About

November 04, 2026

By Design Won't Fix is a practical homelab and self-hosted engineering publication by Steven Farnell, focusing on step-by-step build guides for local AI inference (Ollama, vLLM, LiteLLM), Proxmox VE virtualization clusters, Home Assistant automation, and multi-agent software engineering workflows.

Every tutorial published here is tested on real bare-metal homelab hardware and documented with copy-pasteable configurations, verification steps, and lessons learned.

For the personal engineering war stories behind these builds, visit our sister blogs: Frizzle Tech Blog and Frizzlefry Blog.

Popular Guides

Setting Up Ollama for Local Homelab AI Inference

November 03, 2026

Setting Up Ollama for Local Homelab AI Inference In this guide, we are setting up Ollama in Docker on a local Linux GPU server, with a practical twist I learned the hard way: running two isolated container instances side by side so scheduled background agents do not constantly evict the model you are actively using in your IDE. When you run a single Ollama container on port 11434 and point your coding assistant, your home automation scripts, and your cron jobs at the same endpoint, the first background job that requests a different model weight will unload your active coding model from VRAM. Splitting your deployment into a primary ollama-hub container on port 11434 and a secondary ollama-worker container on port 11435 gives you clean workload isolation while keeping everything reproducible in a single Compose file. Prerequisites Before starting this build, you need a Linux host equipped with an NVIDIA GPU, the proprietary NVIDIA driver, and both Docker and Docker Compose in...

Setting Up Intelliprompter with TypeSafe Jev for Real-Time Speech Scoring

November 05, 2026

Setting Up Intelliprompter with TypeSafe Jev for Real-Time Speech Scoring After watching NetworkChuck's video on TypeSafe Jev and exploring the official TypeSafe Intelliprompter cookbook , I paired up with OpenAI Codex across two sessions to turn the single-user cookbook reference into a multi-user, self-hosted container. In this guide, we will start with the exact prompt used to have Codex generate the application from the TypeSafe cookbook and pull its API key from the system keyring, and then deploy the resulting Intelliprompter stack in Docker Compose so TypeSafe Jev ( jev-1.13.0 / jev-latest ) can evaluate live speech and advance presentation topics automatically. Traditional teleprompters force you to read a scrolling wall of text word for word, which immediately makes a technical talk or video recording sound robotic. Intelliprompter flips that model on its head: you organize a speech into sequential topics and bulleted talking points, speak naturally in your own words...

Setting Up vLLM for High-Throughput OpenAI-Compatible Serving

November 04, 2026

Setting Up vLLM for High-Throughput OpenAI-Compatible Serving After standing up Ollama for quick model switching, today we are deploying vLLM ( vllm/vllm-openai:latest ) in Docker on port 8000 to serve a dedicated OpenAI-compatible API built for concurrent multi-agent workloads. Ollama is tough to beat when you want to swap models on the fly, but as soon as you have three or four autonomous agents firing parallel tool-calling prompts at the same time, request queuing starts to hurt. vLLM uses PagedAttention and continuous batching to process concurrent requests simultaneously in GPU memory, turning a single homelab GPU into a genuine multi-tenant inference server. Prerequisites Before starting this build, you need a Linux GPU host with Docker, Docker Compose, and the NVIDIA Container Toolkit installed so containers can access your CUDA devices. Next, you will need a Git repository to store your Compose configuration and environment template; you could host your own or use a free...