Two distinct worlds, one driven mindset. I manage high-stakes clinical environments by trade, and architect advanced systems using LLMs to solve the problems I see around me.
I am a Healthcare Operations Specialist driven by intense curiosity. My professional life is defined by the zero-error standards of the operating room. My creative life is defined by a drive to close gaps I see in my daily personal and professional life.
The Open- series is the result of that curiosity. I don't write code in the traditional sense—I leverage the very LLMs I integrate to build the applications themselves. I am the architect and the driver; the model is the engine. I build these tools to solve real problems, and I've found success by simply refusing to accept the status quo.
My background in high-stakes surgical environments instills a level of rigor and reliability that I demand from the systems I orchestrate.
Architecting complex workflows using LLMs, RAG, and Agents, bridging the gap between raw model capabilities and user needs.
Implementing on-device intelligence and secure storage patterns to ensure user data remains private and protected.
Shipping production-quality code quickly, with a focus on continuous improvement and adapting to the latest platform advancements.
The successor to my Assistants-era client, rebuilt as a multi-platform OpenAI Responses API playground with AppContainer dependency injection, SwiftUI, and MVVM managing 40+ streaming event types.
computer-use-preview with cancellable runs, reasoning traces, and per-conversation parameters.OpenAIService orchestrates 40+ Responses events, surfacing live token counts, tool execution cards, and status chips across iPhone, iPad, Mac (Catalyst), and visionOS.An advanced on-device RAG engine (RAGMLCore) spanning iOS, macOS, and visionOS with SemanticChunker, NLEmbedding, and hybrid retrieval fused through RRF + MMR, all wrapped in a consent-aware SwiftUI interface.
NLEmbedding.ContainerService, RAGService, HybridSearchService, and PersistentVectorDatabase coordinate ingestion, retrieval, and storage per isolated KnowledgeContainer.A shipped iOS knowledge base that ingests local documents, builds Pinecone serverless indexes, and streams GPT-5 answers backed by the OpenAI Responses API.
text-embedding-3 vectors before Pinecone upserts.The original Assistants API (v2) client that managed assistants, vector stores, and tool stacks before the Responses API shipped; now maintained as a legacy reference.
Leveraging LLMs to build tools. Since my first commit in late 2023, I've used Foundation Models to generate, refine, and ship complex native iOS applications. Driven by a passion for exploration, I orchestrate systems involving RAG, Agents, and on-device intelligence to close the gaps I see in existing software.
Sole technical specialist supporting Stanford surgical teams with complete autonomy. Bridging the gap between complex medical technology and clinical workflows in high-pressure surgical environments.
I'm always interested in new opportunities and collaborations, especially in iOS development and AI integration. Feel free to reach out if you'd like to discuss a project, explore potential partnerships, or just say hello!