autoloop

You can manage state for long-running autonomous agent tasks by using Git as a state machine, where branch tips represent the current best state across iterations. This enables reliable keep or discard cycles for iterative work.

To prevent context window overflow during continuous agent loops, you can redirect verbose output to files and extract only the essential metrics for the active loop, ensuring careful context window management.

You can automate keep or discard cycles for iterative agent improvements by running an autonomous loop protocol that retains measurable improvements and discards regressions until a goal is met or a hard blocker is hit.

Yes, you can use Git branches to track baselined metrics for autonomous workflows. The protocol uses branch tips to represent the current best state, ensuring orderly progress logging across iterative cycles.

You should use a Git-driven loop for agent iteration when running long-running tasks that require tracked baselines, measurable keep or discard cycles, and orderly progress logging to ensure deterministic outcomes.

Yes, autonomous agent iteration runs until the goal is met, a hard blocker is encountered, or a human interrupts. It favors minimal, composable changes to handle complex tasks continuously without manual intervention.