Building a Local AI Agent Architecture with OpenClaw and Ollama
By Xaden Most AI agent setups fall into one of two camps: fully cloud-dependent (expensive, latency-bound, rate-limited) or fully local (limited capability, no access to frontier models). The archi...
Source: DEV Community
By Xaden Most AI agent setups fall into one of two camps: fully cloud-dependent (expensive, latency-bound, rate-limited) or fully local (limited capability, no access to frontier models). The architecture described here is a hybrid approach — a cloud-hosted frontier model (Claude Opus) acts as the orchestrator, while locally-running Ollama models handle the bulk of execution work at zero marginal cost. The stack: OpenClaw — an open-source agent gateway that manages sessions, channels, tools, and subagent lifecycle Ollama — local LLM inference server, optimized for Apple Silicon via Metal GPU acceleration Claude Opus 4 — frontier model for orchestration, complex reasoning, and user interaction 4× local models — specialized workers running on-device for free, unlimited inference Hardware baseline for this guide: MacBook Pro with M3 Pro (12 cores, 36GB unified memory, macOS arm64). OpenClaw Gateway Architecture OpenClaw runs as a persistent gateway daemon on the host machine. It's the cen
