This week, under the leadership of product head Nikita Bier, platform X launched a new tool called "Starterpacks", which begins to package and recommend top accounts for different industries, including a crypto industry starter pack that directly aggregates core figures such as CZ, Brian Armstrong, Vitalik Buterin, and Justin Sun. This means that when new users open X and select "crypto" as an interest, they are likely to start understanding the entire industry from a pre-set list curated by algorithms and the platform. The question of who decides this list and the logic behind its ordering is bringing the tension between "algorithmically preset lists" and "user-driven content discovery" to the forefront. The real issue surrounding this product update is that while the platform is reshaping the entry point, it is also rewriting who holds the primary voice in the crypto narrative.
Rewriting the Crypto Novice World from the Follow List
● The starter pack mechanism essentially pre-packages the step of "who to follow" for users: when new users select crypto-related interests on X, the system provides a pre-installed follow list that concentrates a batch of accounts deemed "industry representatives" by the platform. For seasoned users who are accustomed to searching and selecting on their own, this is just a new entry point; but for newcomers who have just created an X account and lack background in crypto, this is almost equivalent to the "designated textbook" for their first lesson.
● In official terms, Nikita Bier describes the starter pack as "helping new users quickly find accounts that match their interests," presenting a product goal of lowering barriers and shortening cold start times. Rather than letting new users flounder among a vast number of accounts, it is better to provide a streamlined list that allows them to immediately see the "most representative" content. The platform hopes to enhance the initial experience and shorten the path from registration to interaction.
● However, for new users in crypto, such a design effectively delineates their information starting point and cognitive boundaries: who is seen as "must-know" will directly influence whether they initially encounter the exchange perspective, developer perspective, or marketing narrative. In the long run, whether users come to view this algorithmically generated list as a "default collection of industry authorities" will subtly shape their structural imagination of the entire crypto ecosystem.
● A deeper implication is that the entry point for crypto industry narratives is becoming further centralized: from project official websites, media, KOL recommendations, to platform-level "starter packs," who new users see and who they hear from is increasingly less a matter of spontaneous choice and more like a script arranged by platform product decisions and algorithmic scoring. Once the entry point is standardized, it brings both a decrease in onboarding costs and a long-term risk of information diversity and minority voices being drowned out.
From CZ to Vitalik: Who Gets Included in Crypto…
● Currently, the confirmed representative accounts in the crypto starter pack include CZ (Zhao Changpeng), Brian Armstrong, Vitalik Buterin, and Justin Sun, among others. These names require little explanation within the industry: they each stand at the top of different tracks and business models. The starter pack has not publicly disclosed a complete list, but these individuals are enough to sketch out a "default cover composed of centralized exchange and public chain leaders."
● These accounts represent distinctly different camps and interest landscapes: CZ and Brian Armstrong correspond to two massive global trading platforms with divergent regulatory paths and market strategies; Vitalik represents the technical and governance discourse of Ethereum as a decentralized infrastructure; Justin Sun is known for aggressive business operations and cross-chain layouts. Placing them in the same recommendation pool appears neutral, treating "big shots equally," but in reality, it packages multiple competing and conflicting narrative threads for every new user.
● Selected accounts in the starter pack naturally gain an additional sense of authority as "seen by the platform": even if X does not explicitly state "official endorsement," most new users find it difficult to distinguish the subtle difference between "algorithmic recommendation" and "platform trust." Being on this list means winning at the starting line in initial traffic distribution, amplifying their voice, while entrepreneurs, researchers, or community voices not on the list are more likely to be drowned out in the long tail of the recommendation system.
● More troubling is that we cannot know the complete inclusion list and selection criteria, nor how the weight among various accounts is distributed. The composition of the starter pack is almost a black box for ordinary users, who can only infer its logical boundaries from the sporadically named representative accounts. This opacity brings uncertainty and creates potential controversy around "who gets in, who gets out," yet lacks sufficient information to verify whether there is bias or omission.
Product Head and Solana…
● The person responsible for driving this feature, Nikita Bier, has a rather unique identity: on one hand, he is a core figure in charge of the relevant product line at platform X, directly controlling product direction and functionality; on the other hand, he also serves as a Solana ecosystem advisor, with a clear ecological connection to a single public chain. In a social product that emphasizes a neutral platform image, such a "dual identity" naturally raises external concerns about whether his product decisions will influence the industry's traffic landscape.
● Therefore, an unavoidable question arises: when someone deeply bound to a specific public chain ecosystem designs an industry entry-level recommendation tool, is there a possibility of subtle but long-term ecological bias at the strategic level? Even if the recommendation list superficially includes multiple roles, small changes in ranking, exposure frequency, and grouping presentation can invisibly alter a particular public chain or camp's "default status" in the minds of new users.
● Current official information indicates that the starter pack is based on traffic data from the past few months and is generated by categorizing across industries and regions, which sounds like a typical "data-driven" algorithmic choice. However, any recommendation mechanism based on historical traffic, to some extent, projects "past attention distribution" into the future, and the "seemingly neutral" traffic statistics may inherently carry structural biases—especially when those interpreting the data have business relationships with specific ecosystems.
