Threads’ new AI tool lets users reshape their feed with a simple post
'Dear Algo' gives marketers and users a temporary edge in real-time content curation
Meta’s Threads platform is trying a different kind of feed control—one that puts temporary personalization into the hands of users without requiring menus, toggles, or hidden settings.
For marketers navigating ever-changing audience interests, this move could signal a shift in how platforms handle intent-based discovery and trend surfacing.
This article explores Threads’ launch of “Dear Algo,” a new AI-powered feature that lets people shape what they see simply by posting a request. The approach not only adds a novel twist to real-time engagement but also positions Threads as a more responsive alternative to platforms like X and Bluesky.
Short on time?
Here’s a table of contents for quick access:
- What Threads’ new Dear Algo feature does
- How Meta is blending personalization with visibility
- What marketers should know
Patrecia Meliana
What Threads' new Dear Algo feature does
Threads has rolled out “Dear Algo,” a lightweight AI tool that lets users temporarily adjust their feed by publicly posting their preferences. The process is refreshingly low-friction: users type “Dear Algo” in a post, followed by what they want more or less of—like “Dear Algo, show me more posts about NBA games.”
Once posted, the AI adjusts that user’s feed for the next three days. The signal is public, which means other users can see, repost, and apply the same feed adjustment to their own accounts.
At launch, Dear Algo is available in the US, UK, Australia, and New Zealand. Threads plans to expand availability to more regions soon.
The feature provides a more expressive, open-ended way to surface content interests—especially useful during real-time events or topic spikes.
How Meta is blending personalization with visibility
While most social platforms offer passive personalization (like muting or “not interested” buttons), Threads is experimenting with public, short-term intent signals. This gives users a chance to override the algorithm’s defaults without needing deep platform knowledge.
Meta is positioning Dear Algo not just as a personalization tool, but as a community-driven discovery layer. By making requests public, Threads encourages viral exploration—someone’s interest in “more Olympic updates” could inspire others to repost it, creating momentum around live events or niche topics.
Still, there’s a tradeoff: users who prefer private personalization might hesitate to broadcast their preferences. For now, the feature is opt-in and public by design.
According to Meta, the goal is to reflect what matters right now. This time sensitivity gives Threads a potential advantage over rivals like X (formerly Twitter), which has long leaned on chronological or algorithmic feeds without direct user prompts.
The release comes shortly after Similarweb reported Threads surpassed X in mobile daily active users, with 141.5 million as of January 2026, compared to X’s 125 million. While X still leads in web usage, Threads is steadily gaining ground, and tools like Dear Algo may be part of that momentum shift.
What marketers should know
Marketers should keep a close eye on Dear Algo as both a signal source and an engagement lever. Here’s why it matters:
- Surface real-time interests
Dear Algo posts offer visible demand signals for trending or emerging topics. If users start requesting more about specific events, products, or subcultures, marketers can adjust content in response.
- New targeting cues
Public preference posts can reveal short-term audience intent—useful for tuning campaigns, influencer partnerships, or branded content windows.
- Experiment with repost prompts
Marketers or creators can test strategic Dear Algo posts to spark visibility around their niche (e.g., “Dear Algo, show me more posts about B2B marketing playbooks”).
- Content cycle compression
Because changes last just three days, the window to engage is short. Marketers might need to act faster, but also benefit from less algorithmic lag.
This could also be a glimpse into a broader industry shift: from static algorithm feeds to moment-by-moment, user-directed personalization cues. If Threads continues to iterate here, we may see more participatory feed control become a norm.
