You do not have to kill a Ralph loop to redirect it. Edit .agent/STEERING.md mid-run and the agent reads it at the top of the next iteration, handles the critical work first, then resumes the task list.
An autonomous agent only stays safe when every task ends in a machine-checkable result. Tests, type checks, lint, and screenshots are the feedback loop that lets the agent grade its own work.
An autonomous agent is only as trustworthy as what it shows you. Here are the live stream, per-iteration history, progress log, screenshots, and timing metrics that make a Ralph loop auditable.
An autonomous loop burns money when it thrashes. Cap iterations, match the model to the task, and gate every pass on tests so the loop stops instead of looping forever.
Long-running agents lose the plot when one context window fills up. Start each iteration fresh and keep durable state on disk so progress never lives in chat history.
Long autonomous runs fail on three axes (context, cost, crashes). Here is the architecture that keeps an AI coding agent productive overnight and across days.
