The Goal-Driven system implements a master-subagent architecture where a master agent continuously monitors and evaluates a subagent’s progress against predefined criteria. The master agent restarts or redirects subagents that become inactive or fail to meet criteria, sustaining long-running autonomous problem-solving sessions. It supports integration with AI coding assistants like Claude Code, Codex, and OpenClaw, targeting tasks such as compiler design, theorem proving, and system architecture.