Director-altitude org design paired with production AI build and workforce training, from one operator. Director-level Technical Program Manager at eBay before AI was production-ready. Founder of Baxie. Fractional Head of AI Transformation. Applied AI Leader. Not an advisor. Not an automation shop.
You want the board to see results, not slides. A peer running AI strategy, not a vendor you babysit. Your team and your agents working from one source so decisions land in days, not weeks. That's Director-altitude work. Shipping the systems is engineering work. Most fractional AI help in 2026 picks one. This profile compounds Director-altitude program execution at eBay, named frameworks with origins cited, and patterns shipped in production today.
Director and VP-level engineering programs at eBay before AI was production-ready. I map AI dependencies the way I mapped engineering programs: owners, integration points, risk, downstream impact. The layer most AI consultants skip.
Three-Horizon AI portfolio (McKinsey, 1999). Leadership-Lab-Crowd adoption (Ethan Mollick, Wharton, May 2025). Agentic pattern catalog: ReAct, tool-using, multi-step, sub-agents, self-correction. Origins cited so your CFO can quote the source and your board can audit the logic.
Multi-agent orchestration with stall detection, retries, lease-based processing. Multi-model routing tuned for cost and latency. Closed-loop learning that sharpens every job. Vision pipelines turning PDFs and site images into typed scope data. Eval suites in Braintrust per environment. Running in Baxie production.
Org redesign and the build crew, from one operator. Not a deck. Not a referral.
Director-level Technical Program Manager on eBay's Product Strategy and Operations team. Mechanical Engineering foundation from SFSU. Builder hands that now run a production AI stack.
Technical Program Manager on Product Strategy and Operations. Mapped engineering program dependencies across owners, integration points, risk, downstream impact. The discipline that translates directly to AI portfolio rollouts that land.
Bachelor's in Mechanical Engineering. Systems thinking, tolerance analysis, root-cause discipline. Same posture I bring to AI systems that have to behave in production.
Baxie in paid beta. Three engineers' worth of work shipped by one founder on a shared knowledge base and a production AI stack. The proof is current, not historical.
Fractional Head of AI Transformation work. Org redesign, production AI build, workforce training, from one operator. The service ladder runs from AI Portfolio Allocation Reviews through shared-knowledge-base buildouts, scoped production builds, training, and AI System Continuity as the maintenance retainer.
Three-Horizon AI portfolio allocation across H1 efficiency, H2 capability, H3 transformation. What to fund this quarter, what to kill, what your board needs to see.
AI-ready knowledge bases modeled on edwin-os. Versioned. Searchable. Both your team and your AI read from it. Sold as a scoped build, not a deck.
Multi-agent orchestration, multi-model routing, closed-loop learning, vision pipelines, eval suites. Patterns I run in Baxie production, applied to your problem.
Same architecture I sell to clients. The shared knowledge base is the substrate. The work compounds because the context is one layer.
AI-native Margin OS for residential general contractors. Paid beta. Three engineers' worth of work, shipped by one founder running off a shared knowledge base and a production AI stack.
Fractional Head of AI Transformation engagements for operators and founders. Org redesign, production AI build, workforce training, from one operator.
Engagements that violate these don't work. So I don't take them.
If you haven't shipped a pilot, the right work is the AI-Native Org Audit, not a 6-month retainer. The retainer pays off when there is real production behavior to redesign around. Otherwise we are designing in a vacuum.
Every pattern I sell is one I run in Baxie today. Multi-agent orchestration, multi-model routing, vision pipelines, closed-loop learning, the shared knowledge base. If it hasn't earned its place in my stack, it doesn't earn a place in yours.
Model-agnostic and tool-agnostic. I make money from your engagement. No referral fees, no reseller margins, no vendor partnerships. The stack we pick fits your work.
Every engagement ends with your team running the eval suite, playbook, and on-call. Not a permanent dependency. If your team can't take it after handoff, the engagement isn't done.
Book the call. 30 minutes. I'll tell you in the first conversation whether I'm the right operator for what you're trying to ship.