What is an AI workflow?
An AI workflow is a chain of steps, often several model calls and tools wired together, that turns an input into a finished output, with checkpoints where a human can review along the way.
Where an agent decides its own next move, a workflow is a defined pipeline: research → outline → draft → edit → publish, for example. Each stage has a clear job and hands its output to the next. This makes the result more predictable and easier to debug than a fully open-ended agent, which is why teams reach for workflows when they ship the same kind of output repeatedly.
Workflows shine for content pipelines, release notes, data cleanup and code review, anything with a repeatable shape and points where a person should sign off before the process continues.
Most are open source and drop into your existing setup, so you can adapt a stage rather than build the whole pipeline from scratch.
Popular workflows
All Workflows →Type
- tradingview-mcpAI-assisted TradingView chart analysis — connect Claude Code to your TradingView Desktop for personal workflow automationWorkflowsJul 2026
- hyper-waterfallA human-governed AI coding workflow that distills ephemeral session context into persistent project memory—making work traceable, reviewable, and resumable.WorkflowsJul 2026
- Data Cleanup WorkflowDedupe, normalize and validate CRM records on a scheduleWorkflowstoday
- claude-codeClaude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.WorkflowsJul 2026
- FlowiseBuild AI Agents, VisuallyWorkflowsJul 2026
- Content PipelineResearch → outline → draft → edit → publish, fully chainedWorkflowstoday
FAQ
Workflow or agent, which should I use?
Use a workflow when the task has a repeatable shape and you want predictable, reviewable stages. Use an agent when the path to the goal is open-ended.