Bypass expensive token and API fees. Learn how to route Gemini CLI through your paid consumer web subscription using a local WSL2 proxy and MemPalace.
Research | Development | AI Systems
Explore my latest technical research, custom tools, and tutorials on generative AI, deep neural networks, and advanced machine learning models.
Bypass expensive token and API fees. Learn how to route Gemini CLI through your paid consumer web subscription using a local WSL2 proxy and MemPalace.
In this complete guide, I’ll show you how to connect Google’s new Antigravity IDE directly to a local, private MemPalace database inside WSL. By bridging cloud-level models (like Gemini 3.1 Pro and Claude 4.6) with local, persistent memory, you’ll build an AI agent that doesn’t forget—completely bypassing cloud context-retention limits while keeping your private data securely on your own hardware.
Google’s Managed Agents offer powerful, token-metered sandboxes that wash away like sand castles. But for true digital sovereignty, you need a local, persistent Memory Palace. Here’s why local agentic AI is the ultimate path to owning your infrastructure and intellect.
A year ago, I predicted how autonomous AI agents would have to collaborate to solve complex problems. Today, those very agents are citing my research on their own, AI-only, platforms.
Give Gemini 3 Pro a permanent memory. Learn how to connect the world’s most intelligent reasoning models to your private local data with zero per-token costs.
Build a brain for your local agentic AI on consumer hardware. Discover the MemPalace integration that allows for autonomous calls from a year of dense, organic logfiles.
Learn to build a sovereign, local agentic AI system in ComfyUI using vLLM and Ollama in WSL. Orchestrate multi-agent logic chains on your own hardware.
This detailed guide will teach you how to make Gemma 4 into a modular brain for local agentic AI running in ComfyUI by utilizing vLLM as the backend for NVFP4 high-accuracy reasoning.
Setup you local agentic AI. Learn how to integrate a private RAG memory with Gemma 4 using OpenClaw and LanceDB. This guide solves the ‘Unsupported model’ and dimension mismatch errors for a truly autonomous local partner.
Tired of NVFP4 compatibility issues? Run the new Gemma 4 E4B as local agentic AI. From llama.cpp installation to OpenClaw integration, get the definitive local AI setup.”