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A practical, bash-first blueprint for making a Linux workstation AI-ready: choose balanced hardware (GPU/VRAM, CPU, RAM, NVMe), install base dev tools, set up NVIDIA CUDA or AMD ROCm via distro-specific commands, create isolated Python envs and install PyTorch/TensorFlow/JAX, enable reproducible containers (Docker/Podman + NVIDIA toolkit), validate with llama.cpp and vLLM, and use the troubleshooting tips to maximize performance and longevity.