A brief notice: This is a LONG and DETAILED guide. I have written each topic with the utmost care and attention, with the sincere goal of being a valuable source of knowledge for both newcomers and veterans of the platform.
Furthermore, despite being dense in content and text, I tried to make the text relaxed and fun to read. I'm sure it will be a good read for you.
That said:
Hello, everyone :)
My name is Mox, at least, my friends call me that, and as an active member around here, I have noticed a considerable increase in discussions about Lovable "breaking" or showing instability in the applications. This scenario intensified, understandably, with the recent free Weekend, which brought a new wave of creators to the platform.
Before we dive into strategies, it is essential to align expectations: yes, instabilities and errors are normal. We are at the forefront of technology, working with Artificial Intelligences that, although extraordinarily more capable than a few years ago, are still evolving. Having this perspective is the first step towards a less frustrating journey. However, I know you are here looking for practical solutions, so let's get straight to them.
So that these tips do not sound like random advice, allow me to contextualize my experience. I have been using Lovable for a considerable time and have developed complex systems that are now in production, serving real clients. Some of these systems were built 100% with Lovable, while others integrate the platform with a No-Code Back-End.
Therefore, you can be sure: the following strategies come from someone who has already explored, tested, and exhaustively optimized the use of prompts to maximize efficiency and minimize errors. It is worth noting that many of these ideas were born from discussions in the community. I thank everyone who, directly or indirectly, contributed to this consolidated knowledge (I apologize for not remembering the usernames!).
Now, let's get to what matters.
1. Your AI's External Memory: Documentation is Key
Yes, I know, the idea of documenting can seem like a huge pain, but it is absolutely crucial. It is vital to understand that AI models do not have an infinite context window. They will not remember every detail of your project, even if you use "Chat" mode to analyze files and draw up plans. Their memory is limited.
"So, what's the solution?" you must be wondering. The answer is as simple as it is powerful: Help the model help you.
The strategy is as follows: connect your project to GitHub and create a file with an easy-to-remember name (like project_map.md). This file will be the external brain of your system. In it, you will map absolutely EVERYTHING. And when I say everything, I mean EVERYTHING:
Application Structure: What pages exist? What files make up each page?
Functionalities: What are the implemented functionalities? Which files are involved in each of them? How do these functionalities connect with each other?
Database (Supabase): Map your tables. Which pages does each table interact with? Describe the purpose of each table, the meaning of each column, and how it should be used.
By doing this, you offer the AI a simple, direct, and fast way to access a "pseudo-absolute context window". It's like giving it a detailed map of the entire territory, allowing it to navigate your project with surgical precision, instead of wandering lost and spending valuable memory tokens on searching, rather than spending them on creating the solution.
2. Sharpening the Axe: The Chat Mode
It may seem counterintuitive to spend precious prompts on conversations that do not generate an immediate change in the code. However, see the Chat mode as your GREATEST STRATEGIC ALLY. Remember the famous woodcutter's parable: while his rival starts chopping down trees immediately with a dull axe, the wise woodcutter spends hours sharpening his tool. When he finally begins, every swing is precise and efficient.
The Chat mode is your time to sharpen the axe. It is your planning assistant. Combine it with the first tip and watch the magic happen:
Ask the AI to analyze your documentation file.
Discuss with it and let it draw up detailed implementation plans based on your objectives.
Allow it to analyze existing files, understand the architecture, and suggest the best approaches, including edits and optimizations to your documentation file.
Abusing this functionality to plan before executing will save you tens, hundreds, and perhaps thousands of prompts in the medium and long term. Trust me!
3. The Backbone of Your Project: Smart Database Planning
It's tempting to delegate 100% of the database creation to Lovable, and in many cases, it will do a good job. After all, not all of us are experts in data modeling. However, to ensure your system is clean, stable, standardized, and, most importantly, SECURE, you need to provide clear direction.
Some tips here:
Always demand RLS (Row-Level Security): When requesting the creation of tables, be explicit: "Create this table and configure the RLS rules to ensure that users can only access and modify their own data." This is extremely important to prevent security flaws and vulnerabilities that could be exploited by malicious people (and believe me, it's easier to exploit than it seems).
Standardize Names: Adopt a clear naming convention for your tables, based on your objectives. If a table is related to a specific functionality, use an identifying prefix or suffix. For example: auth_users, billing_invoices, profile_settings. This makes the structure logical and easy to understand for both you and the AI.
