Where theory meets execution.
Currently based in Taiwan, I work with local inference and agentic tools as well as cloud AI infrastructure like Google Vertex AI. I have built out Linux-based NVIDIA multi-GPU workstations and work with the Apple MLX layer in addition to traditional software design and development for practical applications. This hands-on work keeps my advisory grounded in reality, not whitepapers.
Modular LLM Engine. A self-improving automation layer where I test multi-agent orchestration, vector databases, and dynamic code generation workflows in real-time.
Custom LMS Platforms. Proprietary spaces where I experiment with human engagement optimization, cognitive retention, and UX architectures across domains like industrial training, compliance, and education.
Aggregate Web Apps. High-traffic consumer tools built specifically to stress-test real-time API latency, model drift, and cost-efficiency at scale across global networks.
Deep Tech Moonshot. Building the data pipelines and AI models required to analyze, halt, and reverse spinal bone fusion and autoimmune inflammation (specifically Ankylosing Spondylitis).
Enterprise Sandbox. A dedicated environment for testing complex, multi-step agentic workflows that interact with legacy enterprise systems without causing disruption.
I leverage this internal R&D lab to build out functional proof-of-concepts for my advisory clients. If you need to stress-test a concept before committing heavy engineering resources, let's talk.
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