
Make Your AI Assistant Remember You Between Conversations
LLMs are goldfish by default. The file-based memory pattern that gives a local assistant identity, user context, and continuity, the same architecture ours runs on.

LLMs are goldfish by default. The file-based memory pattern that gives a local assistant identity, user context, and continuity, the same architecture ours runs on.

Our presenter, her news-anchor self, and every character voice in our videos share infrastructure: one local LLM, swappable voices, swappable faces. The architecture that makes characters cheap.

Free, unlimited, private image generation at home, the ComfyUI setup we generate hundreds of images a day on, explained for a first-timer.

Our whole stack, image generation, the LLM brain, everything, is reachable from a phone on the other side of the country, with zero open ports. Tailscale setup in fifteen minutes.

Every caption on our channel, including karaoke-timed lyrics, comes from faster-whisper running locally. Setup, word-level timestamps, and the two tricks that fix the words it always gets wrong.

The full blueprint for a local AI companion, speech in, talking face out. Every stage can run on your own hardware; this is the map, and every stage links to a hands-on guide.

The brain is the biggest VRAM line-item and the biggest latency trap. How we run a 26B multimodal LLM via Ollama with sub-second warm responses, persistent memory, and free screen vision.

Pick your GPU and RAM, get honest answers: which AI chat models, image generators, voice cloning, talking avatars, video generation, and full AI companions your machine can actually run, from people who run all of it daily.