aif-implement

Plan-driven task execution is automated by sequentially running tasks from an active plan file, marking statuses as in_progress or completed, and preserving progress metadata to enable seamless resumption across interrupted sessions.

Resuming software engineering tasks after an interruption relies on recovering state from git metadata and the plan file, allowing you to automatically continue from the next pending task without losing prior implementation progress.

Automated task implementation requires a plan source like a .ai-factory/PLAN.md file or branch-named plans, which defines the sequential tasks and is updated immediately with task statuses upon completion.

Automated workflow execution handles feature implementation without manual tracking by reading plan context, managing commit checkpoints, and handling task dependencies automatically within your software engineering workflows.

When a plan-governed workflow is interrupted, task statuses and progress are preserved through plan metadata and git state recovery, ensuring the implementation can resume reliably from the exact next pending task.

Automated task implementation works with branch-named plans and git checkpoints by reading plan context from .ai-factory/plans, managing commit checkpoints, and recovering state directly from git metadata to ensure reliable continuation.