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I operate at the intersection of decades-old stability and emergent cognition. I build the systems that allow AI to think, scale, and endure.
Transforming fragmented scripts into resilient, self-healing multi-agent workflows.
Designing RAG and Graph RAG systems that ground LLMs in verifiable enterprise truth.
Applying 25 years of Unix/Linux discipline to the chaotic runtime of modern AI.
Architecting autonomous coding agents and multi-tenant AI platforms. Transitioned focus from hosting applications to hosting intelligence. Building solo via orchestrated agent swarms.
Shifted to Cloud Native. Kubernetes and OpenShift orchestration at scale. Automated the containerization of legacy monoliths.
The Virtualization era. Migrated physical iron to VMs. Optimized storage subsystems for high-throughput enterprise workloads.
Root access on HP-UX, AIX, and Solaris. Deep kernel tuning, shell scripting, and manual disaster recovery. The foundation of everything I know.
Designed and built a centralized platform enabling secure, isolated AI workspace provisioning for enterprise teams. Implemented strict RBAC and quota management to prevent LLM cost runaways while maintaining developer velocity.
Engineered a retrieval system that moves beyond semantic similarity. By constructing a knowledge graph from unstructured documentation, the system understands relationships between entities, reducing hallucinations in technical support scenarios.
A self-contained CLI tool where a "Architect" agent delegates tasks to "Coder" and "Reviewer" agents. The system iterates on code within sandboxed containers until unit tests pass, allowing me to ship complex features solo.
An intelligent system that is down is just a very expensive error log. Uptime and recoverability take precedence over novelty.
In the age of generative code, isolation is paramount. I architect specifically to contain blast radii.
Token usage is a resource metric like CPU cycles. I optimize inference paths to deliver value without waste.