The Short Version: I See What Is Stuck And I Build the Fix
Operations has been the throughline of my entire career, though probably not the version most people picture. This is the discipline that determines whether the rest of the organization functions the way it is supposed to.
For over nine years, I have been the person teams bring in when things are broken, messy, or held together by one exhausted human doing three jobs and documenting none of them. I walk in, I see what needs fixing, and I build the system. Agencies, startups, nonprofits, small businesses where the founder is still answering the general inbox at 9pm. The industries change. The loop does not.
These days, that work means AI operations: helping small teams figure out where AI actually helps, building the systems around it, and making sure the humans inside those systems have more room to do the work that matters.
How I Got Here
I ran my own agency for five years, where I served mission driven organizations, businesses where the budgets were tight, and the people cared deeply about doing it right. I built the entire service delivery infrastructure from scratch, coordinated across distributed teams on five continents, and learned exactly what it takes to build systems for teams that cannot afford to waste a single dollar or hour on something that does not work.
Before that and alongside it: medical scheduling, retail, account management, logistics, call centers, executive services. Every role taught me something different about how systems break and how people get caught in the wreckage when they do. A radiology clinic taught me CPT codes and patient compassion alongside scheduling. A call center taught me de-escalation under pressure and pattern recognition at scale, the kind where you notice the same wrong thing happening hundreds of times before anyone else sees it.
None of these were “AI jobs.” All of them are the reason my AI work is different from someone who came to this from a tech background. I do not design systems for ideal conditions. I design them for the Wednesday afternoon when two people called in sick, the report is due Friday, and the tool that was supposed to automate the intake process is spitting out nonsense because nobody set it up for how the team actually works.
Most recently, I built AI workflows, SOPs, and integrated data operations at ECP, where I designed how AI and humans work together on real data in real time. That work confirmed what I had been building toward for years: the intersection of operations expertise and AI implementation is where I belong, and the teams that need it most are the small ones.
What “Human-First” Means in Practice
“Human-first” gets used a lot in the AI space. Here is what it means when I say it.
I see systems before they are explained to me.
When I walk into an organization, I am not cataloging problems and then designing solutions in two separate steps. I see the architecture the system needs at the same time I see the mess. That is why my work moves fast: the assessment and the design happen simultaneously. Clients start describing their situation and I am already sketching the fix. Nine years of doing this across wildly different industries, from healthcare to creative agencies to five-person startups, is the reason.
I read capacity, not credentials.
Whether it is a team member, a tool, or an AI system, I assess what it can actually do right now and design around that reality; not the org chart version, not the “when we are fully staffed” version, but the one where your best person is also running the volunteer program and answering the general inbox because nobody else has time. Systems designed for ideal conditions fail on the first hard day. I design for the hard days from the start.
I absorb entire systems, not just my role within them.
I have never been able to learn within lanes. A scheduling job taught me radiology billing. A sales role taught me logistics. A paralegal spouse taught me regulatory language. This cross-domain pattern recognition is the reason I catch things other consultants miss; I am not applying one framework. I am drawing on a dozen industries worth of “I have seen this pattern before, and here is what actually works.”
I treat AI as a system to be designed around, not a button to press.
Most AI implementation starts with “what can this tool do?” I start with “what does this team need, and is AI the right way to get there?” Sometimes it is. Sometimes the team needs a better SOP before they need any technology at all. Either way, we get there together; the conversation is part of the process, and I am not in a rush to skip it.
A Few Things That Matter
Autism is not a footnote in my professional story. It is a significant part of why this work looks the way it does. The pattern recognition, the systems thinking, the ability to see architecture underneath chaos: none of that came from a certification. My brain has always worked this way, and the accommodation frameworks I build for clients started as frameworks I needed for myself. That is not a limitation. It is the reason the work is good.
I am based in Denver, originally from Arizona. I am a member of the Colorado Neurodiversity Chamber of Commerce. I care about accessibility, sustainable workflows, and building systems that do not require anyone to burn out to maintain them.
When I am not designing workflows, you will find me knee-deep in a fiber arts project (knitting, crochet, embroidery, whatever catches my hands next), tending my garden, or hanging out with my kids. My desk has a pastel keyboard and too many notebooks. I am that kind of organized.
Want to Work Together?
If your team has more operational friction than it should and you are ready to fix it, let’s start with a conversation about where things stand.