● It must be emphasized that there is currently no public evidence to confirm speculations around "Solana bias" or similar conjectures; all external discussions remain at the level of reasonable suspicion and structural issues. In the absence of detailed algorithm documentation, weight distribution explanations, and a complete list, hastily viewing the starter pack as a directional tool for a particular ecosystem is neither rigorous nor may it obscure more general issues that the platform indeed faces—such as power concentration and recommendation black boxes. This point needs to be approached with sufficient caution in discussions.
Algorithmic Packaging Recommendations and Crypto Information Self…
● From the perspective of platform operations, the starter pack is a routine operation to reduce new user churn: getting newly registered users to immediately follow dozens of active accounts is much more efficient than letting them explore in a blank timeline. For newcomers interested in crypto but lacking a path, directly providing a "curated account collection" can indeed enhance dwell time, interaction probability, and revisit frequency in a short period, which is a reasonable strategy in the growth logic of all social platforms.
● However, from the perspective of users and the industry, a recommendation list packaged by algorithms can easily become the starting point for information echo chambers. Selected individuals often share high degrees of consensus or mutual resonance in viewpoints, interests, and narratives; new users primarily exposed to these voices in the initial stages will unconsciously form a "pre-installed filter," reducing the visibility of dissent, marginal research, or grassroots practitioners. Over time, the entire crypto discourse may become more uniform, yet also more singular.
● The recommendation logic of traditional social platforms has already pushed information dissemination towards centralization in other fields: in finance, politics, entertainment, and other topics, algorithms tend to direct traffic towards a few top accounts. After the crypto circle adopts the same mechanism, new projects and narratives find it increasingly difficult to break through the top list and default recommendations—they must penetrate both the platform's algorithmic wall and the "narrative moat" formed by these starter pack accounts.
● For X, finding a balance between "lowering barriers" and "avoiding overly strong guidance" is a challenge that must be faced moving forward. On one hand, newcomers indeed need friendlier guidance; on the other hand, if the recommendation list is too rigid or lacks sufficient diversity and visible feedback mechanisms, the platform may inadvertently become a strong directional orchestrator of public opinion rather than an infrastructure that allows various voices to compete fully.
Traffic Data-Driven Industry Stratification and…
● According to public information, the starter pack is built on traffic data from the past few months, layered with cross-industry and cross-regional classification logic: first, looking at which accounts received the most visits and interactions in a certain field, then grouping by region and topic, and finally producing a "representative list." From an algorithmic design perspective, this approach balances "data-driven" and "scene coverage," appearing to be a reasonable engineering choice.
● However, when historical traffic becomes the primary sample, it also solidifies existing power structures and discourse centers: players with larger traffic and older accounts are more likely to lock in their advantageous positions through data models; conversely, emerging voices, counter-mainstream narratives, or technical teams that are not adept at operating social media find it difficult to meet the "entry threshold" of the starter pack. Thus, the "Matthew effect" of the strong getting stronger is further amplified at the new user entry point.
● Within the framework of cross-regional classification, there is also an easily overlooked issue: the "American crypto discourse" centered on English content and North American and European markets naturally has an advantage in global traffic statistics, while voices from emerging markets, non-English communities, and localized projects are easily buried in the long tail. For new users from these regions entering X, what they see when they open the app is likely still a highly Americanized industry narrative template.
● In the long run, tools like the "starter pack" may accelerate the standardization of global crypto narratives: who is seen as an authority, how regulation is understood, and how public chain competition is evaluated will all converge towards the viewpoints of a few top accounts. This unification of mainstream narratives may facilitate communication and collaboration, but it also means that local experiences, alternative experiments, and non-mainstream thoughts are being marginalized at an accelerating pace, putting pressure on the ecosystem's diversity.
When the Entry Point is Packaged, a New Round of Discourse…
The starter pack lowers the threshold for crypto novices while quietly reshaping the information starting point: new users can more quickly engage with core industry dialogues, but it also becomes more difficult to break away from a "starting list" preset by the platform and algorithms. It serves as both an onboarding tool and a lever for redistributing discourse power. Currently, we still lack publicly available data on actual usage, conversion effects, and complete algorithm details, making external judgments about its impact inevitably limited by cognitive boundaries, allowing for structural-level analysis only within the range of visible information.
It is foreseeable that in the future, the competition over "who gets in, who gets out, and how to get in" will become a new battleground among project parties, public chain ecosystems, investment institutions, and even individual KOLs. Once the starter pack is viewed as the core entry point for new user attention, all parties will attempt to influence the composition and ranking logic of the list, and the platform will face greater pressure for transparency and fairness. For individual users, while enjoying the convenience brought by this tool, it is essential to consciously navigate beyond preset paths, actively seek diverse information sources, and pay attention to non-mainstream and marginal voices, avoiding being unconsciously tamed by "pre-installed narratives" and mistaking the entire crypto world for just that small group of people packaged by algorithms.
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