I design the architecture of AI conversation: the state machines, evaluation rubrics, prompt frameworks, and behavioral guardrails that make models coherent, safe, and genuinely useful. Trained in psychology. Grounded in a decade of operational leadership. Certified in AI product management to sharpen the strategic edge.
Designed a 12-phase conversational state machine with anti-loop and anti-dependency guardrails for a sensitive emotional wellness context. Authored evaluation rubrics scoring model behavior across safety, tone, and pacing dimensions.
Translated user and stakeholder requirements into conversation flows and AI task structures for a career guidance platform. Developed onboarding quality criteria, memory accuracy benchmarks, and interaction consistency standards.
Defined agent roles, interaction flows, and evaluation criteria for a coordinated multi-agent system serving entrepreneurs. Identified UX and logic gaps across agent outputs. Validated system behavior in a live keynote demo.
State machines, branching logic, anti-loop rules, and multi-turn flow design for complex, high-stakes AI interactions.
Structured rubrics, failure mode mapping, behavioral benchmarking, and reproducible feedback cycles grounded in UX research.
Authoring prompt frameworks that precisely control model tone, pacing, accuracy, and boundary adherence at scale.
Safety guardrails, dependency prevention, and quality thresholds for AI in emotionally sensitive and high-stakes domains.
Most AI systems do not break at the level of language. They break in the layer beneath it, where timing, restraint, and decision-making are defined. When to engage, how to pace an interaction, what to permit, and what to withhold are the forces that determine whether a system feels coherent or collapses under its own output. That is the layer I design for.
My approach is grounded in psychology and UX, which keeps the work anchored in how people actually think, feel, and respond. An operations background ensures that these systems are not only thoughtful, but durable and scalable in practice. With training in AI product management, I work across the full lifecycle, translating insight into systems that hold up from early research through to real-world deployment.
Before moving into AI and UX, I spent nearly a decade in operations roles across technology organizations. The most recent chapter was four years as Director and Manager of Business Operations at a global cybersecurity firm, where the company grew 250% across multiple countries and U.S. states. I worked closely with executive leadership on budgets, resource allocation, and compliance, led SOC II audits, built workforce analytics dashboards, and cut hiring time-to-fill by 30% through process redesign.
That experience gave me a ground-level understanding of how enterprise teams operate, where processes fail, and what it takes to build systems that hold up beyond a slide deck. It is the lens I bring to every AI project.
