Hello, I am Huanfu Li

I believe software is the architecture of the 21st century. Our future social systems—from public services to financial compliance—will be built on code. However, we currently build this critical infrastructure using 'manual workshop' methods.

This bottleneck doesn't just slow innovation; it makes building the transparent, fair, and efficient systems we need to replace outdated bureaucracies almost impossible. My goal as a Responsible Systems Architect is to build the next generation of AI Governance Systems.

But this vision faces a critical barrier: Trustworthiness. How can we verify that a system managing millions of lines of code is fair, secure, and aligned with human rules?

My mission is twofold: First, to develop the foundation: an 'AI for Code' platform that acts as an 'AI Auditor.' This isn't just about speed; it's about Trust-by-Design. By leveraging Formal Verification, this AI will automatically validate that code is secure, reliable, and compliant with ethical rules before it's deployed.

Second, to apply this foundation to build Reliable & Human-Centered AI systems that can accurately translate human policies (like law or regulations) into auditable, executable logic.

I am convinced that without a robust platform to prove their reliability, such complex systems should not be built at all—they would be too complex to manage and too opaque to trust.

This vision now appears across my recent systems: PolicyLab and IdealWorld explore auditable policy and economic simulations, OpenAgenticVTuber explores inspectable human-agent delegation, Trellis focuses on privacy-preserving learning, and MR.Pilipala adapts real services to constrained emerging hardware.