Everything Loop Active Context

Autonomous development agent state is managed by tracking project status, backlog, and decisions through dedicated state files, ensuring persistent context across planning, implementation, and review phases without direct human intervention.

An autonomous development loop enforces critical rules like TDD and quality gates, guiding the AI agent through discovery, architecture, and implementation phases automatically, which prevents inconsistent progress and ensures self-directed work without continuous user prompting.

TDD is implemented within the AI agent workflow by enforcing it as a critical rule during the inner development loop, requiring the autonomous agent to write tests before code and pass quality gates before submitting features for review.

Yes, autonomous workflow management handles complex feature implementation by guiding the AI agent through breaking down requirements, exploring architecture, writing tests, and submitting code for review automatically using persistent state files.

Yes, autonomous agent state management explicitly prohibits user questions during the session, enforcing autonomous decision-making by the AI agent throughout all development loop phases to maintain self-directed work.

An Everything Loop session is an autonomous development workflow that governs an AI agent's progression through outer and inner loops, including planning, feature selection, discovery, exploration, architecture, implementation, and review.