SeaOS Official Technical Insight | 2025 Q2
Over the past decade, the development of public chains has focused on optimizing performance and enhancing general programmability. From Bitcoin's transaction ledger to Ethereum's introduction of the Turing-complete virtual machine, and then to the explosion of Layer2s and modular blockchains, the entire Web3 world has continuously evolved along the path of "faster, more general, and more scalable."
However, a new variable has now emerged: AI Smart Agents are beginning to appear.
We are entering an era of transformation from human-led interaction to smart agent-led behavior. The question that follows is:
Can these AI-native applications directly run on existing mainstream public chains like Ethereum, Solana, and Avalanche? Or rather, are traditional "chains" sufficient to host AI smart agents?
SeaOS's answer is: No.
Why? Because traditional public chains were never designed for "running AI smart agents." Their architecture, semantics, state models, and even operational logic are all based on the "static contract + passive execution" paradigm. AI-native smart agents, however, require a completely different infrastructure.
Three Structural Limitations of Traditional Public Chains
- Static Contract Model, Lacking Support for Smart Agent State Persistence Traditional smart contracts are "stateless response scripts." They can only be passively executed when called and are destroyed upon completion, with no native lifecycle management mechanism. AI smart agents, on the other hand, need to persist, maintain long-term states, and evolve decisions based on context.
In other words:
Contracts are function calls; smart agents are long-running processes. This is simply impossible to achieve on traditional public chains.
- Insufficient Virtual Machine Semantics, Unable to Support Model Inference and Collaborative Execution VMs like EVM and SVM are designed for rule-based computation. They excel at handling conditional jumps, numerical operations, and permission verification but cannot natively process AI-required semantics such as neural network inference, probabilistic decision-making, and model composition.
AI is not just code execution; it's a "model-driven behavior generation system." Traditional VMs fundamentally lack the semantic capability to execute AI models.
- Computing Power and Real-Time Bottlenecks, Unable to Meet Model Deployment and Dynamic Response Needs AI inference typically relies on GPUs, large-scale tensor computations, and low-latency responses. This inherently conflicts with the high-latency, low-throughput, and high-cost attributes of traditional blockchains.
Even with the introduction of oracles or off-chain services, these are merely "external patches" and cannot achieve the structural integration and on-chain autonomy of models with contracts.
What AI-Native Applications Need Is Not a Chain, But an OS
SeaOS's core insight is:
AI smart agents are not "advanced plugins" on the blockchain; they are the native structural units of the next-generation network.
Their operation requires not just an execution environment, but a complete "operating system-level infrastructure (Operating System for Intelligence)."
Therefore, we propose: Moving from "Chain" to "OS" is not a technology stack upgrade, but a paradigm shift.
Feature Dimension
Traditional Public Chain (Chain)
SeaOS (AI-Native Operating System)
Execution Model
Call-and-execute, execute-and-destroy
Long-running agents, with lifecycle and contextual state
Virtual Machine Support
EVM / SVM and other Turing-complete rule engines
Native support for inference VMs, model containers, collaborative semantics
Call State Management
Contract maintains static state
State is persistent, learnable, collaborative, and shareable
Resource Scheduling
Uncontrollable, fixed fees
Decentralized AI computing power network, on-demand scheduling, high elasticity
Smart Logic Update Capability
Hardcoded, non-evolvable
Agents support model upgrades, semantic migration, and self-evolution
SeaOS treats AI models as "first-class runtime entities." Through a modular architecture, an intelligent interlayer system, and heterogeneous VM support, it builds a foundational platform that can truly host, schedule, coordinate, and upgrade AI smart agents.
Designed from System Up, SeaOS Is the Foundation for AI Operations
SeaOS's technical architecture is built around smart agents, with core system layers including:
Heterogeneous Virtual Machine Execution Environment (VM-Layer): Supports multiple types of contract VMs, model inference VMs, model containers, etc., achieving unified calling and semantic docking between contracts and models.
AI Layering Framework: Allows models to be embedded as intelligent components into the main contract flow, supporting on-chain composition, dynamic upgrades, and collaborative interaction.
Distributed AI Power Network (dAI PowerNet): Aggregates global GPU and edge computing nodes to build a trustworthy, efficient, and low-latency on-chain AI inference network.
Semantic Event Bus: Smart agents interact through intentions, tasks, and context, forming a true on-chain "intelligent collaboration system."
Not "AI Compatible," But "AI Native"
This point is crucial.
Most public chains are "AI-compatible" – integrating model APIs, calling AI services, or uploading model parameters. But these are merely short-term optimizations and cannot fundamentally solve the survival problem of AI smart agents.
What SeaOS aims to do is build a system-level ecosystem where AI smart agents can "inhabit, grow, collaborate, and evolve."
This is like the difference in the mobile internet era: A traditional feature phone can also install a browser, but it will never be iOS. What SeaOS wants to do is not just put an "AI browser" on a chain, but build a complete "intelligent ecosystem operating system" that supports AI growth.
In Closing: Building the Underlying Habitat for an Agent Civilization
The essence of Web3 has never been just about chains or coins; it's about structurally reconstructing collaborative relationships and cognitive boundaries.
The rise of AI is pushing blockchain from a "financial tool" to a foundational infrastructure role for "intelligent systems."
SeaOS's mission is precisely at this intersection:
To build an on-chain operating system that natively carries smart agents.
To create the underlying living space for an intelligent collaborative civilization.
To drive the next paradigm shift from static code to dynamic smart agents.
We believe that the next true Web3 will not be driven by "user addresses" but by an "on-chain smart agent network." SeaOS will be their native carrier.
📡 Want to learn more?
Official Website: http://www.seaos.ai
X / Twitter: https://x.com/SeaOSAI
Medium Tech Column: https://medium.com/@seaos.ai.superchain
Telegram Community: https://t.me/SeaOS_Official
Top comments (1)
Really thoughtful post...loved the way you broke down the difference between AI-compatible and AI-native systems. The limitations of traditional chains when it comes to state management, VM semantics, and compute are very real, and you’ve laid them out clearly.
At haveto.com, we’ve been thinking along similar lines, but more from the angle of what devs need right now to build and run AI dApps, especially around making LLM hosting simpler, more cost-efficient, and scalable without backend complexity.
We’d be glad to stay connected and exchange ideas as SeaOS evolves. This is exactly the kind of conversation that helps move the space forward.