Philosophy & Career Arc
My approach: externalize procedural knowledge into AI-powered performance support, freeing human capacity for mentorship, reflection, and complex skill development the things that actually matter.
Information that can be externalized into a "knowledge aid" should be.
True human development happens through community, mentorship, reflection, and experiential learning not information transmission. By leveraging AI to handle procedural knowledge, we prioritize valuable human interaction for application, coaching, and complex skill development.
LLMs are the ultimate knowledge aid but generic AI defaults to the "wisdom of crowds." To preserve competitive advantage and institutional expertise, AI must maintain fidelity to organizational knowledge.
This is what the AI Insight Engine demonstrates: constraining LLMs to verified organizational content through advanced RAG, ensuring answers are grounded in your hard-won tacit knowledge complete with citations and verification trails.
Specialized in asynchronous learning architecture, designing 12-19 STEM courses for self-directed consumption. Managed 150-300+ concurrent learners, achieving 85% completion rates.
Key insight: When information is organized well, learners can access it on-demand freeing coaching time for application and problem-solving.
Designed scalable learning ecosystems (10,000+ participants) integrating community, mentorship, and experiential learning. Pioneered blended programs reducing in-person time 60% through knowledge externalization.
Key insight: Systems that prioritize experiential learning over information transmission achieve better outcomes with less resource intensity.
During 80% departmental turnover, became the "human search engine" synthesizing 500+ fragmented documents into actionable aids. Enabled rapid onboarding for 350 new staff while maintaining programs for 10,000+ participants.
Piloted LLM-assisted synthesis workflows, establishing ad-hoc knowledge bases from historical reports. This proved AI's potential as a knowledge aid but also revealed the fidelity problem.
Key insight: Generic AI gives crowd-sourced answers. Organizations need AI that maintains fidelity to their specific, hard-won expertise.
Developed the AI Insight Engine: advanced KG-RAG system that automatically generates Knowledge Graphs from unstructured documents, then provides answers grounded in organizational expertise with citations and verification trails.
Current focus: Bridging human-centered development strategy with AI systems that preserve institutional memory, accelerate onboarding, and enable organizational resilience.