Agentic Workflow
A multi-step task executed by one or more AI agents that plan, call tools, and adapt — the production shape of agent-based automation.
What Is an Agentic Workflow
An agentic workflow is a multi-step task carried out by one or more AI agents that plan their own next move, call tools, observe results, and adapt — as opposed to a deterministic workflow with hard-coded steps. The term describes the production shape of real-world agent automation: research → synthesize → write → review → publish, or analyze ticket → query DB → suggest fix → file PR. Use the term when discussing what agents actually do in production, not just what they could theoretically do.
How It Works
- Single-agent workflow — one agent runs the full ReAct loop across all steps
- Multi-agent workflow — orchestrator agent dispatches to specialist subagents (researcher, writer, reviewer); the orchestrator handles cross-step state
- Hybrid (deterministic + agentic) — fixed pipeline stages with agents at decision points, the most common production shape
- Checkpointing — production workflows persist intermediate state so the workflow can resume after failure rather than restarting from scratch
Why It Matters
Most real agent ROI lives in workflows, not single chats. A one-shot chat with Claude is useful; a 5-step research-write-edit-fact-check-publish workflow with the same Claude is leverage. Frameworks like LangGraph, CrewAI, and the new generation of orchestration layers (Mastra, AutoGen) exist to make agentic workflows reproducible and observable. The trade-off: agentic workflows are harder to debug than deterministic pipelines, which is why observability tools like Langfuse and LangSmith matter for production.
Examples
- Coding agents — Claude Code, Cursor Composer, Cline run multi-step plan-act-test workflows
- Research agents — Perplexity Deep Research, OpenAI deep research, Manus execute web-research workflows
- Automation agents — Trinity, Hermes, n8n workflows with AI nodes
- Marketing/content agents — multi-agent pipelines for keyword research → brief → draft → edit
- UI/design agents — v0 by Vercel generates React + Tailwind components from text prompts, then iterates via chat — agent loop with code as the output