About Me
TL;DR
Most of my time goes into systems and protocols — currently Web3 infrastructure and smart contracts. I care less about shipping fast, and more about understanding why a system works the way it does.
My learning path spans philosophy, law, economics, and computer science. This was not the result of deliberate career planning, but a natural consequence of repeatedly asking foundational questions. That habit continues to shape how I design systems and write code.
If you're curious about how I think and what kind of environment I work best in, feel free to read on.
How I Think
Before listing skills, it's more accurate to describe how I approach problems. Skills can be learned; cognitive habits tend to persist. They determine what kinds of problems I'm drawn to and how I navigate complexity.
For readers interested in a more structured breakdown, I've shared a detailed cognitive profile here: principlesyou.com
Implication: I'm best suited for work that requires deep understanding and rethinking assumptions, rather than highly standardized or execution-driven tasks.
What Drives Me
Skills describe capability; motivation determines sustainability.
Skill Map
| Skill | Domain | Level |
|---|---|---|
| Solidity | DeFi / Security / Gas | Independent |
| Rust | Systems / Blockchain | Independent |
| System Design | Distributed Systems | Independent |
| Go | Backend / Tooling | Production |
| TypeScript | Full-stack / Types | Production |
| React / Next.js | Frontend | Production |
| PostgreSQL | Database Design | Production |
| Zig | Low-level Systems | Deepening |
| ZK Proofs | Cryptography / Circuits | Deepening |
Meta-skills: Rapidly identifying the essence of a system; designing abstract systems, protocols, and mechanisms from first principles; translating understanding into elegant, constrained structures.
Languages: Chinese (Native), English (Fluent).
Background
Education: East China University of Political Science and Law, B.A. in English (2017–2021). While not a technical major, this period involved extensive self-study across philosophy, law, economics, and computer science. It trained me to analyze arguments, surface hidden assumptions, and apply that mode of thinking to technical systems.
Avinasi Labs — Software Engineer (2025.03 – Present): Leading the design and implementation of DeLong Protocol, a decentralized encrypted data issuance protocol on Phala Network. Responsible for mechanism design, smart contracts, and TEE integration.
Proprietary Trading Firm — Quantitative Engineer (2022.09 – 2025.03): Worked on quantitative trading systems, focused on performance and high-concurrency scenarios.
LTP — Assistant Fund Manager (2021.07 – 2022.08): Fund operations and liquidity management. First systematic exposure to incentive structures in financial systems.
Work Environment Fit
This is a practical assessment, not a value judgment.
Good Fit: Work requiring deep thinking (protocols, system architecture, mechanism design); environments where assumptions can be questioned; small teams with high autonomy; cultures that value correctness and design integrity.
Poor Fit: Highly procedural, speed-first execution roles; rigid hierarchies where decisions are not open to discussion; environments dominated by internal politics or visibility games.
Problems I Keep Coming Back To
Incentive design and mechanism alignment; low-level systems (compilers, virtual machines, memory models); cryptographic primitives (zero-knowledge proofs, MPC); technology and institutions (how technical systems reshape power and trust); education innovation and the intersection of technology and learning.
Contact
If these questions resonate with you, feel free to reach out: wwwwwdemon@gmail.com