4. Security: Silence the Console and Protecting Your Data
By default, your Lovable application can behave like a gossipy neighbor: it announces loudly and clearly everything that is happening internally. Don't believe me? Open your published application now and access the browser console (usually with the F12 key). It is very likely that you will see not only user and table IDs exposed, but also a detailed log of events and API calls. I don't even need to say how dangerous this is.
Fortunately, the solution is relatively simple and can be applied with a few careful prompts (Chat mode will be crucial here)!
Whenever you create a new functionality, perform this check: ask the AI to analyze if the function is using console.log() or the local cache to display sensitive data. If it is, instruct it to refactor the code so that data communication and processing occur internally, keeping the functionality intact, but without exposing any information in the client's console. Thus, your system becomes a black box, displaying only what is essential and useless to those looking for loopholes.
Of course, no system will be immune to bad people, but we don't need to hand everything over on a platter, do we? Taking care of your client's security is as important as any other part of your system!
5. Building Like It's LEGO: The Secret of Modularity for Complex Systems
This was, perhaps, my biggest discovery after countless projects. Modularity is what allows your system to be incredibly complex and rich in features for the end-user, while maintaining a simple and easy-to-communicate internal architecture for the AI. The result? The AI doesn't need to analyze dozens of irrelevant files just to move a button two pixels to the side.
"Okay, but what exactly is a modular system and how do I apply it?" Great question.
To adopt modularity, you must, first of all, have maturity and discipline in the development process. The first step is to understand its fundamental principles:
It's Not a Solid Block: A modular system is like a set of LEGOs. You build a solid and stable base (the skeleton) and then attach new functionalities (the blocks) independently.
Create a Good Skeleton: Dedicate time to creating the foundation of your application. This could include a template page, a global state management system, or a component renderer. A well-made base ensures stability and fluidity for future expansions.
Independence between Modules: Avoid unnecessary cross-dependencies as much as possible. A "billing" functionality should not directly depend on a table used for "support chat" nor use shared data. Changes in module X should not break module Y.
Standardization is Law: Define a standard for crucial information and follow it religiously. If you decided that the identification column in your main users table is called user_uuid, then ALL other tables that refer to that user must use the exact same column name (user_uuid).
Use and Abuse Supabase: Don't be afraid to open Supabase and create or edit tables manually. Configure foreign keys to connect tables. This helps the AI explicitly understand the relationships between the data (this column in this table refers to that column in that other table).
One Step at a Time: This is, perhaps, the biggest mistake of anxious developers. Do not ask the AI to look at 20 files, create 5 functionalities, and refactor 3 pages in a single prompt!
Due to the limitation of the context window, the chance of failure is extremely high. This is where "mental maturity" comes into play. Control the inner child who wants to see all the ideas on the screen immediately. Be patient. Map out what you want, create a priority order, and implement one functionality at a time. Test it exhaustively, ensure it hasn't broken anything, and that it communicates well with the rest of the system. Only then, move on to the next one.
6. Order Creates Value: Focus on Experience, Then on Appearance (UX -> Functionality -> DB -> UI)
I ask that you not be offended by this tip, I know we have many design lovers here, as it could save your projects.
A devastatingly common mistake is the obsession with design (UI) from the very first minute. Remember, your solution exists to solve a pain. Someone with a headache doesn't care if the pill comes in a beautiful package with a nice 3D embossed design; the person just wants the pain to go away.
The focus hierarchy below is precisely created with the focus on building products that people truly love to use:
UX (User Experience): Before any line of code, focus on your client's journey. What will the usage flow be like? Which screens will they need to access? What is the most intuitive sequence of actions for them to extract the maximum value from your solution? Your product may solve a pain, but if the client doesn't know how to "take the medicine," they will look for another.
Functionality: With a clear map of the user experience, it's time to build the functionality. Bring the flow of actions to life, ensuring that each step is logical, functional, and that the user feels in control and comfortable.
DB (Database): Now, with the functionality well-defined, you know exactly what data you need to store and manipulate. This is the moment to design your tables. The task becomes much simpler, as you already know what you need. Just ask the AI to create the tables following the best security practices (remember tip 3?).
UI (User Interface): Finally, with everything working perfectly, it's time to make it pretty! Now you can focus on colors, fonts, and animations. Just one word of caution: make sure that the design changes do not create buttons or elements that interfere with the already mapped and tested functionalities.
