surface the most relevant content to our community.”
This announcement reflects Elon Musk’s philosophy of “open-sourcing everything possible”, a step aimed at inviting developers, researchers, and the public to understand and improve the system.
Back in 2023, X had already shared large portions of its source code, including its recommendation algorithm. The company emphasized that user safety and privacy remain top priorities.
As clarified in the latest update:
“For this release, we aimed for the highest possible degree of transparency, while excluding any code that would compromise user safety and privacy or the ability to protect our platform from bad actors, including undermining our efforts at combating child sexual exploitation and manipulation. Today’s release also does not include the code that powers our ad recommendations.”
This ensures that while the system remains open to scrutiny, critical safeguards against harmful activity remain intact.
X’s Recommendation Algorithm is a complex system of services and tasks designed to curate personalized content across multiple surfaces of the platform — including ‘For You’ timeline, Search, Explore, and Notifications.
In a detailed blog post, X explained how the recommendation pipeline functions:
“For each request, we attempt to extract the best 1500 Tweets from a pool of hundreds of millions through these sources. We find candidates from people you follow (In-Network) and from people you don’t follow (Out-of-Network). Today, the ‘For You’ timeline consists of 50% In-Network Tweets and 50% Out-of-Network Tweets on average, though this may vary from user to user.”
This balance between In-Network and Out-of-Network tweets ensures that users not only stay updated with content from their connections but also discover fresh perspectives and trending discussions.
By open-sourcing its recommendation algorithm, X is setting a precedent in the social media landscape. It offers developers and researchers the chance to analyze, critique, and even suggest improvements, potentially leading to a more balanced and user-friendly platform.
In an era where algorithmic bias, misinformation, and opaque content moderation remain global concerns, Musk’s decision signals an effort to align with public demand for accountability in how content is surfaced to users.
With this move, X aims to strengthen user trust and stand apart from rivals like Meta’s Facebook and Instagram, TikTok, and YouTube, which continue to keep their recommendation algorithms largely private. Analysts suggest that greater transparency could help X rebuild credibility and attract more advertisers and users at a time when competition is intensifying.
Elon Musk’s X is once again in the spotlight for its bold approach to transparency. By open-sourcing the latest code behind the ‘For You’ timeline, the platform is inviting public collaboration while safeguarding privacy and safety.
With the algorithm surfacing a mix of 50% In-Network and 50% Out-of-Network tweets, X continues to evolve its content delivery strategy.
As social media platforms face mounting pressure to disclose how their algorithms work, X’s step could shape future industry standards, fostering trust, innovation, and user engagement.