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modelARch
Stop fixing code in Lovable. Build scalable apps instead.
modelARch turns your requirements into an evolving model that becomes the source of truth. Preview and refine your entire application before generating it deterministically. When things change, evolve the model, dispose of the code, and regenerate, at no additional code cost.
AI app builders made it incredibly fast to start building software.
But as applications grow, so do the roles, permissions, workflows, business rules, and dependencies between them.
With prompt-driven development, every change can mean another generation, another correction, and another attempt to keep everything consistent.
We think the problem is simple: you shouldn't have to keep fixing generated code. You should change the system that defines it.
That's why we built modelARch.
🧠 Model first. Generate later.
With modelARch, AI helps you turn natural-language requirements into an explicit model of your entire application: data, relationships, roles, permissions, workflows, rules, and behavior.
Something changes?
Change the model, dispose of the code, and regenerate it.
The model remains the source of truth.
👀 Build the whole app before buying the code
You can model your application from end to end, preview it across desktop, tablet, and mobile, change it, and validate it before purchasing the generated code.
Your subscription gives you access to the modeling environment.
No credits. No pay-per-prompt.
Keep refining until you're satisfied.
Only then do you pay for the code.
⚙️ Then modelARch generates deterministically
AI helps interpret what you want to build.
But the final application isn't generated probabilistically from another prompt.
Once the model is ready, modelARch generates the full-stack application deterministically from that model.
AI interprets. The model defines. modelARch generates.
🔄 Evolve the model. Regenerate the software.
This is the bigger idea behind modelARch.
We don't think generated code should be something you continuously maintain. The model should be the durable artifact. The code should be disposable.
As your business changes, you evolve the model. The existing code can be discarded, and the entire application regenerated deterministically from its new state.
No patches. No accumulated prompt history. No trying to keep generated code in sync with what the business is supposed to do.
We maintain evolutionary models, not generated code.
The model evolves. The code is disposable. The software is regenerative.
And regeneration isn't another purchase: once you've generated your application, you can keep evolving the model and regenerating the software without paying for the code again.
🎯 Who is it for?
Founders, developers, agencies, and software teams building applications that are becoming too complex for endless prompting — especially systems with interconnected roles, permissions, workflows, and business rules.
If you've been building with Lovable, Base44, Bolt, or similar tools, we're particularly interested in hearing what you think.
Maybe the next step after vibe coding isn't better code generation. Maybe it's making generated code disposable.
the deterministic generation step to fastapi and react/ts is super interesting. how exactly is the explicit model stored physically to guarantee that 1:1 code mapping every single time?
Very interesting idea, reminds me of Rspec back in the rails days. The idea you can define your application as a spec and that is the human readable form. Then can change the code underneath knowing it is fully tested and behaves like you defined.
Would love to hear more
Building client apps for a living, the pressure point I'd worry about isn't the model being wrong, it's the client changing a permission rule at 4pm the day before a demo, with no time to properly evolve the model, regenerate, test and deploy. That's exactly when teams reach for a hand patch regardless of the tool's philosophy. Is there any sanctioned scoped exception for that, clearly marked as debt to fold back into the model later, or is the rule zero hand edits from day one, no exceptions?
the model as the source of truth i buy. the part i keep getting stuck on with this shape of tool is the data.
disposing of the code and regenerating is clean because code has no state. the database does. once there are real rows in it, a change that is one line in the model is a migration with customer data in it, and that is the bit that actually costs you the day. does the model own the migration too, or does regenerate assume a schema you are willing to rebuild?
related, and it is the thing i would put on the page: what happens when somebody has to patch something at 2am. if the answer is you never hand edit generated code, you only change the model and regenerate, that is a real and defensible position. it is just worth saying out loud, because it is the constraint people will feel first.
congrats on shipping it.
@martin_herran This is a really interesting approach! I like the idea of keeping the model as the source of truth instead of letting the codebase become the thing you constantly have to maintain. Good luck guys !
About modelARch on Product Hunt
“Stop fixing code in Lovable. Build scalable apps instead.”
modelARch was submitted on Product Hunt and earned 32 upvotes and 17 comments, placing #25 on the daily leaderboard. modelARch turns your requirements into an evolving model that becomes the source of truth. Preview and refine your entire application before generating it deterministically. When things change, evolve the model, dispose of the code, and regenerate, at no additional code cost.
modelARch was featured in Developer Tools (517.5k followers), Artificial Intelligence (475.9k followers) and No-Code (5.9k followers) on Product Hunt. Together, these topics include over 197.6k products, making this a competitive space to launch in.
Who hunted modelARch?
modelARch was hunted by Martin Herran. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how modelARch stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Martin Herran
Hey Product Hunt 👋
AI app builders made it incredibly fast to start building software.
But as applications grow, so do the roles, permissions, workflows, business rules, and dependencies between them.
With prompt-driven development, every change can mean another generation, another correction, and another attempt to keep everything consistent.
We think the problem is simple: you shouldn't have to keep fixing generated code. You should change the system that defines it.
That's why we built modelARch.
🧠 Model first. Generate later.
With modelARch, AI helps you turn natural-language requirements into an explicit model of your entire application: data, relationships, roles, permissions, workflows, rules, and behavior.
Something changes?
Change the model, dispose of the code, and regenerate it.
The model remains the source of truth.
👀 Build the whole app before buying the code
You can model your application from end to end, preview it across desktop, tablet, and mobile, change it, and validate it before purchasing the generated code.
Your subscription gives you access to the modeling environment.
No credits. No pay-per-prompt.
Keep refining until you're satisfied.
Only then do you pay for the code.
⚙️ Then modelARch generates deterministically
AI helps interpret what you want to build.
But the final application isn't generated probabilistically from another prompt.
Once the model is ready, modelARch generates the full-stack application deterministically from that model.
AI interprets. The model defines. modelARch generates.
🔄 Evolve the model. Regenerate the software.
This is the bigger idea behind modelARch.
We don't think generated code should be something you continuously maintain. The model should be the durable artifact. The code should be disposable.
As your business changes, you evolve the model. The existing code can be discarded, and the entire application regenerated deterministically from its new state.
No patches. No accumulated prompt history. No trying to keep generated code in sync with what the business is supposed to do.
We maintain evolutionary models, not generated code.
The model evolves. The code is disposable. The software is regenerative.
And regeneration isn't another purchase: once you've generated your application, you can keep evolving the model and regenerating the software without paying for the code again.
🎯 Who is it for?
Founders, developers, agencies, and software teams building applications that are becoming too complex for endless prompting — especially systems with interconnected roles, permissions, workflows, and business rules.
If you've been building with Lovable, Base44, Bolt, or similar tools, we're particularly interested in hearing what you think.
Maybe the next step after vibe coding isn't better code generation. Maybe it's making generated code disposable.