Marcus Llewellyn

Local AI assistants keep project context persistent so you skip the daily reload.

Small local models excel at routine coding tasks but struggle with complex multi-step work.

Hardware improvements and cost economics are flipping how AI systems process data.

Open WebUI lets self-hosters route AI work across multiple models without vendor lock-in.

Local AI tools lack defenses against prompt injection attacks that escalate through integrations.

Local inference on mini PCs cuts costs and latency versus cloud APIs.

Unified memory, not GPU cores, determines whether local LLMs even run on Apple Silicon.

Different formats trade speed, memory, and quality depending on your hardware.

Llama 3 excels at reasoning and long context, while Mistral trades depth for speed and efficiency.