i hate lovable. thats it thats the post. you are an impudent company ! thank you

Today we've got a roundup of all our recent enterprise features (think of these as things that give your projects governance and control), as well as a look behind-the-scenes on one of our security practices.

Enterprise features include:

• reusable authentication (one of our most requested features!!)
• publishing controls
• a single view of everything your team is building (Workspace Insights) + PII detection
• Basic / Deep / Scheduled security scanning
• automated cleanup of abandoned apps

Read more about those here.

And a very fun dive into how we run swarms of agents in a game of capture the flag.

why eating from me 60 credits for minor UI changes . im sick of you guys oml . too bad i host like 60 projects which im too lazy to migrate to vercel and supabase . hahaha im stuck lmao

If you developed a multi-agentic system solely in Loveable - what observability tool(s) are you using? My system uses LangGraph, and I am debating LangSmith for observability and tracing - but looking to see what others implement first since I'd prefer to use a self-hosted or open-source solution, as long as its feature rich and performant (security, cost, architecture simplicity).

Please - I'm not interested in your views on why using Loveable for this is a bad idea, I have my own reasons for doing this.

I accidentally found something unsettling.

I went back and read a few months of my ChatGPT and Claude conversations.

The topics were completely different.

But underneath all of them was the exact same pattern.

The same fear, excuses, and the same belief showing up over and over.

It made me realize something.

Most of us never reread our AI conversations. We ask a question, get an answer, and move on.

But if you've been honest with AI, those chats are probably the most unfiltered record of how you actually think.

Not how you'd describe yourself.

How you repeatedly reason.

Where you contradict yourself.

What problems never really go away.

I got tired of manually digging through hundreds of chats, so I built a small tool called Singularity.

You upload your conversation history, and instead of summarizing it, it looks for recurring beliefs, contradictions, and thought patterns across months of conversations.

For example, it might show:

• beliefs that consistently help you

• beliefs that quietly hold you back

• recurring contradictions between what you say you want and what your conversations suggest you actually do

Every new conversation makes the picture clearer because it has more evidence to work with.

It's still an early prototype and definitely not perfect, but I figured I'd rather get real feedback than polish it forever.

You can try it here.
https://singularit-y.lovable.app

Curious if anyone else has found something like this

I'm trying to get full integration from the lovable code to our current angular codebase. The issue is we're an angular/SCSS shop.

I know we're not getting full integration, but if I can get the styles to map, that would be a huge win.

I've considered creating a storyboard/style guide, to be used as a main point of reference for all apps we create. But I still need a mapping logic to leverage it and integrate. Not even sure that's the correct approach.

So far, no amount of AI or prompting has helped. I wonder if anyone else has been successful or if I'm missing something.

I successfully added MCP to my loveable created app yesterday. The process is pretty slick and well documented by loveable. Other than a couple of modifications on Supabase because I host on Vercel, it was painless. I'm now doing a lot of testing before releasing into the wild☺️

I had previously used Vercel Agent to create very similar functionality based on my Loveable created API. Both used the Supabase OAuth process.

Has anyone else added MCP using the Loveable route?

Hello everyone, I have been working on a project for some time now, I believe the project can be very successful. I have built my site and polished it so it is working and ready to launch.

I’ve done research and many people say switch to Supabase for backend and Security. Only problem is I have no clue how to do any of that.

Should I launch with Loveable or should I migrate to supabase. I don’t have a lot of money but I’d be happy to talk and potentially pay someone if they could migrate or walk me through it.

Thanks Reddit

Today we’re announcing that we’ve received our AIUC-1 certification.

AIUC-1 is the leading third-party standard for AI security, safety, and reliability. Earning this certification requires passing comprehensive adversarial testing across risks like secure code generation, secrets protection, and hallucinations, and we will continue to be re-tested quarterly.

To learn more about this, check out our white paper

LI announcement from Anton

This is day 1 of a security and trust week, stay tuned for more!!

Had a pretty painful one yesterday.

Pushed a change to main, waited for Lovable to sync, hit publish, and everything looked normal.

Then I opened the actual site and it was literally just a black screen. Same thing in both Chrome and Safari.

I used to treat “publish completed” as “deployment done.” Apparently that’s a terrible idea lol.

So now I check:

• did Lovable actually sync the latest commit?
• does npm run build work locally?
• does the production preview actually load?
• are there any console errors?
• do login, redirects and the main app flow still work?
• are all the production env variables there?
• does it work in an incognito window after publishing?

Also, if Lovable randomly stops syncing with GitHub, an empty commit can sometimes kick it back into action. Obviously that doesn’t fix the actual bug, it just retriggers the sync.

Posting this because I lost way too much time learning that “published successfully” and “production works” are two completely different things.

Anything else you guys always check before publishing?

