I am a Full-Stack Engineer and Open Source maintainer specializing in high-performance AI tooling, vector databases, and scalable backend infrastructure. As the creator of SimpleVecDB (a local-first vector database) and verifiable-thinking-mcp, I have deep experience building efficient, specialized systems that solve complex data problems without the bloat. What I Bring to Your Project: AI & Search Infrastructure: Expertise in semantic search, embeddings, and vector databases (SimpleVecDB, RAG pipelines). Automation & Tooling: Building custom MCP (Model Context Protocol) servers and developer tools that optimize workflows. Full-Stack Agility: Proficient in Python, Rust, and TypeScript, capable of shipping complete products from database to frontend. Performance-First Mindset: I build software that is lightweight, fast, and local-first by default. I don't just write code; I architect solutions that are easy to maintain and ready to scale. Whether you need a custom AI integration, a specialized database solution, or a robust backend API, I deliver clean, documented, and production-ready code. Check my GitHub (CoderDayton) to see my open-source contributions and coding standards.…

Dayton Dunbar

I am a Full-Stack Engineer and Open Source maintainer specializing in high-performance AI tooling, vector databases, and scalable backend infrastructure. As the creator of SimpleVecDB (a local-first vector database) and verifiable-thinking-mcp, I have deep experience building efficient, specialized systems that solve complex data problems without the bloat. What I Bring to Your Project: AI & Search Infrastructure: Expertise in semantic search, embeddings, and vector databases (SimpleVecDB, RAG pipelines). Automation & Tooling: Building custom MCP (Model Context Protocol) servers and developer tools that optimize workflows. Full-Stack Agility: Proficient in Python, Rust, and TypeScript, capable of shipping complete products from database to frontend. Performance-First Mindset: I build software that is lightweight, fast, and local-first by default. I don't just write code; I architect solutions that are easy to maintain and ready to scale. Whether you need a custom AI integration, a specialized database solution, or a robust backend API, I deliver clean, documented, and production-ready code. Check my GitHub (CoderDayton) to see my open-source contributions and coding standards.…

Available to hire

I am a Full-Stack Engineer and Open Source maintainer specializing in high-performance AI tooling, vector databases, and scalable backend infrastructure. As the creator of SimpleVecDB (a local-first vector database) and verifiable-thinking-mcp, I have deep experience building efficient, specialized systems that solve complex data problems without the bloat.

What I Bring to Your Project:

AI & Search Infrastructure: Expertise in semantic search, embeddings, and vector databases (SimpleVecDB, RAG pipelines).

Automation & Tooling: Building custom MCP (Model Context Protocol) servers and developer tools that optimize workflows.

Full-Stack Agility: Proficient in Python, Rust, and TypeScript, capable of shipping complete products from database to frontend.

Performance-First Mindset: I build software that is lightweight, fast, and local-first by default.

I don’t just write code; I architect solutions that are easy to maintain and ready to scale. Whether you need a custom AI integration, a specialized database solution, or a robust backend API, I deliver clean, documented, and production-ready code.

Check my GitHub (CoderDayton) to see my open-source contributions and coding standards.

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AI Engineer
December 11, 2025 - January 22, 2026
    paper SimpleVecDB

    SimpleVecDB - What Is It?

    SimpleVecDB is like a super-smart filing cabinet that lives in a single file on your computer. But instead of organizing documents by name or date, it organizes them by meaning.

    The Simple Explanation

    Imagine you have thousands of notes, articles, or documents. Normally, finding the right one means remembering exact keywords. SimpleVecDB is different - you can ask “what’s the capital of France?” and it will find documents about Paris, even if they don’t contain those exact words.

    How It Works (The Dumbed-Down Version)

    1. Everything Goes in One File: Your entire “smart filing cabinet” is just a single .db file - no complicated setup, no cloud services
    2. No Internet Required: Works completely offline on your laptop
    3. Understands Meaning: It converts text into numbers (called “vectors”) that represent what the text means, then finds similar meanings when you search

    Perfect For:

    • Chatbots that remember stuff - Build AI assistants that search through your documents
    • Personal knowledge bases - Search your notes by meaning, not just keywords
    • Indie developers - No monthly cloud bills, no Docker containers, just a simple file
    • Privacy-focused apps - Everything stays on your computer

    The Bottom Line

    It’s basically Google search for your own documents, but it runs entirely on your computer in one simple file. No setup headaches, no ongoing costs, just install and go.