Threads introduced Dear Algo on February 11, 2026, an AI-powered feature designed to modify feed content based on user-written prompts.
The tool allows users to temporarily influence what appears in their Threads feed by publishing a public post beginning with the phrase “Dear Algo.”
According to the company, users can specify topics they want to see more or less of directly within the post. After submission, Threads adjusts feed recommendations for three days.
The system focuses on content relevance rather than permanent preference changes.
Threads also allows users to repost another person’s Dear Algo request. Reposting applies the same feed adjustment rules to the user’s own timeline.
The company framed this as a discovery mechanism for exploring different conversation types.
Dear Algo launched in the United States, New Zealand, Australia, and the United Kingdom.
Threads stated that broader geographic expansion is planned.
The feature adds to Threads’ existing recommendation controls, which already include muting, following, and interest-based ranking signals.
Image Credit: Meta
Why This Matters Today
Dear Algo reflects a wider shift toward user-directed recommendation systems.
Social platforms have historically relied on passive behavioral signals such as likes, watch time, and follows. Prompt-driven controls introduce direct, short-term input.
Temporary feed shaping addresses a common user friction point.
Interests often fluctuate around live events, news cycles, or media releases. Static algorithms can lag behind these short-term changes.
The reposting mechanic introduces a secondary layer of influence. Users can test how different preference statements affect content exposure.
This may alter discovery dynamics across Threads.
The update also signals Meta’s continued integration of AI interaction patterns into consumer apps. Rather than adjusting preferences through hidden settings menus, users interact with the algorithm through visible posts.
From a competitive perspective, feed transparency tools have become more common. Platforms increasingly provide mechanisms to explain or influence ranking systems.
For creators, temporary ranking shifts may affect content visibility patterns, particularly around trending topics.
Our Key Takeaways:
Threads launched Dear Algo as a prompt-based feed adjustment feature. The system modifies recommendations for a fixed three-day window. Users can replicate feed preferences by reposting requests.
The rollout expands AI-driven personalization controls.
- Threads users can temporarily influence feed topics by publishing a “Dear Algo” public post.
- Feed adjustments last three days and do not permanently alter recommendation models.
- Reposting Dear Algo requests introduces shared preference experimentation across users.
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