Choosing your AI prototyping stack: Lovable, v0, Bolt, Replit, Cursor, Magic Patterns compared
A practical field guide to picking the right AI builder for your next product idea or super-powere your team.
It is time to compare my favourite vibe coding and AI prototyping tools again.
Last time I did this was back in June. Since then the tools have moved fast. I have my preferred stack, but every few months I go back and poke the others to see whether they offer something genuinely new that my current setup does not.
Quick disclaimer: I am not judging them on basic “can it make a pretty UI” for someone who cannot code. At this point, they all can. What I am looking for is a versatile solution that can help me not only build interactive prototypes with brain and memory (back-end, AI features and database), but build anything from internal tools to small production-ready apps, and generate meaningful code that I can hand over to developers. All in an intuitive single environment without touching any code.
TL;DR
If you want one tool that lets you build anything from throwaway prototype to internal tool or small production ready app, without staring at code all day, choose Lovable.
v0 is the second best fit. It also has a generous free tier, which is nice for experimenting, but you will run into limits once you try to do more advanced collaboration and GitHub flows.
If you need a specific framework, for example Angular or React Native, look at Bolt or Replit, but they might be less intuitive and overwhelming for beginners.
If you mainly want to add a bit of interaction on top of existing Figma designs, and you are not planning to grow that into a fully maintained application, Figma Make is your friend.
If your goal is to compare multiple interface ideas quickly on a shared canvas and do lightweight testing and storytelling, Magic Patterns earns a place in the stack.
If you are comfortable with code and either want to contribute to existing products or grow beyond what low code tools can handle, move to Cursor. Use it directly, or as the next step after you reach the ceiling of Lovable, v0 or Bolt. And use it if you want to convert your Figma design into a code with Figma MCP.
Want to know more about my reasons? Keep reading
How I look at these tools
My main questions when I test them are:
Feature completeness and intuitive all-in-one working environment for solo builders and teams.
Can I get a backend, database, auth and deployment without yak-shaving
Can I reuse the code and collaborate with developers
How well do they handle AI features like chat, reasoning, text-image-voice generation
And yes, my primary target audience is product designers and product managers, but but I also see wide adoption across other teams: sales are building demos, tailored to their customers’ needs, people ops are creating tools to onboard new employees, marketing is going wild on dashboards and shiny landing pages. And everybody is building internal tools and micro-apps they always wanted.
With that in mind, here is where the tools are for me right now.
Lovable
I talk about Lovable in most of my talks because it has become my default workshop tool, and that was not an accident.
In my very first AI prototyping workshop I used Bolt, then I moved to v0. Eventually a bunch of small annoyances piled up and I switched to Lovable. I have not regretted that decision.
Lovable feels like the most complete environment for going from “tiny prototype” to “serious apps” in one place. You can design components, screens and flows, and then wire them up to a backend and database through Lovable Cloud, backed by Supabase, directly from the Lovable interface. If you do not specify something, Lovable will scaffold the missing pieces for you, both frontend and backend. It also has automatic debugging and safety checks, which make it very forgiving for people who have never shipped code before.
One detail that sounds small but is huge in practice: bi-directional GitHub sync. You can push your project out of Lovable, work on it in Cursor or a regular IDE, and then pull the changes back in. That is what enables my Frankenstein workflows like “convert my Figma into code with Figma MCP in Cursor, then continue building in Lovable”.
Cherry on top of the cake is Lovable integration with Gemini, allowing you to build AI features without dealing with API keys. You can add AI-powered features like chat, text and image generation, analysis and other “smart” behaviour without leaving the platform.
Also, it is fully enterprise-ready and is strong on collaboration, making it a great choice for teams.
In other words, Lovable is not just a prototyping toy. It can comfortably power production ready-ish MVPs, internal tools, microsites and thin features that live alongside a bigger product. For teams who want to stay mostly out of the code editor, it is the most “complete world in one tab” I have found so far.
v0 (by Vercel)
I am also a big fan of v0. Visually it can absolutely keep up with Lovable. Sometimes I even prefer its taste level. By default it tends to generate slightly calmer, more “serious” UI, while Lovable leans to add more shine and sparkles. You can of course steer both of them with prompts.
One thing I appreciate is that v0 makes fewer ridiculous UI-flows like white text on white backgrounds or multiple close icons on modals (hey Lovable, can you fix it?).
Where v0 used to really hurt me was Supabase. Previously the connection felt clunky, which is a dealbreaker for workshops where people already have a lot to learn. Now this part is much better. v0 can create Supabase tables and functions for you, and the integration is clearly evolving.
There are still a few constraints. GitHub export is one way only. Not so great if you want to bounce between tools. It also breaks my flow for precises Figma export “Figma MCP → Cursor → v0” loop, which requiresBo two way sync.
On the positive side, v0 has gone hard on integrations. You get an AI Gateway where you can plug in multiple models, including Claude, Gemini and OpenAI, plus deep integration with Vercel hosting. That makes it strong if you are already in the Vercel ecosystem and comfortable with React.
