AI Implementation & Technical Workflows

Planning a multi-GPU workstation, running language models on your own hardware, or selling AI automation to clients? This technical handbook covers the whole job, from choosing hardware and configuring it to pricing the service.

Read it along one of three tracks: hardware and local models, video production, or automation for businesses.

Read a free sample (PDF) →

With this book you will

• work out whether cloud or your own workstation is cheaper (at October 2026 prices) and pick GPUs, VRAM, power and cooling;
• set up Linux, Proxmox, CUDA and Docker, then run models in vLLM and llama.cpp, including MoE models on 48 GB of VRAM;
• produce an AI video, from script and keyframes to avatars, lip sync and sound;
• build automations in n8n and Make and RAG systems, using six documented B2B deployments and pricing guidance;
• connect desktop agents (Claude Code, Codex) through MCP.

Who it is for

Sysadmins, video creators, agency owners and consultants who deploy AI for themselves or for clients.

What you get

• 190 A4 pages, English edition.
• Ready Docker Compose stacks, GPU monitoring scripts, SQL schemas, 50 prompts and a Q4 2026 tool map.
• You can download the PDF right after payment, and the download link is also sent by email.