I design, build, and maintain production-grade AI agents and RAG systems that are secure, reliable, and safe to run in real workflows.
No demos. No hype. Just systems that still work six months later.
"AI systems don’t fail at the model level. They fail when they meet real data, real workflows, and real humans."
Trained to think in risk, verification, and downstream consequences. I treat hallucinations, data leaks, and silent failure as design flaws.
Strategy informed by real constraints: cost, risk, maintenance, and trust. If it doesn’t survive production, it doesn’t ship.
Rapidly prototype agentic workflows and RAG systems to test architecture before scaling.
Design → build → harden → maintain. I stay responsible after launch, not just until demo day.
Multiple surfaces. One responsibility: Production reliability.
A practical knowledge base for building production-grade AI agents and RAG systems.
Focusing on architecture, guardrails, and real-world failure patterns.
Hands-on advisory and implementation for SMBs deploying AI systems that must be secure, reliable, and safe to operate.
A systems-level analysis of why legacy workflows fail when AI moves from assistive tools to agentic execution.
A practical guide for clinicians using AI safely, without compromising judgment, ethics, or compliance.
A systems perspective on workforce design, trust, and AI-native operating models.
Building the future of patient data and clinical safety workflows.
Visual storytelling explaining complex AI concepts for the masses.
Thought leadership and community building.
Designing agentic systems that can plan, act, verify outcomes, and escalate safely when needed.
RAG systems built with permissioning, grounding, and auditability — not guess-and-respond pipelines.
Security-first AI deployments for sensitive data, with clear boundaries and human accountability.
Selective use of multimodal AI where it supports core systems — not as standalone novelty.
Rapid prototyping to validate system design before committing to production builds.
⚠️ AI systems that worked in demos but failed in real use
⚠️ RAG systems nobody trusts
⚠️ Agents that act without guardrails
⚠️ Automation that quietly breaks workflows