AI columns

Use an AI column when the desired value requires interpretation or generation rather than a deterministic formula. AI columns can summarize research, classify accounts, explain a recommendation, or draft personalized outreach content for each row.

#Use an inline AI prompt

1. Add a column and select Use AI.
2. Choose the inline prompt option.
3. Write the Prompt Template. Type {{ to insert list variables or values from other columns.
4. Choose the output value type. Configure allowed options when returning a Select or Multi-select value.
5. Optionally add run conditions, then create the column.
6. Run one cell first to review the prompt and output before running the complete column.

A useful classification prompt states the task, supplies the row context, and defines the allowed answer. For example: classify the account as Enterprise, Mid-market, or SMB using its employee count, revenue, and account research, and return only one category.

#Use a list agent

Choose the agent option when the task should use a configured Bigmind agent rather than a single inline prompt.

1. Select an agent that has a mode available for Lists.
2. Select the agent mode.
3. If the mode expects additional context, enable Variables and map each variable to a fixed value, list variable, or column value.
4. Choose the output type and add run conditions if needed.
5. Create and test the column on one representative row.

#Choose the right output type

• Long text: Research, summaries, explanations, and account theses.
• Select or multi-select: Qualification, segmentation, intent, or persona labels. Explicitly tell the AI to use only the configured options.
• Number: A score or estimated quantity. Define the scale and what each end means.
• Checkbox: A decision that should resolve to true or false.
• JSON: Structured data for a downstream Formula or Targetable People column. Describe the required keys and provide a short example in the prompt.
• Message: An email, call script, LinkedIn message, connection request, or generic message.

#Make AI columns reliable

• Reference only the row context the task needs.
• Describe the expected output and constraints explicitly.
• Use a typed output instead of free-form text when the answer must drive filters or automation.
• Add run conditions to avoid generating content for incomplete or disqualified rows.
• Test rows with complete, incomplete, and unusual source data before running the whole column.