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.