Columns & Configuration

Define, configure, and manage columns for your lists

Columns define the structure of your list. Each column represents a data field — from simple text and numbers to AI-enabled fields that your agent fills automatically during processing.

Manual + AI Columns: Combine columns you fill yourself (company name, website URL) with AI-enabled columns the agent researches (company overview, tech stack, decision makers) for a powerful hybrid workflow.

Column Types

Every column has a type that determines what data it holds and how it's displayed:

Type	Description	Example Use
Text	Free-form text content	Company overview, notes
Number	Numeric values	Employee count, revenue
Date	Date values	Founded date, last contact
Email	Email addresses	Primary contact email
URL	Web links	Company website, LinkedIn profile
Enum	Predefined options (dropdown)	Industry, company size tier

AI-Enabled Columns

AI-enabled columns are the core of what makes Lists powerful. When a row is processed, the assigned AI agent uses its tools — web search, webpage visits, tech stack inspection, CRM lookups — to research and fill each AI-enabled column.

How AI Columns Work

1. You create a column and toggle AI Enabled on

2. You write a Prompt Template that tells the agent what to research for that column

3. When rows are processed, the agent executes the prompt for each row and writes the result

Writing Effective Prompt Templates

The prompt template is the instruction your AI agent follows when filling the column. Be specific about what you want and the expected format.

Pro Tip: Reference other columns in your prompt to give context. For example: "Research the company at {website} and provide a 2-3 sentence overview of their core business, target market, and key differentiators."

Good prompt examples:

Column Name	Prompt Template
Company Overview	Research the company and provide a concise 2-3 sentence overview of their business model and market
Decision Makers	Find the top 3 decision makers (C-level or VP) at this company with their name, title, and LinkedIn
Tech Stack	Inspect the company's website and identify key technologies, frameworks, and cloud providers used
Qualification Score	Based on all available data, rate this lead 1-10 for fit with our ideal customer profile

Avoid vague prompts:

Bad Prompt	Better Alternative
"Research the company"	"Provide a 2-3 sentence overview covering business model, founding year, and employee count"
"Find contacts"	"List the top 3 C-level executives with name, title, and LinkedIn URL"
"Is this a good lead?"	"Score 1-10 based on: company size 50-500, B2B SaaS, and US-based. Explain your reasoning."

Knowledge Base Integration

Some AI columns can be configured to reference your organization's knowledge base during processing. Toggle Requires Knowledge Base when the agent needs internal context — such as your product catalog, pricing tiers, or qualification criteria — to fill the column accurately.

Creating Columns

1

Open Your List Navigate to the list where you want to add columns.

2

Add a Column Click the + button in the table header or use the column management panel. Provide a name and select a type.

3

Configure AI (Optional) Toggle AI Enabled and write a prompt template. Optionally enable Requires Knowledge Base if the agent needs internal data.

4

Save The column is added to your list immediately and will be included in future processing runs.

Column Library

DarcyIQ provides a reusable column library so you don't have to recreate common columns for every list.

Library Levels

Level	Scope	Who Can Create
System Columns	Pre-built columns available to everyone	DarcyIQ (read-only)
Organization	Shared across your entire organization	Admins and Owners
User	Personal columns only you can see	Any user

Using the Column Library

1. Open the Column Selector when editing your list

2. Browse available system, organization, and user columns

3. Select columns to add them to your list

4. Customize the prompt template or configuration for your specific use case

Pro Tip: Create organization-level columns for standardized fields like "Company Overview" or "Qualification Score" so every team member uses the same enrichment prompts.

Managing Columns

Column Operations

Action	Description	Permission Required
Add	Add a new column or select from the library	Editor
Edit	Update name, type, prompt template, or configuration	Editor
Reorder	Drag columns to change their display order	Editor
Hide/Show	Toggle column visibility without removing data	Editor
Remove	Remove a column from the list	Editor
Detach Data	Remove the column's data while keeping the column definition	Editor

Column Visibility

Use the Column Visibility Selector to show or hide columns in your table view. Hidden columns retain their data and will still be processed by AI — they're just not displayed in the table.

Column Configuration Fields

Field	Description	Required
Name	Display name shown in the table header	Yes
Type	Data type (text, number, date, email, URL, enum)	Yes
AI Enabled	Whether the agent should fill this column during processing	No
Prompt Template	Instructions for the AI agent when populating the column	If AI
Requires KB	Whether the agent should reference the knowledge base	No
Description	Help text or notes about the column's purpose	No
Mandatory	Whether the column must have a value	No
Visible	Whether the column is shown in the table by default	No

Best Practices

1. Name columns descriptively: "Primary Decision Maker" is better than "Contact"

2. Limit AI columns to 3–5: More AI columns means longer processing time per row

3. Order matters: Place identifying columns (name, website) first, AI columns after

4. Use the library: Save time by reusing organization-level columns across lists

5. Test prompts early: Process a few rows to validate your prompt templates before running the full list

6. Combine manual and AI: Let AI handle research while you provide the seed data