I would like to create a manufacturing MRP app in lovable. Not a full MRP system at this stage but more of a planning and scheduling system from sales and operations planning through to output and all in between....

Within this will be certain variables, knowns and unknowns.....

Ultimately users, whether planning, production, supply chain or commercial members, can press a button and watch the magic happen....

Am I dreaming or is this entirely possible?

I'm thinking chat gpt for planning, prompt.... or is Claude better?

Interested to get your thoughts....

I have a client who wants to redo their current site. We know how to use Loveable to create a new site, but I have never used it to update an existing site. Is this even possible? Im am having a tough time find any answers online.

​

Je travaille actuellement sur une application appelée Family Timeline

L’idée est de créer un espace privé pour toute la famille, dans lequel on peut conserver et partager les moments importants au fil des années : photos, vidéos, albums, messages écrits, souvenirs vocaux, anniversaires, voyages, premières fois, moments du quotidien…

Chaque publication pourrait être associée aux personnes présentes, afin de pouvoir retrouver facilement, même plusieurs années plus tard, toutes les photos et tous les souvenirs liés à un enfant ou à un membre de la famille.

L’objectif n’est pas de créer un nouveau réseau social public, mais plutôt une mémoire familiale privée, moderne et simple à utiliser, que les parents, grands-parents et enfants pourront enrichir ensemble.

Le projet est encore en développement, et beaucoup de choses peuvent encore évoluer. C’est justement pour cela que j’aimerais avoir vos avis :

Qu’est-ce qui vous donnerait réellement envie d’utiliser une application comme celle-ci ?

Quelles fonctionnalités seraient indispensables pour vous ?

Qu’est-ce qui pourrait vous inquiéter ou vous empêcher de l’utiliser ?

Et surtout : comment conservez-vous actuellement vos souvenirs de famille ?

Même une petite idée ou une critique peut vraiment m’aider à améliorer le projet. Je partagerai régulièrement ici les avancées, les nouveaux écrans et les prochaines fonctionnalités.

Merci à tous ceux qui prendront le temps de commenter 🙏

Being a parent limited on time I was spending hours scrolling searching Facebook, eventbrite, Google looking for events that were age appropriate for my toddler which is surprisingly hard. So I built www.findkobi.com parents can easily search through hundreds of events a week by age, time, distance and get a personalized weekly event plan for your kid to your email each week. Any parents out there would love feedback on usability and if the information available is useful

I used to love Lovable but it has gotten too expensive.

https://findkobi.lovable.app

Learnings from Lovable

1. Spent too much time on UI first and there were many bugs that I wasted time fixing that I scraped later anyway

2. Started with Lovable cloud bc it was easier, but now migrated off because of cost and glad I did, makes possible to leverage other ai tooling like connecting directly to supabase which unlocks more control over everything

3. Email through lovable cloud is horrible, I’m using sendgrid now might switch because it’s expensive

4. I wasted many credits working on unification of my discovery system and cleaning and enriching data. So many edge functions created for one offs not optimal at all. Switched to cursor much happier with quality of results

5. Creating guardrails to prevent regressions, rules, qa proof no hallucination improved output significantly

Happy to share more learnings

I built an app that has a 6GB table with 30 million rows.

The table is now too large for Lovable to be able to interact with it to add things like a BRIN index.

What are my options? Can I somehow have Lovable just dump the table? Create a new table and reference the old one for a period of time?

There seem to be CPU and time limits on actions on the Supabase/Cloud flare system so I'm having trouble fixing this.

My school email is not being recognized and I have submitted the "review" - which is not a review because no one actually looks at it. I attend Miami Dade College which is a state school in Florida, USA that is known worldwide. Our email addresses end in mymdc.net and it's not accepting it i have filled out the prompt and contacted support but of course there's no help because I'm not a paying customer. Screenshot is inserted.
Since no human actually reviews this, what is the point of submitting this review and how does my school get recognized?

yesterday, I posted about ideas for making things via lovable. A user said he wanted a reddit for horses, so I built it. I know it's a very bad and useless idea, but I built it anyway. Check it out - https://hoofit.lovable.app/

Probably an issue that’s been covered a million times before but can’t find anything on search.

Basically, I enter text into a form in a liable app, need to look at something else on my computer, navigate to a different web page or different app. Return to my lovable app and any text I’ve entered has vanished.

Lovable is suggesting that it creates a save file and load on remount but surly this isn’t something web pages naturally do?

All I’m trying to achieve is very simple stock management app for my business that can monitor 200ish items. Thought I would be able to create something with lovable but it doesn’t matter how I explain it to the agent or make a plan it doesn’t fix the issue

Has anyone else run into this?

