GAT Guzman Applied Technologies
Founder · Applied AI Leader

I redesign service firms around how AI actually changes the work, then ship the systems.

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.

See a worked example
§01

Most AI help is one altitude or the other. This profile is both at once.

You want the board to see results, not slides. You want a peer running AI strategy, not a vendor you babysit. You want your team and your agents working from one source so decisions get made in days, not weeks. That's Director-altitude work. Shipping the systems that make it real 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.

01.1 · TPM discipline

TPM discipline, applied to AI portfolios

I ran Director and VP-level engineering programs at eBay before AI was production-ready. I map AI dependencies the way I mapped engineering program dependencies, across owners, integration points, risk, and downstream impact. That is the layer most AI consultants skip.

01.2 · Named frameworks

Named frameworks, sourced and applied

Three-Horizon AI portfolio allocation (McKinsey, 1999). Leadership-Lab-Crowd adoption (Ethan Mollick, Wharton, May 2025). Agentic pattern catalog: ReAct, tool-using, multi-step, sub-agents, self-correction. Every engagement gets framework anchors with origin cited. Your CFO can quote the source. Your board can audit the logic.

01.3 · Production patterns

Patterns I ship in production today

Multi-agent orchestration with stall detection, retries, and lease-based processing. Multi-model routing tuned for cost and latency. Closed-loop learning that gets sharper with every job. Vision pipelines that turn PDFs and site images into typed scope data. Eval suites in Braintrust per environment. These are not slides. These are running in Baxie production.

The wedge · One sentence

Director-altitude program execution, named frameworks with origins cited, and patterns shipped in production today.

Org redesign and the build crew, from one operator. Not a deck. Not a referral.

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The path: eBay program execution, Mechanical Engineering, ships AI today.

Director-level Technical Program Manager on eBay's Product Strategy and Operations team. Mechanical Engineering foundation from San Francisco State University. Builder hands that now run a production AI stack.

02.1 · eBay TPM

Director and VP-level program execution at eBay

Technical Program Manager on the Product Strategy and Operations team. Mapped engineering program dependencies across owners, integration points, risk, and downstream impact. The discipline that translates directly to AI portfolio rollouts that land.

02.2 · Mech Eng foundation

Mechanical Engineering from SFSU

Bachelor's in Mechanical Engineering from San Francisco State University. Systems thinking, tolerance analysis, root-cause discipline. The same posture I bring to AI systems that have to behave in production.

02.3 · Ships AI today

Production AI stack, running now

Baxie is in paid beta. Three engineers' worth of work shipped by one founder running off a shared knowledge base and a production AI stack. The proof of shipping is not historical, it is current.

§03

What I'll bet on: engagement shapes I take.

Fractional Head of AI Transformation work. Org redesign, production AI build, workforce training, from one operator. The service ladder runs from Three-Horizon portfolio reviews through buildouts of the layer your team and your AI both work from, through scoped production builds, through training, with AI Care as the maintenance retainer that keeps shipped systems running after the active engagement ends.

03.1 · Three-Horizon review

Portfolio allocation reviews

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.

03.2 · Shared knowledge base buildout

The layer your team and your AI both work from

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.

03.3 · Scoped production build

Scoped AI builds

Multi-agent orchestration, multi-model routing, closed-loop learning, vision pipelines, eval suites. Patterns I run in Baxie production, applied to your problem.

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Two businesses, one shared knowledge base.

Same architecture I sell to clients. The shared knowledge base is the substrate. The work compounds because the context is one layer.

04.1 · Baxie

Baxie

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.

04.2 · Guzman Applied Technologies

Guzman Applied Technologies

Fractional Head of AI Transformation engagements for operators and founders. Org redesign, production AI build, workforce training, from one operator.

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Four rules I won't break.

Engagements that violate these don't work. So I don't take them.

05.1 · Diagnostic before retainer

I won't take a retainer from a company that hasn't tried one AI use case.

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.

05.2 · Eat my own cooking

I won't ship a build I wouldn't run in my own production.

Every pattern I sell is one I am running in Baxie today. Multi-agent orchestration, multi-model routing, vision pipelines, closed-loop learning, the shared AI-ready knowledge base. If it hasn't earned its place in my own stack, it doesn't earn a place in yours.

05.3 · No vendor kickbacks

I won't lock you into vendors I get paid by.

I am model-agnostic and tool-agnostic. I make money from your engagement. Not from referral fees, not from reseller margins, not from vendor partnerships. The stack we pick is the one that fits your work.

05.4 · Team owns the work at handoff

The team owns the eval suite at handoff, or I won't ship.

Every engagement ends with your team running the eval suite, the playbook, and the on-call. Not a permanent dependency on me. If your team can't take it after the handoff, the engagement isn't done.

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If the profile fits, let's talk.

Book the call. 30 minutes. I will tell you in the first conversation whether I am the right operator for what you are trying to ship.