Threads has introduced a new AI-driven personalization tool called Dear Algo, designed to give users temporary control over what appears in their feed. The feature, now rolling out in select markets, allows people to publicly request changes to their content recommendations by posting a message that begins with “Dear Algo,” followed by a specific instruction.
For example, a user who wants more posts about podcasts or fewer updates about a trending TV series can publish a post such as, “Dear Algo, show me more posts about podcasts.” Once submitted, Threads adjusts that user’s feed for three days. After that period, recommendations revert unless another request is made.
Unlike traditional preference controls hidden in settings menus, Dear Algo operates through public posts. That means other users can see these requests and even repost them to apply similar feed adjustments to their own accounts. While Meta frames this as a way to turn personalization into a shared, community-driven experience, the public nature of the feature may not appeal to everyone. Some users may prefer to refine their feeds without broadcasting their interests or content fatigue to followers.
Most social platforms already offer passive feedback tools, such as “Not Interested” buttons or mute options. Threads, X, and Bluesky all provide ways to downrank content. Dear Algo differs in that it invites direct, explicit instructions to the recommendation system. It also positions feed customization as something more dynamic, responding to short-term interests like live sports events or major news cycles rather than long-term algorithmic learning alone.
Meta says the goal is to help Threads remain a real-time platform where conversations shift quickly. If a user wants to follow commentary during an NBA game or temporarily avoid spoilers for a series finale, Dear Algo offers a more immediate adjustment than traditional engagement signals.
The feature is currently available in the United States, the United Kingdom, Australia, and New Zealand, with additional regions expected later. Its launch comes amid growing competition in the social media landscape. Recent third-party data from Similarweb indicates that Threads has surpassed X in daily mobile usage, reporting 141.5 million daily active mobile users as of early January 2026, compared to 125 million for X. However, X continues to maintain stronger web traffic, highlighting a divide between mobile-first engagement and broader cross-platform reach.
As Threads continues to refine its recommendation systems, Dear Algo represents an experiment in making algorithmic control more visible and interactive. Whether users embrace public feed customization—or revert to quieter preference tools—will likely shape how this feature evolves.
