Lovable has dropped the barrier to entry for building apps and websites to almost zero.

Illustration by Mohit Pandey
‘Tech Twitter’, a term roughly used to represent a community of tech enthusiasts on X (formerly Twitter), is the birthplace of many great AI tools and also where plenty of tools die once developers discover better alternatives. Following the popularity of Cursor, GitHub Copilot, and Windsurf, Lovable is currently capturing developers’ attention due to its exceptional ease of use.
It turns out that Lovable has dropped the barrier to entry for building apps and websites to almost zero, making it possible for virtually anyone to become a developer. AIM tested Lovable and successfully built functional apps and websites within just an hour of prompting, without even touching a single line of code.
My friend, who's a barber, wanted me to create a landing page for his new course business.
This is a one-shot landing page built with @lovable_dev. Pretty crazy! 🤯
I tried 3 other tools, and Loveable's first version was the best this time. pic.twitter.com/m9pY28H1rF
For example, Dan Denney, a senior software engineer at DataCamp, managed to create a working web app without writing any code at all. In under three hours, his app was live on a real URL, syncing lists with his partner in real time. On his blog, he described how a rough sketch in Excalidraw turned into a fully functional app, powered by Lovable.
In another instance, when Shep Bryan, founder and chief AI officer at Galaxy Brain AI, began experimenting with Lovable, he had no idea he was about to log over 200 hours building more than 60 projects.
In a blog post, he shared that what started as curiosity soon became an obsession with understanding how to work alongside AI—not just to generate code, but to build full-stack applications collaboratively.
Worth the Hype?
Denney and Bryan aren’t the only ones. Across forums, social media, and developer groups, more developers are quietly—or sometimes loudly—gravitating towards Lovable, frequently choosing it over alternatives like Cursor, Bolt, or Windsurf.
Ahmer Sultan, product and software engineering consultant at a stealth startup, shared a similar experience. To compare Lovable and Cursor directly, he gave both the tools the same prompt for a landing page. Lovable executed immediately. “One big prompt → working landing page… clean and effective,” Sultan revealed.
Cursor, on the other hand, struggled. “It got stuck…I had to break the prompt into smaller steps…and still needed more trial and error.”
If your goal is to go from idea to prototype, Lovable is your best bet. However, if you’re already deep into a codebase and need finer control, Cursor may have an advantage. This sentiment was echoed by Prajwal Tomar from ignytlabs, who said Lovable can handle 80% of MVP design while Cursor can take care of the remaining 20% of execution.
How I use @lovable_dev + @cursor_ai to build MVPs 10x faster
This workflow helps me skip the design phase, automate 70% of the dev work, and stay flexible for rapid changes.
If you’re building with AI, you’ll want to see this. pic.twitter.com/0Nc0Jwib3Q
Just as Cursor became the fastest-growing SaaS in history, achieving $100 million in annual recurring revenue (ARR) within 21 months of its inception, Lovable is following a similar trajectory, scaling from zero to $17 million ARR in three months as of March. What began as an open-source tool for GPT Engineer, evolved into a full-fledged company after garnering 56,000 stars on GitHub.
One of the founders, Anton Osika, even acknowledged that dropping the barrier to entry to build products was the goal. “I always felt [that] building products takes too long. So I started Lovable to fix this,” he said during the product launch.
Backed by prominent figures like Meta board member Charlie Songhurst and Hugging Face co-founder Thomas Wolf, Osika, alongside Fabian Hedin—the inventor of Stephen Hawking’s computer interface—founded Lovable with the vision of “building the last piece of software”.
Lovable positions itself as an AI software engineer—not just a coding assistant. It’s not trying to write a line or two of helper functions; instead, it’s built to develop landing pages, wire backend, hook up APIs, and write thoughtful documentation.
INSANE: Grok 3 + Lovable = BEST AI Agent Apps!!!!
Grok 3 generated the code for an AI agent that manages your Gmail – send, reply, and draft effortlessly
Here's how it works:
– Connect with your Gmail using Composio
– Use Lovable to build an extremely cool frontend for the… pic.twitter.com/JMgwwf14vk
For All the Praise, Lovable Isn’t Without Flaws
Adithya S Kolavi, founder of CognitiveLab, told AIM that Loveable can ‘vibe code’ and build fully-fledged apps, complete with backend functionality. “Not only can it implement functional features effectively, but the UI it generates is also significantly better compared to competitors like Bolt or v0,” Kolavi said.
According to him, what stands out the most about Lovable is its solid implementation of an AI agentic system. “The user experience is smooth, and the integrations with Supabase make it truly viable for building end-to-end applications,” he added.
“It’s clearly more general user-focused. So, while it’s a bit difficult to directly edit code, it compensates with great GitHub connectivity and seamless workflows.”
A developer on Reddit took the rapid prototyping capabilities to the next level. In a self-imposed challenge, they built 30 apps in 30 days using Lovable. That journey went viral, drawing in half a million views on X. Yet, despite its success, just like other tools, Lovable is not without its flaws.
Complex backends continue to be tricky. While it handles Supabase well, developers have reported that anything beyond “standard setups” quickly becomes complicated. It’s also not cheap. Bryan noted that his preferred workflow sometimes takes two to three credits per feature iteration. This cost can add up quickly for hobbyists.
Furthermore, fine-grained control isn’t Lovable’s forte. When it comes to refactoring a specific section or handling intricate architecture work, tools like Cursor and GitHub Copilot continue to perform better.
Cursor, for instance, is ideal for structured, step-by-step coding. Developers who want to plan out architecture, split tasks into manageable pieces, and control execution every step of the way tend to prefer Cursor—even if it means more work upfront.
For early-stage founders, indie hackers, and experimental builders, it lowers the barrier to entry dramatically. Instead of waiting weeks to validate an idea, they can do it in a day.
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Mohit Pandey
Mohit writes about AI in simple, explainable, and sometimes funny words. He holds keen interest in discussing AI with people building it for India, and for Bharat, while also talking a little bit about AGI.
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