I build things to run, not to babysit.
Production systems that operate without daily intervention. Observability that surfaces signal without asking for attention. Documentation that stays accurate because the workflow updates it automatically. The point of the methodology isn't the methodology. It's freedom from the systems you depend on.
That's what I think most operations leaders actually want, and almost nobody is selling it honestly.
How a two-person firm ships enterprise work.
Twenty-five years of enterprise infrastructure. National-scale operations under regulatory frameworks like NERC-CIP and PIPEDA. Sales engineering leadership. A 36-for-36 record on competitive proof-of-concept evaluations. Top-10 finish at the AWS Enterprise Agentic AI Hackathon as the only solo competitor in a field of teams.
That's the experience. Here's the operating model.
I don't write production code by hand. I run a multi-layer build system where no single AI tool gets to be both the author and the reviewer. Architecture and planning happen in one place. Execution happens in another. Adversarial code review happens in a third. A persistent vault holds the memory of every project so no session starts from scratch. Every change is documented, every decision is reversible, every fix is grounded in an investigation written down before code is touched.
The AI gives me programmatic speed. The 25 years of enterprise infrastructure gives me the judgment to keep the speed from producing garbage. The two together are why a two-person firm can credibly take on enterprise work.
Business Impact Lab
Business Impact Lab is the proof-of-concept methodology behind the 36-for-36 record at Cohesity, run as an engagement rather than sold as software. Traditional proof-of-concepts fail because they test features rather than business outcomes: stakeholders leave unconvinced, deals stall, and technical success never turns into a signature.
- Real-world scenario testing on production data and real use cases, not synthetic demos.
- Stakeholder alignment workshops, every decision-maker in the room, the value metrics documented.
- Success metrics written down before the evaluation starts, quantified for executives and finance.
It is delivered as the POC and Evaluation Frameworks engagement below.
Five ways I work with clients
Each one is a different commitment level and a different shape of outcome. Most clients start small and expand if the fit is right.
Strategic AI Assessments
- For
Executive teams making AI investment decisions in the next two quarters
- What it looks like
A clear, unhyped read on where AI fits in your operations. What it would cost to do well. What it would cost to skip. Delivered as a written report and a working session, not a slide deck that goes in a drawer.
- Time-shape
Four to six weeks, scoped at engagement start
POC and Evaluation Frameworks
- For
Vendors and resellers running enterprise sales motions, plus enterprise buyers running competitive evaluations
- What it looks like
I spent a decade designing POC programs that won competitive evaluations. Business Impact Lab is that methodology, and there is a version of it built with modern AI tooling that does not exist in the market yet. I can build it for you.
- Time-shape
Six to twelve weeks, depending on scope
Observability and Telemetry Platforms
- For
Operations leaders with messy data they can’t see clearly through off-the-shelf tools
- What it looks like
Custom dashboards. Programmatic data ingestion and processing. Real-time signal extraction from systems that weren’t designed to be observed. Most off-the-shelf tooling stops where the interesting questions start. I build past that line.
- Time-shape
Eight to sixteen weeks for the first production system
Production Software Builds
- For
Organizations that need real systems built, not prototypes
- What it looks like
AI-native where it matters, traditional where it doesn’t, compliance-aware from day one. Built to ship, run, and stay out of your way. Multi-phase delivery with documented architecture, audit trails, and a real handoff plan.
- Time-shape
Twelve to twenty-four weeks per phase, multi-phase engagements common
Fractional Chief AI Officer
- For
Executive teams that want senior AI leadership without making a full-time hire
- What it looks like
Strategy. Vendor selection. Architecture review. Internal capability building. The unglamorous operational work that makes AI initiatives actually land instead of stalling. I sit alongside your leadership team, not above it.
- Time-shape
Monthly retainer, typical engagements run six to twelve months
The deliverables are not hypothetical
A four-portal system of record, in production
Residents, administrators, federal oversight and lenders on one governed data layer, deployed per organisation so each owns its own stack. Canadian residency, built to OCAP and PIPEDA.
36 for 36
A perfect record on competitive proof-of-concept evaluations over four years at Cohesity. The methodology that produced that record is the same methodology I run now.
AWS Enterprise Agentic Hackathon
Top-10 finish in July 2025 as the only solo competitor in a field of teams. The first published artifact of the operating model that became Phi Intelligence.
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I'm holding capacity for a small number of engagements at a time. I'd rather have ten honest discovery calls than one premature pitch.
Vancouver, Canada