I design governed, AI-augmented systems with explicit lifecycles, authority boundaries, and traceability.
My background spans over two decades in regulated environments, including pharmaceutical engineering, commissioning, qualification and validation (CQV), and large-scale project delivery. I bring that discipline to human–AI interaction and workflow design.
- AI-augmented workflow architecture
- Lifecycle-driven system design and deterministic interaction logic
- Governance, rules, and human approval boundaries
- Structured knowledge and controlled outputs
- VALOR_LEGACY: A visual history of ten attempts to make AI-assisted CQV work more structured and traceable, from instruction packs and architecture to workflow engines and narrower experiments. It records incomplete work, changing goals, and lessons learned. Published for display and reference, with no open reuse license.
- VALOR_ASCENDENT: A software project for commissioning, qualification and validation (CQV) planning, coordination and equipment User Requirements Specification (URS) preparation. Work in progress.
- Governance before capability
- Explicit states over implicit assumptions
- Boundaries are features
- Determinism where it matters
- Human authority is never delegated silently
I’m expanding my architectural practice into domain-agnostic AI systems that support decision-making, execution, and learning while preserving human control and accountability.
The projects above cover architecture, implementation, and supporting assets at different stages. Each project has its own scope and status.