I work on enterprise AI systems, with an emphasis on architecture, agentic systems, and governance. My focus is on designing AI solutions that can grow, adapt, and remain reliable over time.

• Agentic Systems Architecture Designing multi-agent systems with clear responsibilities, control flows, and failure boundaries.

• AI Evaluation & Optimization Building evaluation layers that make agent behavior observable, comparable, and improvable.

• Enterprise AI Governance Translating governance frameworks (e.g. ISO 42001) into concrete architectural and operational decisions.

• Production Readiness Making AI systems deployable, auditable, and maintainable beyond the prototype stage.

This repository contains:

• architectural prototypes
• reference implementations
• experimental frameworks
• design notes and technical essays

Most projects are intentionally incomplete: they exist to explore design space, trade-offs, and constraints — not to be products.

I believe AI systems should be:

• engineered, not improvised
• governed, not just optimized
• understood, not mystified