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Achievement: Pull Sharkx3Achievement: Pair Extraordinairex3Achievement: YOLOAchievement: Quickdraw

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PatrickFanella/README.md

Patrick Fanella

Full-stack engineer building AI agent platforms, GPU transcription pipelines, 3D graph visualization tools, and on-chain provenance systems — production software across Go, React, Python, and TypeScript, from first commit to monitored deployment.

What I build: Multi-agent AI systems, real-time collaborative platforms, search infrastructure, and developer tooling. The interesting problems live where systems meet — search pipelines feeding frontends, AI agents coordinating through WebSockets, smart contracts verified by browser extensions.

Core stack: Go · React · TypeScript · PostgreSQL · Python · Docker · Kubernetes

Open to: Software Engineer, Full-Stack Engineer, Backend Engineer, Product Engineer

📍 Chicago, IL · patrickfanella.co · patrick@subcult.tv

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  1. clpr clpr Public

    A modern Twitch clip curation platform that allows users to discover, organize, and share their favorite Twitch clips with the community.

    Go 1

  2. subcorp subcorp Public

    Self-hosted multi-agent system — 6 AI agents with native tool execution, autonomous workflows, roundtable conversations, and semantic memory. Next.js 16 · PostgreSQL + pgvector · OpenRouter.

    TypeScript 1

  3. subcults subcults Public

    Subcult connects underground and local music communities by mapping scenes, events, and live audio sessions while preserving autonomy, privacy, and creative identity.

    Go 1

  4. clustr clustr Public

    A full-stack application for collecting, analyzing, and visualizing Reddit communities and their user interactions as network graphs.

    TypeScript 1

  5. transcript-create transcript-create Public

    Create searchable, exportable transcripts from YouTube videos or channels. The stack includes a FastAPI backend, PostgreSQL queue/store, a GPU-accelerated Whisper worker (ROCm or CUDA), optional py…

    Python 1

  6. augr augr Public

    Autonomous multi-agent trading system in Go with LLM-powered analysis, debate, and execution pipelines

    Go 2