About
I’ve spent twenty years inside the machinery of higher education compliance. I know exactly what happens when policy meets a system that wasn’t built for it, and that’s the same gap I now study in AI.
01 – Background
I’m the Director of Financial Aid at Lemoore College, in California’s Central Valley. For 20 years, my job has lived at the intersection of state and federal regulations, institutional capacity, and student need… three things that rarely move at the same speed. Title IV compliance doesn’t leave room for theoretical answers; every interpretation has to survive an audit, every process has to work for the student in front of you, not the student the policy assumed.
That’s the lens I’ve started turning on AI. Not “can this model do the task,” but “what happens when this tool meets a real institution,” and that institution’s incentives, constraints, and people who are skeptical for good reason. I hold an Ed.D., and my dissertation research (logistic regression across 7,729 community college students) found that one of the state’s own mandated interventions had a null-to-negative effect on the outcome it was supposed to improve. That finding has shaped how I evaluate every technical rollout I’ve touched since: mandates and good intentions don’t guarantee impact. Implementation is where the truth comes out.
I’ve since built and led AI tools inside my own institution: a retrieval-grounded compliance assistant, an audit-defensible documentation workflow, and a cross-functional AI work group bridging staff who’ve never touched these tools with the few who already have. I’m looking for the next place where that same combination of regulatory depth, technical fluency, and an instinct for where implementation actually breaks, is useful.
02 – What’s Different
There’s a specific combination I bring that’s hard to find in one person:
Regulatory Depth
Twenty years inside state and federal compliance, not adjacent to it
Technical Fluency
Hands-on building, not just sponsoring or evaluating from a distance
Equity-Focused Context
Community college, Central Valley, the students furthest from ed-tech’s assumptions
Fast Domain Acquisition
Dissertation methodology, information systems, financial aid regulation, applied AI. Same diagnostic pace each time.
Most people pivoting into AI come from one of these. Few come in with all four already proven.
03 – Next
If you want to see what this looks like in practice (not theory) the projects are the place to start. Or if you’d rather just talk it through, reach out directly.