I help groups turn scattered expertise into usable systems: training, onboarding, knowledge infrastructure, community intelligence, and AI-supported workflows. The recurring question in my work is not how much can be automated, but where the boundary should sit between human judgment and system support.
Currently Instructional Design Lead at ZKXP Innovation, where I support AI adoption, workflow scoping, and implementation readiness. Founder of Headwater, where I apply the same knowledge-systems methodology to community and audience intelligence. Architect of the Insight Engine, the technical proof behind my AI knowledge-systems work.
Currently exploring full-time roles where AI adoption, knowledge systems, and adult-learning practice need to live in the same person. Open to remote, hybrid, or Vancouver-based positions. Selective fractional and project work continues through ZKXP and Headwater.
Leads instructional design and AI adoption at a systems engineering firm modernizing technology for regulated professions and mid-market clients.
Productized community intelligence for educators and enterprise. Complete-population analysis at the individual commenter level.
Twenty-one months of self-funded R&D. Production-oriented KG-RAG prototype over Neo4j and pgvector with citation tracking preserved across multi-hop reasoning.
Five stages, methods that compound. Click any to expand.
Asynchronous, self-regulated STEM courses across three districts. Mentored 30+ teachers transitioning to remote during COVID.
What it taught meWhen information is well-organized and on demand, human capacity can focus on coaching and problem-solving rather than content delivery.
Two roles across two undergraduate-development departments during organizational restructuring. Learning ecosystems for 6,000–8,000 students annually. Led Jump Start Leader Training (330 staff). Authored Cultivating the Future, a 12-chapter leadership development framework.
What it taught meThrough roughly 80% departmental turnover, I became the institutional knowledge broker. That experience is what motivated the Insight Engine.
Dual retrieval combining graph-neighborhood traversal with global vector search. Tiered LLM routing for cost efficiency. Evaluation harness using published multi-hop QA benchmarks.
What it taught meHow to architect production AI systems end to end, and where capable models reward complexity versus where they don’t.
Commercialized the Insight Engine’s infrastructure for community intelligence. Two tracks: a Creator Program for educators and creators, and Brands & Studios for enterprise. Methodology designed against documented failure modes of commercial sentiment tools.
What it taught meWhere the framework gets commercial validation. The handoff between technical infrastructure and a delivered service is its own design problem.
Leads instructional design and AI adoption at a systems engineering firm. The lessons from the Insight Engine, the commercial discipline from Headwater, and the adult-learning practice from UBC, all directed at one specific problem.
What it taught meMost AI initiatives stall at the human layer, not the technical one. Closing that gap is the work.
Most practitioners build only one side. The gap between them is the asset.
Documents, captured expertise, institutional knowledge, contracts, procedures. The artifact record of what an organization actually knows.
Public conversation, expressed demand, narrative dynamics. How a market or community is forming consensus about your work in real time.
Holding both sides, and naming the gap, is where opportunity, risk, and communication challenges actually live.
Technology earns its place by handling the repetitive and rote, so that judgment, relationship, and the work of building shared understanding stay human.
Communities of education, mentorship, peer connection, and challenging experience build what AI cannot automate. As more knowledge work shifts to systems, these stop being the supplement and become the curriculum.
Knowledge aids embedded in real work beat front-loaded curriculum. Problem orientation, just-in-time access, and meaningful challenge are the conditions for development, even when they’re not what learners say they want.
Technical choices follow from understanding what’s needed. The reverse rarely produces durable systems.
If anything above warrants going deeper, this is where to start.
The full long-form on the question under everything: where information access actually matters in human development, where it doesn’t, and why most organizations confuse the two. Grounded in 70-20-10 and adult-learning practice.
A production-oriented KG-RAG prototype for messy organizational and community data. Hybrid Graph + RAG over Neo4j and pgvector, Schema-on-Edge knowledge graph, citation-grounded answer synthesis. The technical white paper, with architectural decision log.
Leadership development as ecosystem rather than curriculum. A 12-chapter framework arguing leadership is emergent, not taught. Organized around five pillars and grounded in the Social Change Model and 70-20-10. Validated through benchmarking against fifteen peer institutions.
Including the 200K-subscriber Headwater engagement (30,000+ comments from 17,000+ unique participants, 200 dormant advocates surfaced); the UBC Imagine Day project sponsorship; and selected design artifacts from the Insight Engine build.
Primarily exploring full-time in-house roles where AI adoption, knowledge systems, and adult-learning practice need to live in the same person. Selective fractional and project work continues through ZKXP and Headwater alongside the search.
For general conversations, role inquiries, or ambiguous projects, write me directly at samcfath@gmail.com.
For roles where AI adoption, knowledge systems, and adult-learning practice need to live in the same person. The combination of production AI architecture, technical translation, and adult-learning depth is the differentiator.
Currently exploring titles like AI Adoption Lead · AI Enablement Manager · Director of AI Programs · Customer Education Lead · Senior Learning Strategist with AI focus · Head of AI Transformation
Project work routes through ZKXP Innovation, where the engineering, data, and AI capacity I draw on actually lives.
zkxp.xyz →Audience and community analysis routes through Headwater on a selective-engagement basis only. A Creator Program for educators and online creators; Brands & Studios for enterprise.
headwater.cc →