The whitelist phase was designed for a large but intentionally constrained audience. Approximately 25,000 wallets were allowlisted, spanning protocol partners, ecosystem builders, early Hyperliquid users, and long-standing community contributors. The goal was to prioritize alignment and legitimacy while still operating under real-world load conditions that could not rely on off-chain shortcuts or manual gating.

Where HypeRPC Sat in the Stack and What It Powered

dotHYPE used HypeRPC as its primary RPC provider for all read and write interactions during the whitelist reserve flow. During the launch, dotHYPE ran high-volume concurrent eth_call requests for Merkle proof verification, balance checks, and signature validation, alongside state-changing reserve transactions. They also used HypeRPC across three concrete paths:

• Frontend read calls for eligibility checks, including Merkle proof validation and reservation state.

• Transaction simulation and submission for reservation transactions, in both test and production.

• Confirmation polling and receipt finality during peak traffic.

dotHYPE described HypeRPC as the backbone between their frontend and the contracts during the highest concurrency moment of the product.

What dotHYPE Saw During Day One

dotHYPE chose this architecture to avoid off-chain fallbacks and keep the reservation logic on-chain. They did not use off-chain queues, centralised APIs, or manual gating to protect infrastructure. They wanted the contracts to do the work they were designed to do, even with a large whitelist and real user demand.

During the day one reservation window, dotHYPE reported no visible outages, no cascading failures, and no need to throttle or gate users artificially. They also described three outcomes from the reservation stage.

Fast, deterministic eligibility checks

dotHYPE said users confirmed whitelist status without lag or ambiguity, even during heavy traffic windows. They also said they saw no issues during the whitelist check or during the launch of the reservation stage.

Clean reservation settlement

dotHYPE said reservations settled cleanly, with very few dropped transactions or retries relative to the size of the whitelist. They connected that outcome to reduced user confusion and lower support load.

Predictable confirmations and clear feedback

dotHYPE said confirmations stayed predictable. Users received clear success or failure feedback without long-pending states, which they framed as critical for establishing trust during a reservation event.

dotHYPE also noted that Hyperliquid users called it one of the smoothest launches they had seen in the ecosystem at the time. They tied that perception to trust: once users see confusion or distrust during launch conditions, recovery becomes difficult.