Agentic Workflow

An agentic workflow is a structured process in which an AI agent autonomously plans and executes a series of steps to complete a complex task. Rather than relying on a human to direct every action, the agent decides its own path through the work — using tools, evaluating results, and adapting as needed.

Components of an Agentic Workflow

A typical agentic workflow consists of:

→ Task definition — A goal or instruction provided to the agent (e.g., "add authentication to this API")
→ Planning — The agent breaks the goal into sub-tasks
→ Tool execution — The agent calls tools such as code editors, shells, APIs, or search
→ Observation — The agent reviews results and adjusts its plan
→ Completion or escalation — The agent signals done, or asks a human for guidance

Why Agentic Workflows Need Human Oversight

Agents can make mistakes — misunderstand requirements, take irreversible actions, or get stuck in loops. Human-in-the-loop checkpoints prevent small errors from cascading into large problems. With AgentRQ, you can define exactly when the agent should pause and wait for your approval before proceeding.

Single-Agent vs. Multi-Agent Workflows

Pattern	Description
Single agent	One agent handles the entire workflow end-to-end
Multi-agent	Multiple specialized agents collaborate, passing results to each other
Supervisor pattern	An orchestrator agent delegates tasks to sub-agents