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A workflow is a visual canvas in the Blend AI editor. Think of it like Figma, but for AI: an infinite pane where you drop nodes, wire them together, and run them. You don’t build a workflow only to ship it. Most of the time you build one to experiment: try a model, branch off a variation, compare outputs, and learn what works. The canvas is huge on purpose, so you can lay out many experiments side by side, run a lot at once, and explore freely. Publishing is optional. Some workflows you keep as a private playground forever; others you publish once they’re worth rerunning. Both are normal.

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The canvas

The canvas is an infinite pane. Drag nodes in from the toolbar, move them around, and connect them. Click a node to open its settings panel, where you choose models, write prompts, and configure options. Run a supported server node to test it, or run the whole graph. Lay out experiments side by side and use Annotation nodes to explain or group them. Each node type is documented on its own page under Nodes.

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The shape of a runnable chain

When you do want an end-to-end run, a connected chain follows the same three stages:
1

Input

User Input nodes receive values — typed in directly, or sent by a caller once published.
2

Processing

LLM, Image Gen, Video Gen, Tool, Utility, Batch, and Choose Output nodes transform that data step by step.
3

Result

User Result nodes mark the output of the chain.

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Node families

The live workflow canvas has eleven registered node types: Every registered node has its own page under Nodes.

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How nodes connect

Nodes connect through handles — the small dots on a node’s edges.
  • Input handles sit on the left of a node. They receive data.
  • Output handles sit on the right of a node. They emit data.
You draw an edge by dragging from an output handle to a compatible input handle. A few rules govern what’s allowed:
If a connection is rejected, the editor tells you why — usually a type mismatch, a cycle, or an input handle that’s already full.

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Data types

Every handle carries a data type. This is how the editor knows which connections make sense.

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Compatibility matrix

When you drag an edge, the editor checks the source type against the target type:

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Running the same node many times

By default a node runs once for each input item group it receives. Most workflows start with one item, so each node runs once. A Batch, a multi-select Choose Output, or an LLM structured list can create multiple items. Downstream nodes then run once per item. See Lists & single values for the exact behavior, including Cartesian products when multiple handles receive lists.

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Publishing

When a workflow is worth running again and again, publish it. Publishing turns the canvas into a reusable runner page. User Input nodes become form fields, User Result nodes become outputs, and public workflows can include a creator fee.
Publishing is optional. A workflow you never publish still runs perfectly well inside the editor. When you do publish, you can keep iterating on the canvas and publish a new version later.

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Next steps

Review and publish

How inputs, results, visibility, pricing, examples, and API access work when publishing.

Lists & single values

How batches, selections, and structured list outputs change downstream run counts.

Agents, sub-agents & tools

The difference between an Agent, a Sub-agent, and a Tool — and how to wire them together.

User Input

Start with the node that feeds values into your workflow.