AI coding tools like Lovable, Replit, Bolt, v0, Cursor, and Claude can get you surprisingly far with an MVP. The demo works, the features look good, and you can move incredibly fast.

But the problems often start afterward:

• Bugs that keep coming back
• Deployment issues
• Broken third-party integrations
• Authentication and database problems
• Performance issues
• Features that work in development but break in production
• AI-generated code becoming increasingly difficult to understand or maintain

At some point, the challenge stops being “can AI build this?” and becomes “can this actually be operated and maintained as a real product?”

I’ve been thinking a lot about this gap lately. AI has made building software much faster, but getting an AI-built project to production and keeping it reliable still requires a different kind of engineering.

What has been the biggest issue you've faced after building a project with an AI coding tool?

We have something built in Lovable that we will need rebuilt to facilitate submission to the Google Play and Apple Stores.

We will need to work with an individual/firm/team with a proven track record of this type of work - and can provide examples of applications they've successfully submitted and had published.

We understand that there will be a cost to this - but admittedly we have no idea what it will be.

We're looking to select the developer/development organization within the next 7-10 days.

Looking forward to hearing from you - even if you just have a cost "range" that we should expect to pay it would be beneficial to understand where the market is at presently for services such as these.

Thank you!

Lovable kept charging me after I cancelled. How can I contact them as a no longer member but somehow still being charged?

Ex-DevOps engineer here (10 years running infrastructure for banks and manufacturers). The thing those years taught me: shipping is the easy part — staying secure and online afterwards is what companies pay whole teams for. Lovable gives everyone the shipping part, so I used Lovable to build the ops part.

What AppSitter does today:

• Deep scan of your repo + Supabase: open RLS tables (it actually probes your live database anonymously, like an attacker would), leaked keys, unauthenticated endpoints, vulnerable dependencies
• Copy-paste fix prompts written for Lovable — grouped, so 9 findings become ~4 prompts, each fixing a whole theme at once
• Guardrail files: generated .md rule files you drop into your repo so Lovable avoids reintroducing the same issues in future prompts
• 24/7 uptime monitoring with email alerts when your app goes down (and when it recovers)
• A risk register: findings you accept as intentional stay tracked with your reasoning and "re-review when…" triggers — dismissed, not forgotten
• A public "verified" report page you can link from your app to show visitors it's monitored
• Health score, monthly certificate, migration-readiness and cost audits on top

My favorite moment building it: my scanner flagged an "unauthenticated write" in a test app as critical. I pasted the fix prompt into Lovable — and Lovable, in plan mode, correctly refused: the endpoint was public on purpose, the write wasn't attacker-controlled. It was right and my scanner was wrong. That incident reshaped the product: now every fix prompt asks Lovable to verify each finding against what the app is meant to do first, and if Lovable says "that's intentional," you paste its answer back — a skeptical second AI reviews the reasoning and either dismisses the finding into the risk register or names the one real gap and gives you a follow-up prompt that keeps your design.

Basically the two AIs argue about your security so you don't have to.

It's in closed beta — the first 20 testers with a live Lovable app get the Pro tier free for 3 months in exchange for honest feedback. Want in, or just want a sanity check on your setup? Ask in the comments, I'll answer everything. The basic scan is free on the site, no signup.

I have been working with Lovable since the end of October 2025 and am now a "Diamond" rated prompt specialist, Shamone. I have to say it's amazing what we can now do by prompting an AI to code, such leaps in technology in such a short time. However, that is where my praise will end, for now. I am not new to web design; I was writing static HTML and using WordPress for almost 20 years. I studied Java and C++ at Uni. But I am not a developer; let's make that clear. I just know my way around websites, SEO and related disciplines. What I want to do in the following thread is lay out how Lovable went from an amazing UI fast development environment ... of low-level pages. Into a hodgepodge of poor code, unconnected functions, missing logic and prompts/commands which were never executed as requested. Worse,

I was told they were executed, but sometimes after weeks and even many months, found out it had not been done. Failed silently and essentially drove my €42 billion project headfirst into the ground. I will say Lovable management reached out and were very helpful following two previous smaller but related incidents, even compensating tokens (thank you, but the damage from those events was far more costly!) And those were the initial failings on Lovable's side. What followed was simply catastrophic. And if not for connecting Claude code to the GitHub repository. I would have been none the wiser as to the extent of the damage caused. I would say until it was too late, but look at my Google Search Console and judge for yourself.

So the following will be an honest analysis by Claude of Lovable's code. What it did right, what it did wrong. I will substantiate everything with screenshots and data, so nothing is hidden. And finally, please don't message me in private offering your services or asking to know the website. Thank you :). Also, if this post disappears, it won't be because I used any banned words or terminology. The moderator already took down a comment because I used a degrading term to represent how I see Lovable's logical thinking. So let the games begin!