I focus on agentic AI systems that work in production, not just demos. This means building architectures that handle failure gracefully, evaluation frameworks that catch edge cases, and guardrails that prevent costly mistakes.
I am interested in reusable solution patterns with opinionated accelerators that scale across use cases and teams. Most of my time is spent at the intersection of enterprise requirements and what's actually possible with current AI capabilities.
Architectures, evaluation, failure modes, and guardrails.
Opinionated accelerators that scale across use cases.
PoCs, adoption playbooks, and technical deal strategy.