Best Practices
Development · 21 articles
How do I build efficiently with Lovable?
Break big requests into small, clear prompts. Use Plan mode to outline architecture before building. Start with core features, then iterate. Use visual editor for quick tweaks (colors, sizing, text). Leverage integrations (Supabase, Stripe, Resend) via simple prompts. Check Cloud → Logs when debugging. Revert and re-prompt if needed.
How should I structure my prompts for the best results?
Be specific and clear: 'Add a login form with email and password fields' beats 'make login.' Include context: 'This is a SaaS dashboard for task management.' Use Plan mode first to outline your architecture. Break complex features into multi-step prompts: 1) Build UI, 2) Add database, 3) Add validation. Provide examples or screenshots if possible.
What should I do when I hit an error?
Click 'Try to fix' (free)—it scans logs, detects issues, and attempts quick fixes. Check Cloud → Logs for error details. Use Plan mode to investigate before trying again. Revert to a stable version and re-prompt with clearer instructions. Break your request into smaller prompts. Contact [email protected] if stuck.
API Integration and Network Management
When integrating external APIs, store secret keys via Cloud → Secrets or Supabase Edge Functions, never in chat or code. Use Supabase Edge Functions for backend logic that calls external APIs securely. Set reasonable timeouts and implement retry logic for unreliable networks. Log API responses to debug integration issues.
Check Console Logs
To debug issues, open your browser's Developer Tools (F12 or Cmd+Option+I) and check the Console tab for error messages. JavaScript errors often appear there with stack traces. Lovable projects also log errors to the Cloud tab → Logs, which shows AI agent and deployment errors. Comparing browser console vs. Cloud logs helps pinpoint whether issues are client-side or infrastructure.
Code Consistency
Maintain consistent naming conventions, component structure, and styling across your project. Follow the Lovable tech stack (React, Vite, TypeScript, Tailwind CSS, shadcn/ui, Radix UI). Reuse existing components instead of duplicating logic. Establish guardrails in Workspace knowledge (Lovable's Knowledge System) so all projects follow the same architectural rules.
Data Flow Management
Trace data from user input through your app to the database and back. Ensure each step validates and transforms data correctly. Avoid passing unvalidated data between components. Use React state management patterns (props, context, hooks) consistently. Clear data flow makes debugging easier and prevents subtle bugs.
Database Query Verification
Test database queries in isolation (via Supabase dashboard or Edge Functions) before integrating them into your UI. Verify that filters, joins, and aggregations return the expected data. Check Row Level Security (RLS) policies to ensure users see only what they should. Log query results during development to spot issues early.
Deep Problem-Solving Approach
When facing a complex issue, break it into smaller parts. Investigate each component (frontend logic, database queries, API calls, external integrations) separately. Use logging and error messages to trace the exact failure point. Consider whether the issue is reproducible and how it manifests. This systematic approach narrows down the root cause faster.
Documentation and Explanation
Document your architectural decisions, database schema, and business logic in Project knowledge (docs.lovable.dev/features/knowledge). Include naming conventions, why certain patterns were chosen, and domain terminology specific to your app. Clear documentation helps Lovable generate more accurate code and makes it easier to onboard collaborators.
Error Fixing
Use the "Try to fix" button (free, no credits) to auto-scan logs and attempt quick fixes—it resolves about 60% of simple issues. For deeper problems, check Cloud → Logs for specific error messages, use Plan mode to investigate before Agent mode executes fixes, and break complex changes into smaller prompts. Reverting to a previous version and re-prompting with a clearer request also helps.
Error Management and Resilience
Implement proper error handling for API calls, database operations, and external integrations. Show user-friendly error messages instead of stack traces. Provide fallback UI for loading states and failures. Use try-catch blocks in Edge Functions. Test your app's behavior when external services are slow or unavailable.
Learning and Adaptation
Stay updated on Lovable features by reading release notes and docs. Learn from each project—what prompts worked well, what required iteration. Experiment with different prompt styles (detailed specs vs. quick requests) to find what works for your workflow. Join the community and share lessons learned with other builders.
Performance Optimization
Use Lovable's built-in Speed tool (powered by Google Lighthouse) to identify performance bottlenecks. Optimize images by compressing and using appropriate formats. Break components into smaller parts to enable better code splitting. Cache API responses and database queries where appropriate. Monitor Core Web Vitals and aim to keep scores green.
Preserving Working Features
Before making changes, understand what works and why. Test existing functionality after edits to ensure nothing breaks. If you need to modify a working feature, consider creating a new version first, testing it thoroughly, then switching over. This staging approach reduces the risk of regression.
Solution Verification
After implementing changes, verify the fix works by testing in preview or deployed app. Check both the happy path and edge cases (empty states, error conditions, boundary values). Confirm related features still work and no new errors appear in the logs. Document what was changed and why for future reference.
Systematic Debugging Approach
Start with high-level observation (what's broken, where does it fail?). Check logs in Cloud → Logs. Isolate the issue by disabling parts of the code. Use browser dev tools to inspect DOM and network requests. Reproduce the issue consistently, then test fixes in a controlled way. Document what you find for future reference.
Technical Debt Awareness
Track decisions that prioritize speed over polish (quick wins vs. clean code). Document temporary solutions and mark them for later refinement. Periodically refactor code to reduce complexity, eliminate duplicated logic, and improve readability. Addressing technical debt early prevents it from slowing down future development.
Thorough Issue Analysis
Before proposing fixes, gather all relevant context: check error logs in Cloud → Logs, understand the current implementation, trace data flow, and verify database queries. Ask clarifying questions about expected behavior versus actual behavior. This deep analysis prevents introducing new bugs and ensures solutions address root causes, not just symptoms.
Type Safety and Data Validation
Lovable generates TypeScript code with proper types. Leverage type definitions to catch errors early. Validate user input before sending to the database (check required fields, formats, length limits). Use Supabase RLS policies as a second security layer. This combination prevents many runtime errors and security issues.
UI Consistency and Theming
Use Tailwind CSS consistently across your app for spacing, colors, and typography. Define a color palette and font scale upfront in Workspace knowledge. Leverage shadcn/ui and Radix UI components to maintain consistency. The visual editor lets you tweak styling directly on the page—use it to refine layouts and ensure uniform appearance.
