Union Platform 01 Open For Boarding

I make AI systems easier to ship, operate, and understand.

I work on model-serving infrastructure, developer tooling, and technical writing that helps teams move from prototype to production.

Current Route

What I work on

Status

Shipping

Primary Work

Serving models, building tooling, and turning implementation details into usable docs.

Systems

Triton, vLLM, Ollama, TensorRT, and LLM product workflows.

Output

Projects, explainers, and technical notes built to be inspected and reused.

Focus

Production AI

Strength

Clear Interfaces

Approach

Hands-On

Production Inference Developer Tooling Frontend Explainers
Current Line Operating Notes

Work across inference, interfaces, and technical communication.

The focus is practical AI engineering with enough product and frontend discipline to make the systems useful, observable, and understandable.

Open Route

Inference Systems

Serving, tuning, and simplifying model workflows so product teams can run AI features without guesswork.

Open Route

Interactive Interfaces

Building frontends and explainers that make technical systems easier to inspect and use.

Open Route

Technical Writing

Turning experiments into notes, tutorials, and implementation guides that other engineers can reuse.

Journal Board Latest Dispatches

Recent writing on machine learning, engineering, and experiments in progress.

See All Posts
Freight Yard Projects In Motion

Selected projects across machine learning, visualization, tooling, and product experiments.

    01
    Freight Ticket
    Race Car RL Agent
    PythonReinforcement LearningOpenAI GymPyTorch

    Developed a Deep Q-Learning agent in a simulated racing environment to autonomously navigate tracks by learning from reward feedback.

    02
    Freight Ticket
    Garbage Classification with CNN
    PythonComputer VisionEfficientNetTensorFlow

    Transfer-learned an EfficientNet backbone to classify multiple waste categories in images, enhancing model performance through data augmentation.

    03
    Freight Ticket
    Haiku Generator
    LLMsPrompt EngineeringNLPReact

    Explored prompt-engineering strategies with large language models to generate structured haikus, enforcing syllable constraints and thematic coherence.

    04
    Freight Ticket
    D3.js Reference Tutorial
    JavaScriptD3.jsData VisualizationHTML/CSS

    Interactive web guide demonstrating core D3.js features and visualization techniques.

    05
    Freight Ticket
    Chat App
    ElmNode.jsExpress.jsWebSockets

    Real-time chat app with WebSocket messaging; Elm frontend and Express.js backend.

    06
    Freight Ticket
    Twitch Python Discord Bot
    PythonDiscord.pyTwitch API

    Python Discord bot with Twitch API integration for live stream alerts and moderation.

    07
    Freight Ticket
    Rust Tauri App
    RustTauriDesktop App

    Cross-platform desktop color picker built with Rust and Tauri, showcasing native UI integration.

    08
    Freight Ticket
    Guided Sudoku Solver
    AlgorithmsBacktracking

    Interactive Sudoku solver with step-by-step guidance built in Python using a backtracking algorithm and heuristic improvements.

    09
    Freight Ticket
    Wordle Solver
    TypescriptEntropyTanStack Start

    Interactive wordle solver using entropy with a practice mode for improvements.

    10
    Freight Ticket
    Interval Timer
    TypescriptProductivityTanStack Start

    Interval Pomodoro timer for Work/Study Sessions.

Long Haul Learning Route
Active Route

The roadmap tracks topics worth studying deeply enough to turn into usable systems, notes, or experiments.

Current learning route across reinforcement learning, performance engineering, graph systems, and agents.

  1. Stop 01
    In Progress

    Applied Reinforcement Learning

    Reading

    Reinforcement Learning (Sutton & Barto), Deep Learning (Goodfellow et al.)

    Building With

    MarkdownPythonObsidianPyTorchNumPy

    Exploring

    RL algorithms • Policy gradients

  2. Stop 02
    In Progress

    High-Performance Systems

    Building With

    CUDAPolarsTritonParallelizationTensorRT

    Exploring

    Distributed systems • GPU acceleration

    Operating Principles

    • Prototype fast in Python, then optimize the critical path deliberately.
    • Use hardware acceleration where latency matters enough to justify complexity.
    • Keep operational visibility alongside performance work.
  3. Stop 03
    In Progress

    Graph Intelligence

    Reading

    Graph Representation Learning (Hamilton)

    Building With

    PyTorch GeometricNeo4jNetworkXC++

    Exploring

    Knowledge graphs • GNNs

  4. Stop 04
    In Progress

    Autonomous Agents

    Reading

    Generative Agents (Park et al.)

    Building With

    LangChainOpenAI APIAutoGPTFastAPI

    Exploring

    Multi-agent systems • Emergent behavior

Signal Box Inspiration Sources