autonomous-loop

To set up an autonomous self-improvement loop, run the autonomous-loop installer to scaffold a memory directory and wire canonical operational instructions with human override controls. This creates a structured, reviewable workflow that repeatedly investigates project weaknesses across short iterative cycles.

Project memory scaffolding creates and seeds a memory directory with work-logs, blockers, themes, predictions, and human override files. This replaces manual bookkeeping and chat scrollback, allowing your autonomous workflow to maintain context and track recurring issues across cycles.

Yes, the autonomous workflow includes an operational control surface with a human override file. You can stop, pause, monitor, or reset the loop at any time, and pre-flight discipline checks ensure the loop respects blocklists and recent error signals before proceeding.

Autonomous loops maintain quality by applying counter-action discipline checks and health signals. Pre-flight checks monitor recent errors, blocklists, theme escalation, and soft-failure root-fixing, while null-result and self-modification metrics keep the iterative cycles stable.

The best way to track recurring themes is by using a seeded project memory system that logs blockers, predictions, and soft-failures. The autonomous loop periodically escalates these recurring themes, ensuring systematic investigation rather than just shipping work.

Yes, the self-improvement workflow leverages existing loop and nonstop skills to execute repeated tasks. The autonomous-loop installer bootstraps the required memory files, discipline rules, and loop-launch setup so these iterative cycles remain structured and reviewable.