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An AI agent column runs a prompt against each row and writes the result into one or more fields. Use it where an enrichment or a function cannot help: research a company, classify a lead, or say why it fits.
The agent column editor docked beside a table, showing an Effort card with a web research toggle, a Prompt card whose text holds a column reference pill, and an Outputs card listing two named fields.

The agent column editor.

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Add an agent column

1

Open the Agent tab

Click Tools in the toolbar, then the Agent tab. Click Use AI at the top of Your agents to write a new prompt from scratch.
2

Describe the column, or write it by hand

The editor opens on an AI Assistant card asking what this column should find or write. Describe what you want and click Generate, or click Set up manually to fill in the fields yourself.
3

Choose effort

The Effort card sets which model the column runs on, and each option shows its cost per row. Turn on Web research to let the agent search the web, and Use business context to add your company profile to every run.
4

Write the prompt

In the Prompt card, type / to reference another column’s value, for example “Write a one-line summary of /Company”. Add column under the prompt inserts a reference without typing.
5

Define the outputs

In the Outputs card, pick Fields to list what comes back, each with its own name and type. Each field becomes its own column once the agent runs.
6

Preview, then create and run

Click Preview on 3 rows to run the column on the table’s first three rows for free. Then use the split button for Create & run 10 rows, Create & run 50 rows, or Create and don’t run.

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Build an agent you can reuse

The Agents page is where you build agents to deploy on any table. It is one page with three sections: Build an agent, Or start with a template and Browse agents. Describe the agent under Build an agent and click Generate, or click Set up manually to start from empty fields. Built-in templates opens every agent Oneprofile ships, plus the ones your team has saved.

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Good to know

Your agents comes first: Use AI, the blank prompt you write on the spot, then any agent you have saved. Built-in agents sits under it, ready to run without writing a prompt.
Arrow keys move through the picker, and the right arrow drills into a column that holds several fields or list items. Click a pill to mark that reference required, so a row is skipped when the value is missing. Press Backspace to remove one.
Compare effort levels in the Effort card opens the full trade-off between the models. The Advanced disclosure below it sets a Starting URL column the research begins from, and can keep the agent on that domain.
Click Add output for another field, and Add description to explain one to the model. A description is worth writing when the field name alone could be read two ways.JSON Schema in the Outputs card replaces the field list with a raw schema you write yourself.
Preview on 3 rows is free, within a daily allowance for your workspace. When the allowance runs out, the preview tells you so instead of running.
A column deployed from a saved agent stays linked to it. Its banner names the agent and tells you to open the agent to change the prompt, effort, output or tools.The Quick set-up tab stays editable, so you can still remap which table columns feed the agent’s inputs. Click Stop using this agent on the banner to keep a copy of its settings on the column instead.
Preview stays available on a linked column. Previewing spends nothing and changes nothing.

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Next steps

Enrichment columns

Fill a column from the catalog instead of a prompt.

Run columns

Control what runs, when, and over which rows.