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.
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Agentic Systems Architecture Designing multi-agent systems with clear responsibilities, control flows, and failure boundaries.
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AI Evaluation & Optimization Building evaluation layers that make agent behavior observable, comparable, and improvable.
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Enterprise AI Governance Translating governance frameworks (e.g. ISO 42001) into concrete architectural and operational decisions.
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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