AI Architect · Production agent systems

Systems that
think carefully
and ship cleanly.

I design and build AI systems and autonomous agents for teams that need reliability, not demos. Tool loops, multi-agent orchestration, and the integration patterns that turn model capability into software you can trust.

7+

Years shipping

15+

Systems in production

500K+

Users impacted

About

An architect who still writes the hard parts.

Blueprints that survive contact with production. Hands-on when it matters. Clear about tradeoffs either way.

How I work with clients

I translate business problems into technical blueprints: agent architectures, data flows, API contracts, and phased build plans with explicit tradeoffs.

Requirements discovery comes first, then deliberate architecture, then disciplined execution with AI-assisted engineering. Working systems, not just diagrams.

What I bring into a team

The same rigor, hands-on: design docs, model and infrastructure decisions, and shipping. I specialize in tool loops, multi-agent orchestration, model selection, and the integration patterns that make LLMs reliable software.

  • Architected and shipped agentic systems: Oak and Annie ACS
  • Enterprise AI deployed to production for clients across healthcare, finance, and recruiting
  • 3 iOS applications published to the App Store
  • Co-founded a game studio whose first title passed 500,000 downloads
7+

Years experience

15+

Systems shipped

500K+

Users impacted

System

Anatomy of an agent system

How I decide, then the seven layers I design before a demo. Each layer is grounded in Oak or Annie ACS.

How I decide

  • An agent only where a workflow can't. Deterministic code is cheaper, faster, and testable; agents have to earn their place.
  • Multi-agent only when isolation pays. Splitting context costs coordination, and the split has to buy more than it costs.
  • The smallest model that passes the evals. Model choice is an eval result, not a brand preference.
  • The harness before the feature. Evals and traces come first, so every change after is measurable.

Cross-section of a production agent system

Layer 01

Orchestration

The control flow above the model: plain workflow, single agent, or multiple agents with scoped context. Handoffs, retries, and stop conditions are designed, not emergent.

Control flowHandoffsStop conditions

In practice

Annie ACS

Patient path is route, retrieve, respond, not a free-form free-for-all. Insights is a second, scoped agent for staff.

See the same layers in shipped systems.

Selected work

Case studies with the architecture left in.

Flagship systems up front. Everything else as a clean index. Outcomes and decisions, not marketing copy.

13 projects

More work

Nibble AILogoForgeFamilyCartYosihealthSuit BreakLaboratory Information Management SystemDMEPOS Order Management SystemAI-Powered Expense Validation & AuditingAI Resume ParserParaverseAgent RED

Capabilities

Where depth lives.

Not a laundry list of tools. The competencies that show up when systems have to work under real constraints.

01Requirements Discovery02Technical Solution Design03Production Delivery04Cross-functional Leadership05Stakeholder Communication06AI-assisted Engineering

Contact

Let's build something that holds up in production.

Open to architecture engagements, full-time roles, and conversations about agentic systems that need to be reliable.

Email me