Business Systems Design & AI-Native Operations
Most transformation fails because it layers new tools onto old structures. I start with the harder question: if you were designing this business today, how would it actually work? Then I build that.
About
"Don't fix the process. Rethink whether it should exist at all."
I'm a business systems designer and program leader with 8+ years of experience building operating models, decision frameworks, and organizational architecture across enterprise software, medical devices, and operations-heavy industries.
My foundation in industrial and systems engineering trained me to see organizations the way an engineer sees a system: where work actually flows, where decisions get made (and where they stall), what's generating friction, and what would need to be true for things to work differently. That lens doesn't change depending on the industry — the physics of how organizations work are surprisingly consistent.
What's changed is what's now possible. AI isn't a productivity tool to bolt onto existing workflows — it's a design variable that changes what operating models can look like from day one. I'm interested in the organizations willing to start from that premise: not "how do we add AI?" but "how would we build this if we'd had AI all along?"
The result is businesses that are structurally faster, less dependent on heroics, and designed to improve as they scale — not slow down.
Expertise
Four disciplines that rarely sit in one person — and work best when they do.
I design operating models, decision architectures, and organizational structures from scratch — starting with what outcomes you need, then building backward to the systems that produce them reliably.
I build AI in as a design element from day one — not as a plugin added later. That means designing the data structures, decision rights, and human workflows that make AI genuinely useful, not just present.
An engineering-trained eye for flow, constraints, variation, and human factors gives me a rigorous foundation for diagnosing why organizations behave the way they do — and what to change.
I translate between strategy, engineering, operations, and leadership — and I've built the alignment infrastructure (OKRs, decision frameworks, operating rhythms) that keeps complex organizations moving.
Leadership Style
I lead humbly — as a team member, not above the team. I don't walk in with all the answers, and I don't pretend to. My job is to create the conditions for the people around me to do their best work and lead in their own right.
I build trust by being consistent, transparent, and genuinely invested in the growth of the people I work with. I believe that trust earns you the ability to have the honest conversations that actually move things forward.
I give direct feedback early and often — and I expect it in return. Ambiguity is rarely kind. The clearer we are with each other, the faster we grow together.
I don't have all the answers, and I'm not trying to. I grow alongside the people I work with — learning from them as much as I contribute to them.
I build environments where people have the confidence and room to lead in their own areas. My goal is to be needed less over time, not more.
I give honest feedback early and expect it in return. Clarity is a kindness — vague positivity helps no one grow.
When I hand something off, I hand it off fully — with the authority and accountability to match. That's how people grow, and how trust gets built.
I've navigated competing priorities, fast-moving organizations, and no-clear-answer situations. Ambiguity doesn't unsettle me — it's usually where the most interesting work is.
Selected Impact
My Approach to AI
When you design a business system today and leave AI out of the architecture, you're already building something you'll have to rebuild. The question isn't where to plug AI in — it's what becomes possible when you design with it from the start.
That means rethinking decision rights, data flows, human roles, and operating rhythms — not as an afterthought, but as the foundation. AI that's native to the system is a different category from AI that's bolted onto it.
Start from outcomes, not features. What decisions need to be made faster? What information is consistently missing or late? Design to solve those — AI will emerge from the right constraints.
Human judgment is still the architecture. The best AI-native systems don't remove humans — they put human expertise where it actually matters and offload everything else.
Messy data and ambiguous processes don't get better with AI. They get worse, faster. Structural clarity is the prerequisite, not the cleanup project.
Designing an AI-native system
This is the process I run. It produces operating models that are structurally different — not just faster versions of what existed before.
Experience
Designed and scaled operating frameworks across 50+ product teams at a global enterprise software company. Led a platform migration serving 110,000+ users. Built executive OKR and KPI infrastructure. Created intake, triage, and lifecycle systems from the ground up — including an intake model representing 40,000 customers that converted 3,000+ annual submissions into structured product decisions.
Redesigned 85,000 sq. ft. of lab operations from first principles — rethinking space allocation, workflow, and stakeholder alignment from the ground up. Applied industrial engineering methods to identify and eliminate structural waste, generating $7.5M in annual savings across 2,000 stakeholders.
Replaced a manual, error-prone quoting process with a purpose-built digital system — reducing time and errors by 80% and generating $5M in annual savings. Designed custom tooling and led business analysis across cross-functional teams to replace legacy systems with ones designed to work.
Project management, execution discipline, and operational coordination across complex multi-stakeholder environments. Built operational clarity and communication systems in a fast-moving, high-accountability context.
Tools & Methods
What I reach for when designing systems, leading organizations, and building with AI.
Thoughts
Articles in progress on system design, AI-native organizations, and rethinking how businesses operate.
What changes when AI is a design variable instead of a feature request — and how to build organizations that are structurally different, not just faster versions of what already exists.
How the engineering discipline of studying systems — flow, constraints, variation, human factors — applies directly to redesigning how organizations operate, not just their factories.
Most organizations don't have a strategy problem or a talent problem — they have a decision problem. Who decides what, with what information, at what speed, and who gets consulted versus who gets notified?
Process improvement assumes the process is basically right. Business system design asks a harder question: what would this look like if you built it today, with everything you know now?
Get in Touch
I'm interested in conversations about building AI-native organizations, business system design, rethinking how teams operate, and what becomes possible when you design from first principles.
Open to conversations on AI-native system design, business transformation, and organizational architecture.