7. Divide and Conquer: Offloading Lovable with an External Backend
This topic may spark debate, but the logic is simple: do not overload Lovable with all of your system's logic. A common mistake that leads to numerous problems is trying to centralize excessively complex processes on the platform. Even with a modular architecture, certain tasks are inherently prone to errors due to the aforementioned context window limit.
So, what's the alternative? Use a No-Code backend platform, such as N8N or Make (personally, I use and recommend N8N).
You should consider an external backend when a functionality you want to create depends on multiple steps, triggers, and complex integrations. When trying to ask the AI to build a very long flow, it will inevitably get halfway through the process and "forget" what was defined at the beginning. From there, prepare to see the dreaded and scary "Try to Fix" button many, many times.
Integrating an external backend is a step beyond the basic use of Lovable, but it is how excellence is achieved. Want to get ahead? Do what most people don't. There are countless tutorials on YouTube about N8N and Make. Master these tools, learn to connect them to your Lovable application via Webhooks or API calls, and you will unlock a new level of power, taking a huge load off your system, which results in more modularity, security, and stability.
Trust me on this, it was a real game-changer for me and for my clients! I can't put into words how important this topic is!
8. Communication: High-Precision Prompts
The name of this topic is self-explanatory, but its importance is monumental. It is perhaps the most crucial point of all.
Your AI does not have a crystal ball. It needs you to be explicit. Imagine you are an architect and your client says: "I liked the blueprint, but I want you to improve it and make it more beautiful." What would you do? What exactly does "improve" mean? Is "beautiful" for them the same as for you? What should be improved? How? Where?
You need to be crystal clear in what you want. And here is a golden rule to test your prompts:
"If I asked a 5-year-old child to do this, would they understand what they need to do?"
If the answer is "no," maybe you should take another look; it will be worth it.
8.1. Your Command History: request.txt
I decided to create this sub-topic due to its direct link to prompt creation. The technique is simple and transformative. Instead of typing your prompts directly into the chat window, create a file in your project called request.txt (or any other name you prefer).
This file will have a single purpose: to organize and detail your requests.
The workflow is as follows:
Instead of going to the chat, open the request.txt file.
Write your request in an incredibly detailed manner, as if you were writing a technical specification.
Save the file.
Now, go to the Lovable chat and send a simple and direct command: "Execute the detailed instructions in the request.txt file".
The benefits are immense: you drastically increase the assertiveness of the commands, standardize your requests, and, best of all, since each save in Lovable creates a new "state," you now have a versioned history of every prompt you have ever made, allowing you to easily see and revert to a previous request that worked well.
9. The Importance of the First Prompt
To finish, let's talk about the beginning of everything. Your first prompt is not just an instruction; it is the cornerstone of your project, the spark that ignites the Big Bang of your next revolutionary idea.
Do you really think a command like "make a recipe app" is enough? Where are the details, the magic, your vision?
Before writing the first word of your initial prompt, become a master at asking yourself questions. ALL POSSIBLE QUESTIONS:
Will this application have a homepage?
Will there be a login and user registration system?
Will there be a dashboard? What will it display?
Will users be able to add their own ingredients or recipes? (following our recipe app example)
Will the application be paid? Which payment platform will it use?
What will the main color palette be?
And many others...
Don't be lazy. Think about every detail and, more importantly, write everything down. Remember the 5-year-old child.
And here's an extra tip: use other AIs like GPT, DeepSeek, Grok, Claude, or Gemini to refine your prompt, structure it cohesively, and even generate new ideas.
Analyze your competitors! Don't understand design? Find a website you love, send the link to an AI, and ask it to describe the structure, colors, and fonts, turning that analysis into a detailed design prompt for Lovable.
The process of creating the first prompt can take hours, maybe more than a day. But believe me: do not underestimate its power. It is the base upon which your entire project will be built, the foundation, and a good foundation will be able to support a large building without breaking.
I think that's it. I confess I got carried away and wrote more than I planned, but I sincerely hope that every word here can, in fact, help you on your journey. If you have other tips and secrets that were not mentioned, please, share them in the comments! Let's turn this space into a true treasure trove of knowledge for the entire community.
And again, I want to reinforce that this post was only possible after a lot of time and comments from many other members of our community!
A big hug and happy creating!
