Here's something nobody tells you about generating data tables with AI: it's way harder than it looks.
I've spent the last month building data tables with various AI tools. Dashboards for SaaS apps, admin panels for e-commerce, analytics views for startups. And I'll be honest—most of my early attempts were disasters. Tables that couldn't sort. Filters that broke everything. Pagination that just... didn't paginate.
But after 20+ attempts, I finally cracked the code. The difference between a working data table and a mess of broken columns comes down to how you write your prompts.
Key Takeaways:
- Data tables need explicit feature requests (sorting, filtering, pagination) or AI skips them
- Always specify your data structure upfront—AI guesses wrong about 80% of the time
- Mobile-responsive tables require different patterns than desktop—ask for them separately
In This Article
- Why Data Tables Break with Generic Prompts
- The Anatomy of a Good Data Table Prompt
- Basic Table Prompts That Work
- Adding Sorting
- Filter and Search
- Pagination Done Right
- Row Selection and Bulk Actions
- Mobile Responsive Tables
- Complete Templates
- Common Mistakes
- FAQ
Why Data Tables Break with Generic Prompts
You know what happens when you prompt "create a data table for users"?
You get a table. Technically. It renders some rows and columns. But it won't sort. Clicking headers does nothing. There's no pagination (so your 10,000 rows load all at once). The search box is decorative.
Here's the problem: AI tools treat "table" as a solved problem. They give you HTML. But a real data table is actually one of the most complex UI components out there.
Think about it—a production data table needs:
- Column headers that sort (ascending AND descending)
- A search/filter system that actually filters
- Pagination that doesn't break when you change page size
- Row selection for bulk actions
- Responsive behavior on mobile
- Loading states for async data
None of that comes free. You have to ask for it. Explicitly.
The Anatomy of a Good Data Table Prompt
After building dozens of tables, I've landed on a formula that works consistently. Every good data table prompt needs four elements:
| Element | Why It Matters | Example |
|---|---|---|
| Data Structure | AI needs to know column types | "columns: name (string), email (string), status (badge), created (date)" |
| Features | Nothing is assumed | "sortable columns, search filter, pagination (10/25/50 per page)" |
| Visual Style | Prevents generic output | "minimal design, alternating row colors, rounded corners" |
| Behavior | Interactions need specs | "clicking row opens edit modal, checkbox selection for bulk delete" |
Here's the structure I use:
Create a [STYLE] data table component showing [DATA TYPE]. Columns: - [Column 1]: [type] - [any special formatting] - [Column 2]: [type] - [any special formatting] ... Features needed: - [Feature 1] - [Feature 2] ... Styling: - [Visual requirement] - [Visual requirement] Use [FRAMEWORK] with [STYLING LIBRARY].
The magic is in being specific. Let me show you what that looks like in practice.
Basic Table Prompts That Work
Let's start simple. Here's a basic table prompt that actually generates usable code:
The Prompt:
Create a clean data table for displaying customer orders. Columns: - Order ID: string, monospace font - Customer: string with avatar placeholder - Amount: number formatted as currency ($) - Status: colored badge (pending=yellow, completed=green, cancelled=red) - Date: formatted as "Dec 20, 2025" Include: - Striped rows (alternating gray/white) - Hover state on rows - Header row should be sticky Use React with Tailwind CSS. Include sample data for 8 orders.
This generates a working table because we've told the AI exactly what each column should look like and how. No ambiguity.
Want to try this yourself?
If you've been following our guides on building admin panels with AI, you'll recognize this pattern—specificity beats brevity every time.
Adding Sorting Without Breaking Everything
Now let's add sorting. This is where most AI data table prompts fail.
The common mistake? Just adding "make it sortable" to your prompt. That gives you click handlers on headers that do absolutely nothing meaningful.
The Prompt That Works:
Create a sortable data table for employee records. Columns: - Name: sortable alphabetically (A-Z default) - Department: sortable alphabetically - Salary: sortable numerically (highest first default) - Start Date: sortable by date (newest first) - Status: NOT sortable (badge only) Sorting behavior: - Show sort indicator arrow on active column - Click toggles between ascending/descending - Only one column sorted at a time - Default sort: Start Date descending Visual indicators: - Active sort column header slightly highlighted - Up/down arrow icons for sort direction - Cursor pointer on sortable headers Use React with Tailwind. Create useState hooks for sort state management.
See the difference? We're not just saying "sortable"—we're specifying which columns sort, how they sort, and what the visual feedback looks like.
The key insight: AI doesn't know which columns should be sortable unless you tell it. A status badge doesn't need sorting. A date column probably should sort newest-first by default. You have to think through these details.