The tradeoff is that v0 is very opinionated about the stack: React, Tailwind, shadcn/ui. That focus buys you quality and consistency, but it also means it will not ever use MUI or other opinionated UI libraries, let alone different frameworks.
Bolt and Replit
On the other hand, Bolt and Replit really shine on framework flexibility.
Both can scaffold full stack apps across multiple stacks: React, Angular, Vue, React Native and others. Bolt in is positioned as “prompt to full stack app” in the browser. Replit is closer to a full development environment with a strong AI agent, where you can prompt an app into existence, keep editing it, and then deploy from the same place.
You get a lot of control, but the price you pay is complexity. Replit is incredibly powerful, but it feels more like developer environment than a low code tool.
Bolt has also grown a lot in the last months. They also have a built-in backend and database, powered by Supabase under the hood (sames as Lovable). At the same time, I still find the UX a bit rough, and it tends to generate more bugs that require more debugging.
If you absolutely need Angular, or let us say a React Native app for App Store release, Bolt and Replit are the more natural fit. For someone who just wants to spin up a quick demo and does not really care what stack it uses, Bolt and Replit might feel overwhelming.
On the GitHub side, both can work with real repositories with two-way sync. Bolt supports full GitHub sync, and Replit makes it easy to import and export entire projects, not just single files. That is something most of the low code tools still cannot do well.
Figma Make
Figma Make is in a league of its own simply because it starts where so many designers already live: Figma.
Where it really shines is precision. It can implement your Figma designs as prototypes that stay visually close to the original layout and styles. For designers, this feels like magic.
The problems begin once you try to treat that output as “real app code”. The generated code can be awkward to reuse outside Figma, and even inside Make things get messy when you start layering your own logic and structure on top.
To their credit, Figma Make is moving fast. You can connect to Supabase for backend and database, but I wish it worked with fewer bugs. Recently they also added Gemini 3 to boost the quality, let us see if it can make a difference.
Cost wise, Make has a nice advantage. If you already use Figma, you essentially get it “for free”.
For now, I still see Figma Make as great for breathing life into your Figma designs and getting richer prototypes under one roof, not yet as my go to for production ready applications. And get ready to fight weird bugs, as there are a lot more of them in Figma.
Magic Patterns
Magic Patterns sits somewhere in between design playground and app builder.
The part I like is its focus on exploration. You can spin up lots of variations of the same idea, place them on a canvas and compare them side by side. The canvas also supports light collaboration, so you can walk stakeholders through multiple options in one place.
They now support Figma import, use OpenAI models via your own key, and have been gradually improving API and database integrations. But compared to Lovable or Bolt, the backend and data story is still weaker and less intuitive. Clearly their primary focus is on prototyping and exploring variations, not on shipping full internal tools with complex logic. And I think it is a little too small of a purpose, I would go for a tool that is more versatile.
Cursor
Cursor is in a different category. It is not a low code AI prototyping tool. It is an AI powered IDE.
Cursor is what I reach for when I need to work in a real codebase, not when I want to avoid code entirely. It has strong awareness of your whole project, support multiple coding AI models, and multi agent workflows that can plan, edit and refactor across large repositories.
Another Cursor superpower for design work is its ability to work with Figma MCP, which is the best way to convert Figma designs into meaningful code. Ironically, it works better than Figma Make.
Unlike other tools in the list, Cursor does not come with one click deployment, built in databases or a low code UX. You bring your own stack and integrate your tools of choice manually: Supabase for backend, Vercel for deployment, etc. Cursor will help you wire things together, but you have to ask for everything explicitly and understand at least the basics of what it is doing.
The upside is control. You can import existing products and work on huge repos. It plays well with tools like Lovable via GitHub, which for me is the ideal flow: prototype fast in Lovable, then graduate the project into a proper repo and continue in Cursor when it gets serious.
I would not recommend Cursor as a starting point for someone who is just discovering vibe-coding, but it can be a natural next step once you hit the ceiling of low code tools.
Conclusion
The good news in all of this: all those tools above are doing magic. And things that are important for me might not be important for you. Whichever tool you decide to start with, it will give you enormous superpowers and will allow you to do a lot more and faster. You can always change when you feel like one tool is not cutting it. They are very similar in the way they work and how you need to prompt them. Once you master one of them, you become proficient in any other. So do not overthink it, just pick the option that smiles at you, test it out, and when you hit a limit, see if any of the other tools would solve this for you better.
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nice write up, I think there’s also other considerations which is how well these tools fit into an existing codebase (production) and how well they work with existing deployment pipelines. If not then PMs / Designers etc end up creating almost production like code but don’t have the scrutiny of tests / linting and how it all works with everything else. Whilst it can be valuable to rapidly prototype etc I think closing the gap between toys / validated ideas / working code and customer value needs to be closed over time.. (at least in the context I care about).