X Copies Bluesky with a ‘Starterpacks’ Feature that Helps You Find Who to Follow

Why It Matters

X’s rollout signals a strategic push to boost user discovery and engagement, leveraging data‑driven curation to compete with emerging onboarding tools across social platforms.

Key Takeaways

• X launches “Starterpacks” mirroring Bluesky’s curated lists
• X’s packs built from internal data, not user submissions
• Feature rolls out to all users in coming weeks
• Meta Threads and Mastodon also adopting similar onboarding packs
• Past Twitter suggested users list sparked controversy over fairness

Pulse Analysis

X’s decision to launch "Starterpacks" reflects a broader industry shift toward algorithmic onboarding tools that help users quickly find relevant voices. Bluesky’s original packs proved effective at jump‑starting connections, prompting X to replicate the concept with its own data‑driven approach. By sourcing top posters across niches and geographies, X aims to surface high‑quality content while maintaining control over the curation process, differentiating its offering from Bluesky’s community‑generated lists.

The feature revives a familiar pattern from Twitter’s early days, when suggested‑users lists were manually curated to boost visibility for emerging accounts. Those lists sparked debate over fairness, leading Twitter to transition to algorithmic recommendations in 2010. X’s internal methodology sidesteps the bias concerns of user‑generated packs but may still raise questions about transparency and the influence of platform‑owned curation on follower dynamics. Understanding how these packs affect user growth metrics will be crucial for advertisers and creators alike.

X is not alone in adopting this tactic; Meta’s Threads and Mastodon have introduced comparable onboarding packs, underscoring a competitive race to lower friction for new users. As platforms vie for attention, curated starter lists become a low‑cost lever to increase session length and ad inventory. For businesses, early exposure through such packs could accelerate brand discovery, while for the ecosystem, the trend hints at a convergence toward data‑centric, user‑friendly discovery mechanisms across both centralized and decentralized networks.