Last week I wrote about two paths to vLLM on Apple Silicon - comparing vllm-metal and vllm-mlx as options for local inference. This week the picture changed. LM Studio shipped concurrent request support, and suddenly the simplest option became the most practical one. People David Idea We spent the week
People Donavan Idea Set up MCP servers for CRM and Google Drive to connect them directly to Claude Desktop - giving Claude real-time access to our deal pipeline, contacts, and documents without copy-pasting or context-switching. Details * MCP (Model Context Protocol) for connecting AI assistants to external tools and data sources.
People David Idea I tested both vllm-metal and vllm-mlx on the M3 Ultra Mac Studio to see which one gives better multi-user LLM throughput on a high-memory Apple Silicon machine. Details * Both projects showed up in late 2025 - vllm on Metal/MLX is very exciting because it should let
People David Idea Testing Nvidia's v1 LLM Router blueprint as a third approach to intelligent query routing - this time using policy-based task classification instead of semantic similarity or neural network intent matching. Details * Nvidia's v1 LLM Router blueprint (main branch) takes a three-step approach: apply
People: David Idea: Tested UIUC's LLMRouter framework as an alternative to LiteLLM's semantic routing - this one trains an actual neural network for intent classification and can run on hardware as small as a Raspberry Pi with 4GB of ram. Details: * Wanted to compare this against