Guides
Technical learning content, from running your first model to fine-tuning. Ten topics, ordered roughly by progression but designed to be entered at any point.
- Getting Started What local AI is, why it matters, and how to run your first model. 2 guides
- Hardware GPUs, unified memory, VRAM, and what you actually need for what you want to do. 3 guides
- Running Models Quantisation, inference engines, model formats, and getting good performance. 2 guides
- Local AI Coding Code assistants, autocomplete, and agentic coding tools that run on your machine. 3 guides
- RAG & Knowledge Systems Building retrieval systems over your own documents, entirely locally. 3 guides
- Agentic AI & Harnesses Tool use, agent frameworks, and orchestration with local models. 3 guides
- Fine-Tuning Adapting models to your domain: LoRA, QLoRA, full fine-tunes, and when each is worth it. 2 guides
- Beyond LLMs Image generation, speech recognition, text-to-speech, and other local models. 5 guides
- Server & Enterprise Self-hosting at organisational scale, from a small team on a couple of GPUs to enterprise clusters running open models beyond 100 billion parameters. 6 guides
- AI Regulation & Sovereignty AI-specific regulation like the EU AI Act, alongside data residency, GDPR, and the practical case for keeping data in-house. 3 guides