Filter and Search the Right Way
Filtering is tricky because there are two types that people conflate:
- Global search - one input, searches all columns
- Column filters - dropdowns/inputs per column
Most prompts just say "add search" and get a useless input that filters nothing. Here's how to get both working:
Global Search Prompt:
Add a global search to the employee data table. Search behavior: - Single search input above the table - Searches across Name, Department, and Email columns (not ID or salary) - Case-insensitive matching - Debounced input (300ms delay before filtering) - Shows "X results found" below search box - Clear button (X) to reset search - Empty state: "No employees found matching [search term]" Styling: - Search input with magnifying glass icon - Full width on mobile, 300px max on desktop - Subtle border, rounded corners
Column Filter Prompt:
Create a data table with column-specific filters. Filter types by column: - Department: dropdown select with "All Departments" option - Status: multi-select checkboxes (Active, On Leave, Terminated) - Start Date: date range picker (from/to) - Salary: range slider ($0 - $200k) Filter UI: - Filter row below header row - Collapse/expand filter row with button - "Clear all filters" button when any filter active - Active filter count badge on filter toggle button The filters should stack (AND logic) - selecting Department AND Status shows employees matching both.
Pro tip: If you're building a SaaS dashboard, column filters are usually better than global search. They give users more control over data-heavy views.
Pagination Done Right
Pagination seems simple until you actually implement it. Here's the thing—most AI-generated pagination looks right but breaks in weird edge cases.
The Robust Pagination Prompt:
Add pagination to the data table with these requirements: Controls: - Page size selector: 10, 25, 50, 100 rows per page - Previous/Next buttons with icons - Page number buttons (show 5 at a time with ellipsis) - "Showing 1-10 of 247 results" text Behavior: - Default to 10 rows per page - Disable Previous on first page, Next on last page - Changing page size resets to page 1 - Maintain current page when filtering (unless results require fewer pages) - Jump to first/last page buttons Position: - Pagination controls below table - Page size selector on left - Page numbers centered - Results count on right Edge cases: - 0 results: hide pagination entirely - Less than page size: hide page numbers, show only count - Last page: don't show empty rows
That edge cases section? That's the difference between a demo and production code. AI often forgets about zero-result states or partial last pages.
Row Selection and Bulk Actions
Now we're getting into the features that make data tables actually useful for real work. Row selection sounds simple, but there are about five ways to screw it up.
The Prompt:
Add row selection with bulk actions to the data table. Selection features: - Checkbox in first column for each row - "Select all" checkbox in header (selects current page only) - Indeterminate state for "Select all" when some rows selected - Selected row count shown: "3 selected" - Selected rows get light blue background Bulk actions (shown when 1+ rows selected): - Floating action bar appears above table - Actions: Delete, Export CSV, Change Status - Delete requires confirmation modal - Actions applied to all selected rows Keyboard support: - Shift+click for range selection - Escape key clears selection State management: - Selection persists when changing pages - Selection clears when filtering changes results - Track selected IDs (not row indices)
That last point about tracking IDs instead of indices? I learned that one the hard way. When you filter or sort, row indices change but IDs don't. If your AI generates index-based selection, your bulk actions will affect the wrong rows.
Making Tables Work on Mobile
Here's my hot take: most data tables shouldn't exist on mobile.
Seriously. If your table has 8 columns, trying to cram it into 375px of screen width is user-hostile. But sometimes you need it. So here's how:
Mobile-First Table Prompt:
Create a responsive data table that transforms on mobile. Desktop (768px+): - Standard table layout with all columns visible - Horizontal scroll if needed Mobile (<768px): Transform into card-based layout: - Each row becomes a card - Show only key columns: Name, Status, Amount - "View details" expands card to show all columns - Stack cards vertically with 12px gap Alternative: Priority columns - Always show: Name, Status (columns 1-2) - Hide on mobile: Email, Department, Start Date - Add horizontal scroll hint shadow on right edge Do NOT just shrink the table - it becomes unreadable. Transform the layout entirely.
The transformation approach works better than trying to make tiny tables usable. If you're working on dashboard prompts, you'll find that card layouts often outperform tables on mobile anyway.
10 Complete AI Data Table Prompt Templates
Alright, here's what you came for. Copy-paste ready templates for common table types.
