X unveils Bluesky-like “Starterpacks” to help users find accounts that match their interests, curated by X and rolling out in the coming weeks
Bluesky's “Starter Packs,” the curated lists of suggested users to follow, have proven a popular way to help people connect with others …
Context & Ripple Effects
Bluesky built user discovery around custom, subscribable feeds and later added controls for tuning what those feeds show. Its Starter Packs made curated follow recommendations a recognizable social-network onboarding format.
That discovery model gained salience as Bluesky reported sharp user inflows after X policy changes, including a single-day addition of 500,000 users. X’s adoption turns a rival’s differentiating mechanic into a feature within its own network.
First-order effects
- X will begin surfacing curator-selected account lists, giving users a more guided way to build interest-based follow graphs as the rollout starts.
- Bluesky loses some feature-level distinctiveness around Starter Packs, while its existing curation and feed-customization tools remain part of its discovery stack.
Second-order effects
- Curators and creators on X gain another distribution channel: inclusion in a Starterpack can direct new or returning users toward their accounts rather than relying solely on timeline ranking.
- The move raises the competitive bar for social platforms’ onboarding and discovery flows; Bluesky’s prior controls for personalizing feeds illustrate that account recommendations are only one layer of the broader discovery experience.
Third-order effects
- If major networks continue borrowing discovery formats from one another, differentiation will shift away from individual features and toward the quality, transparency, and user control of the systems that shape social graphs.
- Curated discovery can concentrate visibility in the hands of platform-selected or prominent curators, making governance over who creates lists and how they are surfaced a more consequential product question.
The trend: Social platforms are competing to reduce the cold-start problem by combining algorithmic personalization with human-curated pathways into interest communities.