Ensuring Lovable Includes All Required Features in Your Prompt

Why Lovable skips features from your prompt

When you send a long, detailed prompt to Lovable, the AI does its best to implement everything. But complex prompts with many requirements often result in some features being silently skipped. This is not a bug in Lovable — it is a limitation of how large language models process multi-part instructions. The AI tends to focus on the first and most visually prominent requirements in your prompt. Features mentioned at the end, or described in a single sentence among many paragraphs, are the most likely to be omitted. This is especially true when features depend on each other — the AI may build the foundation but skip the edge cases or secondary behaviors. Lovable's own documentation acknowledges this pattern, which is why they recommend building incrementally. Instead of describing your entire app in one prompt, build one feature at a time, verify it works, and then move on to the next. This approach uses more prompts but results in more complete and reliable output.

• The prompt contains too many requirements for the AI to implement in a single pass
• Features at the end of a long prompt are deprioritized by the language model
• Dependent features are described together but the AI only implements the base feature
• Vague language like 'add some validation' gives the AI room to interpret minimally
• The AI scope is too broad — no @file references to anchor the changes to specific components

Error messages you might see

Before you start

• A Lovable project where you need multiple features implemented
• A clear list of all features you want (written down before prompting)
• Familiarity with Plan Mode (the non-code-modifying reasoning mode in Lovable)

How to fix it

// Vague prompt:
// "Create a dashboard with user stats, orders table,
// search functionality, and export options"

// Structured prompt:
// Build a dashboard page with these features:
// 1. A stats card at the top showing total orders count
// 2. A table listing recent orders with columns: Order ID, Customer, Amount, Date
// 3. Pagination on the table showing 10 rows per page
// 4. A search input above the table that filters orders by customer name
// 5. An "Export CSV" button that downloads the current filtered data

// Using Agent Mode directly (risky for complex prompts):
// Agent Mode prompt: "Build a dashboard with 5 features..."

// Step 1 — Plan Mode prompt:
// "Review my requirements and create a detailed plan:
// 1. Stats card with total orders
// 2. Orders table with pagination
// 3. Search filter by customer name
// 4. CSV export button
// 5. Loading skeleton while data fetches
// List every file you will create or modify."
//
// Step 2 — Review the plan, confirm all 5 items are covered
// Step 3 — Click "Implement the plan" to build

// One massive prompt with everything:
// "Build a complete dashboard with stats, table, search,
// pagination, export, loading states, error handling,
// and mobile responsiveness"

// Prompt 1: "Create @src/pages/Dashboard.tsx with a stats card showing total orders"
// Verify in preview → works ✓
//
// Prompt 2: "Add an orders table below the stats card in @src/pages/Dashboard.tsx
// with columns: Order ID, Customer, Amount, Date"
// Verify in preview → works ✓
//
// Prompt 3: "Add pagination to the orders table in @src/pages/Dashboard.tsx
// showing 10 rows per page with Previous and Next buttons"
// Verify in preview → works ✓
//
// Prompt 4: "Add a search input above the table in @src/pages/Dashboard.tsx
// that filters orders by customer name in real time"
// Verify in preview → works ✓

// No systematic verification process

// Feature Audit Checklist:
// [✓] 1. Stats card shows total orders count → verified in preview
// [✓] 2. Orders table renders with all 4 columns → verified in preview
// [✓] 3. Pagination works, 10 rows per page → tested Next/Previous buttons
// [✗] 4. Search filter — filtering works but does not reset on clear
// [✓] 5. CSV export downloads correct data → tested with filtered results
//
// Follow-up prompt for item 4:
// "Fix the search filter in @src/pages/Dashboard.tsx — when the user
// clears the search input, the table should show all orders again"

Complete code example

1# Feature Implementation Rules
2
3## When receiving multi-feature prompts:
4- Implement EVERY numbered item in the prompt
5- Do not skip items that seem minor or optional
6- If a feature cannot be implemented, explain why instead of silently omitting it
7- After implementation, list which items were completed and which were deferred
8
9## Implementation order:
101. Create the data model / types first
112. Build the UI structure second
123. Connect data to UI third
134. Add interactivity (search, filter, sort) fourth
145. Add edge cases (loading, error, empty states) last
15
16## Verification:
17- Every new component must render without errors in preview
18- Every button must have a working onClick handler
19- Every form must have proper state bindings
20- Every list must handle the empty state
21
22## File conventions:
23- One component per file
24- Keep components under 150 lines
25- Extract reusable logic into custom hooks in src/hooks/
26- Use @/ path alias for all imports

Best practices to prevent this

• Write numbered lists, not paragraphs — the AI tracks numbered items more reliably
• Send one feature per prompt for critical features that must work perfectly
• Use Plan Mode for any prompt with more than 3 requirements to verify the plan before building
• Reference specific files with @file syntax to prevent the AI from creating new files when it should modify existing ones
• Test each feature in the preview immediately after generation, before moving to the next prompt
• Keep an external checklist (even a simple text file) to track which features have been verified
• If a feature is skipped, do not re-send the entire original prompt — send a focused prompt for just the missing feature
• Add feature implementation rules to your AGENTS.md so the AI always acknowledges every item

Still stuck?

Copy one of these prompts to get a personalized, step-by-step explanation.

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