aloop

Automate AI coding tasks by structuring iterative plan-build-review loops that cycle through specs, builds, and reviews. This enforces backpressure validation via tests, type checks, and linting to steer development aligned with quality gates.

Yes, autonomous AI development loops support multiple providers including Claude, Codex, Gemini, and Copilot. This allows you to leverage diverse reasoning models across iterative coding tasks while maintaining live steering and per-session state.

Backpressure validation in autonomous AI development enforces quality gates by running tests, type checks, linting, and builds. This steers the automated loop, ensuring iterative coding progress meets project requirements before proceeding to the next cycle.

Start and monitor an autonomous development loop by configuring your project with the setup command, then use start and status commands. A real-time dashboard displays progress, allowing live observation and steering without manual code edits.

Yes, autonomous AI coding uses worktree isolation to keep main branches clean during active development. Persistent runtime state is stored in the local environment with per-project configuration, ensuring isolated and manageable iterative build cycles.

Automated AI development loops require environments that support compatible providers and rely on predefined backpressure gates like tests and linting. If your project lacks these quality validation steps, the loop cannot effectively steer iterative progress.