continuous-agent-loop

You can stop unbounded cycles by deploying continuous agent loops with built-in quality gates that enforce strict progress tracking and fault handling across planning, execution, and evaluation phases.

Recover from failures in long-running AI agent tasks by using continuous agent loops with targeted replay, cycle freezing, and scoped failure analysis for incremental recovery.

Orchestrate RFC decomposition by using a structured cycle selection flow within continuous agent loops to guide branching into pipelines, quality gates, evaluation harnesses, and session persistence.

You need quality gates in continuous autonomous agent loops when long-running AI tasks require strict progress tracking, clear guardrails, and structured failure handling across execution phases.

Yes, continuous agent loops support infinite parallel exploration because their structured cycle selection flow explicitly guides when to branch into parallel exploration or sequential execution.