About

I'm a software engineer with interests spanning systems design, distributed architectures, and understanding how complex systems reach stability.

My work focuses on the intersection of practical engineering and theoretical foundations—building tools that help reason about equilibrium, convergence, and coherence in systems ranging from multi-agent AI to service meshes.

Current Focus

I'm exploring how equilibrium-based analysis can improve modern AI systems:

• Multi-agent orchestration with principled stopping criteria
• Adaptive RAG systems that know when to stop refining
• Prompt optimization with convergence detection
• Graph-based memory systems with temporal decay

Open Source

I maintain TaoCore, a systems-level abstraction layer for reasoning about stability and dynamics. It's designed to be domain-agnostic, descriptive rather than prescriptive, and built on fixed-point iteration rather than optimization.

Approach

I believe in:

• Simple over clever — Boring solutions that work beat elegant ones that don't
• Descriptive over prescriptive — Observe and analyze, don't force outcomes
• Equilibrium over optimization — Seek stability, not optima
• Explicit over implicit — Make behavior observable and inspectable

Contact

Find me on GitHub.