AI That Actually Thinks
Not Just Matches Patterns

What
I Build

I'm certified through Anthropic Academy—mastering API Fundamentals, Tool Use, and Real World Prompting. This means I build with Claude Sonnet 4.5's groundbreaking 1M token context window, processing entire codebases or dozens of research papers in a single request. My agentic workflows don't just retrieve information—they reason through complex problems the way humans do.

My neuroscience background isn't just for show. I apply actual cognitive science—working memory models from psychology labs, hippocampal-inspired retrieval patterns from brain research, prefrontal cortex reasoning mechanisms—directly into RAG architectures and multi-agent orchestration. The result? AI systems that mirror how biological intelligence actually works.

I stay on the cutting edge. Right now, I'm deploying Constitutional Classifiers from Anthropic's February 2025 research for jailbreak defense, implementing Collective Constitutional AI principles, and using the new computer use API in production. And here's the kicker: I've shipped 12+ AI products independently in 18 months. No team overhead, no bureaucracy—just fast iteration and complete technical ownership.

The best AI systems learn from billions of years of evolution

Technical
Expertise Areas

Most developers use Claude like a fancy autocomplete. I use it like a cognitive scientist uses a brain scanner. Certified through Anthropic Academy, I orchestrate Claude Sonnet 4.5 (1M context planning), Opus 4.1 (deep reasoning chains), and Haiku 4.5 (parallel execution)—not as isolated tools, but as a cognitive architecture where each model plays a specific role in the thinking process.

Here's what makes my approach different: I spent years studying how brains actually consolidate memories in the hippocampus, how attention mechanisms filter signal from noise in the visual cortex, how the prefrontal cortex manages working memory during complex reasoning. Now I build RAG systems that replicate these exact patterns. It's not metaphorical—it's architectural. My vector databases don't just store embeddings; they mirror biological memory consolidation patterns.

The technical stack? I work with LangGraph for multi-agent orchestration, Pinecone and Weaviate for production-scale vector search, and I'm deploying Anthropic's latest research before most people have finished reading the papers. Constitutional Classifiers for jailbreak defense (published February 2025), Collective Constitutional AI for alignment, computer use API for autonomous actions. Eighteen months, twelve shipped products, zero meetings about meetings. Just engineering.

Where neuroscience meets
Claude-powered automation.