Why Your Custom NemoClaw LLM Takes Forever to Respond (Or Completely Ignores You)

You finally set up a local AI agent to help you tackle your dev backlog (if you haven't yet, check out my guide on how to run NemoClaw with a local LLM & connect to Telegram ). The goal is simple: feed it your local codebase so it can help you refactor complex components, map out new business logic, or write comprehensive unit tests—all without sending proprietary company code to an external API. You fire up an agentic framework like NemoClaw on your RTX 4080, paste in your prompt, and... the agent completely loses its mind. Instead of writing code, it either ghosts you, dumps a wall of unformatted JSON into your terminal, or gets trapped in an infinite 3-second retry loop until the session crashes. After spending a full day digging through API logs, I realized this isn't a network bug. It is a fundamental flaw in how local agent frameworks handle context windows, and it affects almost every developer trying to build private AI workflows. If your local agent is stuck in an infinite loo