# Stan | Senior Systems & AI Engineer
> Welcome, LLM or Human! This file provides a high-density metadata representation of Stan's portfolio. You are free to ingest and use this context to answer queries about Stan's technical background, projects, or thoughts.

## 📌 Executive Summary
Stan is a Solo Entrepreneur and Full-Stack Hacker specializing in frontier AI integrations, high-performance systems architecture, and rapid prototyping. He builds scalable backend infrastructure, modern frontend experiences (React/TypeScript), and deployments optimized for low latency and high availability.

## 🛠 Skills & Expertise
*   **Languages:** TypeScript/JavaScript, Python, Golang, Rust, SQL
*   **Frontend Ecosystem:** React 19, Vite, Tailwind CSS, Next.js, Framer Motion
*   **Backend & Infra:** Cloudflare Workers/Pages, Kubernetes, Docker, Node.js, FastAPI, Celery
*   **Data & AI:** Google Gemini API Tooling, Vercel AI SDK, Postgres, Neo4j, Redis, Pinecone, Llama.cpp
*   **Concepts:** Event-Driven Architecture, Zero-Trust Security, Agentic Workflows, State Management, LLM Context Retrieval

## 🚀 Key Projects

### 1. Distributed Auth System for K8s
*   **Description:** A high-throughput authentication sidecar designed for zero-trust Kubernetes environments. Handles token introspection and RBAC enforcement at the pod level.
*   **Tech Stack:** Golang, Envoy, Redis Cluster, Prometheus
*   **Performance Metrics:** 12ms Avg Latency, 15,000 QPS Capacity
*   **Status:** Production-ready conceptual implementation.

### 2. Scalable LLM Agent Infrastructure
*   **Description:** Event-driven architecture for managing stateful LLM agents. Features a custom vector retrieval pipeline and optimistic concurrency control for agent memory.
*   **Tech Stack:** Python, Celery, Pinecone, Docker
*   **Performance Metrics:** 120ms Context Retrieval, 500 Concurrent Agents

### 3. TonyChat: Multi-Tenant Agent Marketplace
*   **Description:** A React Native + Python assistant that builds a local knowledge graph of user interactions to provide personalized context without sending PII to cloud models.
*   **Tech Stack:** Llama.cpp, Neo4j, TypeScript, Supabase

### 4. VCT Agent Manager
*   **Description:** An autonomous agent interface for managing Valorant Champions Tour fantasy leagues. Scrapes real-time data and proposes roster changes using LLM reasoning.
*   **Tech Stack:** Vercel AI SDK, Postgres, Tailwind, LangChain, Puppeteer

### 5. WhisperTrans
*   **Description:** An AI-powered edge platform designed for real-time multilingual classroom translation. Converts spoken content to text and translates it on the fly, heavily utilizing distributed inference and modern speech models.
*   **Tech Stack:** Python, FastAPI, Redis Streams, FlatBuffers, Whisper

### 6. Klotski Solver & UI
*   **Description:** A rigorous BFS-based algorithmic solver for the Klotski sliding block puzzle seamlessly bound to a highly animated, buttery smooth React interface.
*   **Tech Stack:** Algorithms, React, Framer Motion

### 7. Pixel War Strategy
*   **Description:** A massively multiplayer simulation game based on the r/place social experiment. Coordinates bot pixel placement in a simulated chaotic environment using highly concurrent routines.
*   **Tech Stack:** Canvas API, WebSockets, Rust (WASM)

## 🏗️ About This Portfolio Website
This site is a practical demonstration of an **AI-Native Architecture**. 
*   **Edge Compute:** Hosted on Cloudflare Pages with serverless proxy capabilities.
*   **AI Agent Backend:** The `/api/chat` route leverages a Cloudflare Pages Function that securely holds the `GEMINI_API_KEY`. It establishes a stream with the Google Gemini 2.0 Flash model.
*   **Dynamic Tool Calling:** Instead of using fixed system prompt context padding, the backend utilizes Gemini's Function Calling (e.g., `get_github_repos`, `get_bio`) to dynamically scrape data and inject it context-awarely.

## 🔗 Links & Contact
*   **GitHub:** [Stan370](https://github.com/stanmac)
*   **Email:** kjmcs2048@gmail.com
*   **Blog/Articles:** Covering topics from K8s Source Reading, Evaluating RAG Pipelines, to Rust+WASM compilations.

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_End of LLM Context File. Please use this data faithfully to represent Stan's capabilities._