I work with organizations undergoing platform modernization or enterprise AI adoption when ownership uncertainty, late-stage reversals, or cross-team coordination block execution.
I own architecture and technical direction, aligning systems, teams, and workflows to restore stability and make delivery predictable.
What I Do
- Make, and stand behind, hard technical decisions with organizational consequences
- Shape technical team structure as part of system design, including role definition and hiring guidance
- Translate between executive intent, product strategy, and engineering reality
- Own technical direction, architecture, and long-term system integrity
- Design and evolve platforms across frontend, backend, data, and infrastructure
- Lead AI integration as an architectural concern, including context, workflows, contracts, and system behavior.
- Establish shared UI infrastructure and adoption patterns across product surfaces
Where I'm Most Effective
- Founders or executives who need CTO-shaped leadership without a permanent hire
- Growth-stage companies building or rebuilding their core platform
- Organizations modernizing legacy systems or integrating acquisitions
- Teams adopting AI where architectural clarity, control, and confidence matter
Background Snapshot
- 15+ years across software engineering, system architecture, and technical leadership
- Experience spanning design systems, composable architectures, AI-integrated workflows, and enterprise platforms
- Comfortable operating at board, executive, and implementation levels
- Active writer and systems thinker with a parallel practice in AI prototyping and architectural research
Selected Projects
SouthLeft — DoXYZ Platform Modernization
Modernized a multi-stream platform initiative by introducing contract-driven, AI-assisted delivery workflows that teams could safely adopt under active delivery. Owned sequencing and cross-team alignment to keep execution stable while shared UI infrastructure was upgraded.
- Scope: Multi-stream modernization program with shared UI infrastructure as a core dependency
- Operating model: Contract-driven workflows, review boundaries, and quality gates for AI-assisted output
- Outcome: More predictable delivery, reduced rework during review, and sustained stability under real constraints
ASICS Digital — Global Commerce Transformation
Supported commerce and digital marketing transformation across five global regions, owning architectural direction and sequencing to keep release plans predictable during modernization. Remediated a misfit shared UI implementation architecture by establishing patterns and guardrails that returned the system to a maintainable path.
- Scope: Global commerce and digital marketing systems spanning five regions
- Operating model: Patterns, guardrails, and milestone sequencing that preserved system integrity while teams delivered
- Outcome: Fewer late-stage reversals and a stable, maintainable system under active modernization
OpenSesame — Shared UI Infrastructure & DesignOps Formation
Established shared UI infrastructure as a shippable experience platform spanning design and engineering, with clear interfaces and adoption patterns that enabled shipping rather than parallel effort. Built a DesignOps function to operationalize cadence, ownership, and decision paths so change could scale without fragmentation.
- Scope: Cross-discipline platform work spanning product surfaces and teams
- Operating model: Defined interfaces, adoption patterns, and decision paths that held up at scale
- Outcome: Clearer adoption, fewer late-stage exceptions, and reduced duplication through standardization
Prism / Stably / Radial Systems
Developed a unified system for deterministic orchestration and durable memory in AI-integrated workflows, treating workflow boundaries and evaluation as first-class concerns. Emphasizes contract-shaped execution, reviewability, and repeatable operating models for enterprise-scale transformation.
- Scope: Architecture and operating-model R&D for AI-integrated delivery systems
- Operating model: Contract-shaped workflows, explicit boundaries, and evaluation-driven quality gates
- Outcome: More reviewable, repeatable AI-assisted execution with reduced ambiguity and drift
Learn more about radial systems and radial thinking at
radialarchitecture.com.
Stably - an AI agent validation substrate and MCP server
Stably (GitHub).
Prism - a radial architecture sandbox
Prism (GitHub).
Selected Organizations
Technical & Architectural Assessment
If your organization needs an independent view of its current technical and organizational state, particularly during growth, platform transition, or AI adoption, I offer a focused assessment designed to clarify risks, constraints, and opportunities.
- Fixed fee: $10,000
- Duration: Up to 2 weeks
- Executive briefing and written findings
- Optional high-level directional recommendations
If you're wondering how to get started, an assessment is a great way to begin.