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Founder · Applied AI leader

Edwin Guzman. I own AI programs.

I map how the work actually moves, then I ship the systems that change it. Technical Program Manager at eBay operating at director-plus scope, reporting to a VP of Engineering. Founder of baxie, an AI-native construction SaaS in beta.

Edwin Guzman, founder of Guzman Applied Technologies
Edwin Guzman · Founder, GAT
01 · The operator

Program layer.Build hands.

  • Ex-eBay TPM, director-plus scope
  • Mechanical Engineering, SFSU
  • Founder of baxie, in beta

Ex-eBay TPM.
Founder of baxie.
20 to 200 people.

At eBay I was a Technical Program Manager operating at director-plus scope, reporting to a VP of Engineering. My peers were directors and engineering managers across Core Product and Core Technology. My day job was getting them to agree on trade-offs and then holding the plan together while it shipped.

Someone has to own the AI program. I worked that layer at eBay, and I ship the systems myself. Setting direction is one job and shipping against it is another. Strategy firms tend to do the first and subcontract the second. That handoff is exactly where the work goes unmapped and stalls.

  • I map AI work the way I mapped engineering programs. Owners, handoffs, risk, and what breaks downstream when one piece moves. It is the layer AI consultants usually skip, because they have not run a program.
  • I use named frameworks and I cite where they came from. McKinsey's Three-Horizon model for portfolio allocation. Ethan Mollick's Leadership, Lab, and Crowd for adoption. Your CFO can check the source and your board can audit the logic.
  • I ship production AI today. The patterns I sell are running in baxie right now, with a public write-up of what it cannot do yet.
02 · The path

How I gotto this work.

GAT.

eBay · Program execution

Technical Program Manager

Director-plus scope, reporting to a VP of Engineering. I aligned directors and engineering managers across Core Product and Core Technology on trade-offs, dependencies, and sequencing. The same map an AI portfolio needs.

GAT.

Engineering foundation

Mechanical Engineering

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

GAT.

Ships AI today

Founder of baxie

An AI-native construction SaaS for residential general contractors, in beta. A full production app shipped by one founder, running off a shared knowledge base and a production AI stack. The proof is current.

03 · In production

What I runin baxie today.

These are the patterns I bring to a client build. Every one of them is running in my own product, so I have already paid for the mistakes.

  • Vision extraction behind a review gate. The model reads architectural plan sets. A person approves what it found before anything reaches an estimate, and the gate is enforced in the data layer.
  • Multi-model routing. Each task goes to the model that fits it on cost and latency, instead of one model for everything.
  • A deterministic verifier. Plain code checks the model's output and flags the outliers for review without overwriting them.
  • A closed scope catalog. The model picks from a fixed list, which stops it from inventing scope names.
  • A markup engine that throws. When the inputs make no sense it stops with an error, and it never returns a nonsense number.

This practice and baxie run on one shared knowledge base: the layer my team and my AI both read from. It is the same architecture I build for clients.

04 · The rules

Four rulesI won't break.

Engagements that break these do not work, so I do not take them.

  1. The plan comes first

    Every engagement starts with the AI Program Diagnostic. I will not quote a build or a retainer before I have mapped the work, and I will not take a retainer from a company that has not tried one AI use case yet.

  2. I run what I sell

    Every pattern I put in a client build is one I run in baxie. If I would not run it in my own production, I will not ship it into yours.

  3. No vendor money

    I am model-agnostic and tool-agnostic. I make money from your engagement and nothing else. No referral fees, no reseller margins, no vendor partnerships. The stack we pick fits your work.

  4. Your team owns it at handoff

    Every engagement ends with your team running the eval suite, the playbook, and the on-call. If your team cannot take it, the engagement is not done.

05 · Working with me

Three steps.In this order.

  1. 01

    The plan: AI Program Diagnostic

    Two weeks. A workflow map, a 90-day sequence with an owner, a baseline, and a build type on every line, and a kill list.

    Flat fee, paid before kickoff. Credited in full if you build or retain me within 30 days of the readout.

    $2,5002 weeks
  2. 02

    The build: Scoped AI Build

    The first lines of the plan, shipped into the stack your team already runs, and measured against the plan's baseline.

    From $7,500 a workflow, two-workflow minimum. Price fixed in writing at the readout.

    From $15kPer build
  3. 03

    Keep me on, monthly

    AI System Continuity keeps what shipped running. The Fractional Head of AI Transformation owns the program and the next builds.

    Continuity is 2 to 3 days a month. Fractional is 1 to 3 days a week, 6-month minimum.

    From $12kA month, Fractional
GAT.

If the profile fits, talk to me.

30 minVirtual call

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

Book 30 minutes with Edwin

Not ready to talk? Score your AI program first. Twelve questions, about four minutes, scored breakdown by email.