Hi HN, I’m Ted. While recovering from a major surgery from 2022-24, I decided to finally try building something instead of just consuming. I became fascinated with AI assistants but frustrated by their reliance on cloud infrastructure and the costs that come with it.
I started wondering: could I build something that runs entirely on my own machine?
I’m not a professional programmer — this is my first real project — but over 5 months of learning and trial and error I put together a rough prototype, Evelyn.
Right now Evelyn can:
– Run fully on macOS (I’m testing on a Mac Mini M4 Pro/Macbook Pro M1).
– Use Whisper for transcription.
– Connect to open-source LLMs via LM Studio
– Generate real-time speech with fallback layers (XTTS → ElevenLabs → macOS TTS).
– Keep a simple memory across sessions (JSON-based, with dedupe + recall).
– Route queries between local and external models with a basic orchestrator.
Demo video: https://www.youtube.com/watch?v=OtJpAgLSmfI
This is *not a product* — just an early attempt at exploring local-first AI in a world that's hyperscaling. I use it daily to learn and to see what works and what breaks.
I’d really appreciate feedback on:
– The technical approach (what would you change or simplify?)
– Whether local-first assistants like this have potential vs. cloud-only.
– Advice on making a project like this easier for others to try.
I don’t have source ready yet, but I can share more about the architecture and trade-offs in the comments.