1. User Management Table
Create a user management data table with: - Columns: Avatar (image), Name (sortable), Email (sortable), Role (badge), Status (badge: active/inactive), Last Login (date, sortable), Actions (edit/delete buttons) - Features: Global search, role filter dropdown, status filter, pagination (10/25/50) - Bulk actions: Activate, Deactivate, Delete with confirmation - Row click opens user edit modal - Use React + Tailwind + shadcn/ui table component
2. Order History Table
Create an order history table showing: - Columns: Order # (monospace), Date (sortable), Customer, Items (count badge), Total (currency, sortable), Status (colored badge), Actions - Status colors: pending=yellow, processing=blue, shipped=purple, delivered=green, cancelled=red - Include: Date range filter, status multi-select filter, search by order # or customer - Expandable rows showing order line items - Export selected orders to CSV - React + Tailwind CSS
3. Product Inventory Table
Build a product inventory table: - Columns: Image thumbnail, SKU, Product Name (sortable), Category (filterable), Stock (number with low-stock warning <10), Price (sortable), Actions - Low stock rows highlighted in light red - Category dropdown filter - Stock range filter (0-10, 11-50, 50+) - Inline edit for stock count (click to edit) - Bulk update stock levels - React with Tailwind
4. Analytics/Metrics Table
Create an analytics metrics table: - Columns: Metric Name, Current Value, Previous Value, Change (percentage with up/down arrow + color), Sparkline chart, Trend - Change formatting: green for positive, red for negative - Sortable by any numeric column - Date range selector affecting all values - Compact design for fitting many metrics - React + Tailwind + Recharts for sparklines
5. Lead/Contact CRM Table
Build a CRM leads table: - Columns: Name, Company, Email, Phone, Lead Score (progress bar), Stage (badge), Assigned To (avatar), Last Contact (relative date) - Stage filter: New, Contacted, Qualified, Proposal, Won, Lost - Assigned To filter (team member dropdown) - Lead Score sortable - Quick actions: Call, Email, Schedule - Drag-and-drop row reordering for priority - React + Tailwind
I could keep going, but you get the pattern. Be specific about every column, every feature, every interaction.
Mistakes That Ruin AI Data Tables
Let me save you some debugging time. These are the most common ways AI-generated tables break:
1. Forgetting Loading States
The fix: Always add to your prompt: "Include loading skeleton state for when data is fetching. Show spinner or skeleton rows, not blank table."
2. No Empty State
The fix: Add: "When no data matches filters, show empty state with illustration and 'No results found' message. Include 'Clear filters' button."
3. Breaking Sort on Re-render
The fix: Specify: "Sort state should persist in URL params or localStorage. Refreshing page maintains sort."
4. Select All Selects EVERYTHING
The fix: Be explicit: "Select All checkbox selects current page only. For all pages, show 'Select all 247 results' link."
5. Filters Don't Reset Pagination
The fix: Add: "When any filter changes, reset to page 1. Don't stay on page 5 when filtered results only have 2 pages."
If your AI-generated code is throwing errors, check out our guide on fixing AI-generated code errors for quick debugging strategies.
What About TanStack Table?
Quick note on libraries: If you're building production tables, you might want to specify TanStack Table (formerly React Table) in your prompts:
Create a data table using TanStack Table (React Table v8). Use the useReactTable hook with these features: - getSortedRowModel for sorting - getFilteredRowModel for filtering - getPaginationRowModel for pagination - Column visibility toggle - Use @tanstack/react-table package
TanStack handles the complex state management that AI often gets wrong. The AI generates the UI layer while TanStack handles the logic. Best of both worlds.
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- Fix AI-Generated Code Errors - Quick debugging when your table breaks
Frequently Asked Questions
How do I make AI generate a sortable, filterable data table?
Specify each feature explicitly in your prompt. Say which columns should be sortable, what type of sort (alphabetical, numeric, date), which columns should be filterable, and what filter type (dropdown, search, date range). Don't just say "sortable table"—list every sortable column by name.
What's the best way to prompt for pagination in data tables?
Include page size options (10/25/50), navigation controls (previous, next, page numbers), results count text, and edge cases (what happens with 0 results, or fewer results than page size). Specify default page size and whether it should persist between sessions.
Why does my AI-generated table break on mobile?
Standard table layouts don't fit on small screens. Prompt for either a card-based transformation (each row becomes a card) or specify priority columns that stay visible while others hide with horizontal scroll. Never try to just shrink a multi-column table.
Should I use TanStack Table with AI prompts?
Yes, for production tables. Include "using TanStack Table v8" in your prompt and ask for specific hooks like useReactTable, getSortedRowModel, and getFilteredRowModel. It handles the complex state management while AI generates the visual layer.
How do I add bulk actions to an AI data table?
Prompt for: checkbox column, select all behavior (current page only vs. all pages), selected row count display, action bar that appears when rows are selected, specific action buttons with confirmation for destructive actions, and keyboard shortcuts like Shift+click for range selection.
Written by the Fardino Team. We build AI tools for frontend developers. Try Fardino free →
