Lumiterra, the survival crafting game known for its AI-powered agents, has announced its expansion to the Monad blockchain, opening Early Access on August 13 during the LUMONAD Converge event.
Why Monad Was Chosen
Monad is a high-performance, EVM-compatible Layer 1 blockchain designed for speed and scalability. With sub-second block times, single-slot finality of around one second, and support for up to 10,000 transactions per second, Monad is well-suited for interactive, on-chain environments like gaming and real-time marketplaces.
Its architecture separates consensus from execution, allowing faster transaction processing without heavy hardware demands.
Keone Hon, cofounder of Monad, described the network as “the child of Ethereum and Solana,” combining Ethereum’s developer familiarity with Solana-like performance. This blend offers a strong match for Lumiterra’s AI agents and its economy-focused gameplay.
How Lumiterra Uses Monad’s Capabilities
In Lumiterra, AI agents learn from player behavior and continue operating even when the player is offline. These agents handle harvesting, crafting, and trading, making fast and reliable transaction settlement critical. By running on Monad, Lumiterra benefits from near-instant confirmations, allowing in-game markets to update prices quickly and agent actions to be processed with minimal delay.
Early Access and Rewards
The LUMONAD Converge event serves as the main entry point for players into this new phase. Participants can earn exclusive LUMONAD NFTs, gain testnet access, unlock AI companions, and collect cosmetics linked to various Monad projects. The event also doubles as a large-scale test of Monad’s performance under active player engagement.
What to Watch in the Coming Weeks
Key measures of success will include how efficiently AI agents perform during high activity, how well the in-game marketplace maintains stable pricing, and whether liquidity grows as more players join. The developers will use Early Access as a chance to monitor marketplace health and fine-tune agent behavior if needed.