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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:

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

Agentic Workflows with Claude Code

Claude Code is purpose-built for agentic coding workflows. It can autonomously read codebases, write tests, fix bugs, and open pull requests — while integrating with AgentRQ to notify you at critical decision points via MCP.

Autonomous Agents vs. Agentic Workflows

An agentic workflow and an autonomous agent answer different questions. Whether the steps are fixed in code or chosen by the model is the workflow vs. agent question; whether a human approves those steps is the autonomy question. See autonomous agents vs. agentic workflows for the full comparison, and autonomous workflow for the term itself.

Related Terms

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