1. On-Chain Finance Enters a New Operational Paradigm

As the centralized financial system continues to evolve into a decentralized financial system, the on-chain market is entering a brand new operational paradigm: high-frequency, complex, 7×24 hours of uninterrupted operation, gradually dominated by automated decision-making systems and AI execution models.

In this paradigm, transactions are no longer centered around manual operations or interface interactions but are continuously powered by algorithms, strategy systems, and execution engines. The speed of market state changes, information density, and structural complexity have far exceeded the limits that traditional manual trading and platform interaction modes can endure.

2. Structural Bottlenecks of Traditional Trading Models

In the current on-chain environment, the traditional “platform”-centered trading model is showing significant structural limitations:

• Natural limitations of humans regarding time scale
• Cognitive bandwidth cannot cover high-frequency, multi-state parallel market changes
• Manual execution inevitably has fluctuations in stability, consistency, and long-term operation

As the market enters a phase dominated by automated systems, the manner of interaction between humans and the platform itself is becoming a bottleneck for execution efficiency.

3. Background of PlanX's Creation

PlanX was born amidst this structural transition.

PlanX is an AI-centric on-chain execution protocol aimed at upgrading transaction execution from “platform actions” to protocol-level, verifiable, evolvable, and long-term operational execution infrastructure, thereby restructuring the collaboration between humans and on-chain financial systems.

Execution Beyond Human does not replace humans but extends human capacity boundaries within the financial system.

Founding Team

PlanX was founded by a technology team known for its engineering capabilities, system design experience, and practical on-chain execution. The core consensus of the team is very clear: the essence of competition in on-chain finance is not marketing, traffic, or short-term arbitrage, but the engineering quality and long-term stability of the execution system.

Lex Li｜Co-founder & CEO

Lex Li graduated from UCLA with a degree in Electrical Engineering and Integrated Circuits (EEIC), possessing a composite background spanning aerospace engineering, communication systems, algorithmic trading, and blockchain entrepreneurship.

He has participated in the development of high-performance, mission-critical systems for SpaceX and AT&T and possesses deep engineering understanding of low-latency, high-reliability systems operating under extreme conditions. After entering the Web3 domain, Lex has continuously focused on token incentives and protocol-level economic model design, the construction of underlying structures for decentralized financial systems, on-chain/off-chain collaborative execution architecture, crypto asset strategies, and system-level risk management.

Through multiple system implementations and entrepreneurial practices, Lex has gradually formed a methodology of reverse engineering financial structures based on engineering constraints, which has become the core philosophical source for the execution layer design of PlanX.

Michael Gao｜Co-founder & CTO

Michael Gao graduated from UC Berkeley with a degree in Electrical Engineering and Computer Science (EECS), having worked for DELL EMC, McAfee, Taraxa, and InfStones, with over 10 years of software and systems engineering experience.

He has long focused on blockchain underlying architecture and cryptography, high-concurrency asynchronous distributed systems, enterprise-grade security and infrastructure engineering, Layer 1 public chains, PoS consensus, and multi-chain staking systems.

Michael has been deeply involved in the core design and implementation of several public chains and infrastructure projects, with the ability to understand system-level on-chain state machines, security boundaries, execution determinism, and performance bottlenecks. In PlanX, he is responsible for structuring complex trading, settlement, and risk control logic into verifiable, scalable, and long-term operational on-chain execution protocols.

Technical Advisors

PlanX has garnered support from two artificial intelligence research and engineering advisors with long tenures at DeepMind and Waymo. Their expertise mainly focuses on large-scale machine learning systems, automated decision-making and reinforcement learning, high-reliability automated execution frameworks, and human-machine collaboration and autonomous control in complex systems.

This experience provides important theoretical and engineering support for PlanX in AI-driven execution, Agent architecture design, and long-term autonomous system evolution.

Engineering Philosophy

The PlanX team does not position itself as a traditional “trading platform,” but rather as an engineering builder of on-chain execution systems.

Execution-First System Design Principles

The team consistently adheres to the following core principles:

• Define execution constraints first, then design financial behaviors
• Decompose trading, risk, and liquidity issues using systems engineering methods
• Transform uncertain human behaviors into verifiable protocol-level execution logic

From Platform Logic to Execution Infrastructure

In PlanX's architecture:

• Execution is not a UI layer experience issue, but a protocol layer determinism issue
• Risk control is not about parameter tuning, but state machine and constraint design
• AI is not a gimmick, but an automated extension of the execution layer

This allows PlanX, from the very beginning, to build products from the perspective of Execution Infrastructure, rather than replicating existing DEX or trading platform models.

Xgent

In the overall system of PlanX, Xgent is not a single strategy model or trading tool, but a vertical intelligent execution layer oriented towards future financial forms.

Core Goal: Compete Against Institutional-Level AI

The core goal of Xgent is to provide retail traders and trading platforms with execution capabilities that can compete against institutional-level AI.

In the context of the gradual arrival of Web4.0, the main competitor in trading is no longer “humans,” but large-scale AI trading models deployed by institutions. Retail traders and small-to-medium platforms face challenges that have shifted towards execution speed, strategy composition capabilities, systematic risk control, and real-time responsiveness. Xgent is designed to address this generational asymmetry.

Natural Language → Strategy Agent Architecture Output

The long-term vision of Xgent is to make “natural language input → strategy agent architecture output” a foundational capability for traders, rather than an exclusive privilege for institutions.

Traders only need to express their goals, constraints, and risk preferences, Xgent can transform these into executable, verifiable, and long-term operational strategy systems. This does not replace human decision-making but amplifies human judgment and risk awareness, leaving execution and optimization to machines.

Compete Against Institutional AI Trading Models, Not Imitate

Xgent rejects black box models that are not explainable or verifiable, emphasizing open strategy expression, modular agent architecture, and assessable, evolvable execution intelligence.

When institutions rely on scaled AI, individuals can still obtain equivalent or superior execution capabilities through structured intelligence.

4. Phased Product Mechanism

In the current phase, PlanX adopts a fee model centered on execution fairness:

• 0 opening fees
• loss closure 0 fees
• dynamic fees charged only when profitable

This design aims to align platform incentives with user outcomes, allowing execution to return to value creation itself.

5. Completely Decentralized Execution Architecture

PlanX uses an architecture of off-chain matching, on-chain settlement, and non-custodial fund management:

• User assets are always custodied by smart contracts
• Execution prices can be verified on-chain
• The platform cannot intervene in the transaction results

All key states are auditable, ensuring execution transparency and trustworthiness.

6. Intelligent Staking Pool

PlanX introduces Intelligent Staking:

• Governed by vertical AI models
• Dynamically identify user-side Alpha and hedge risk exposure
• Achieve long-term, autonomous liquidity allocation

This mechanism is not a simple yield aggregation but allows AI to become the long-term manager of on-chain liquidity.

7. Conclusion

PlanX is not just another trading platform but is building a layer of on-chain intelligent execution infrastructure aimed at the future.

As execution begins to exceed human limits of time and energy, the financial system will also move towards a new civilizational stage.

PlanX

Execution Beyond Human

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