Summary:
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On a small island off the coast of Sweden, Damien launched Lovable with a Renaissance-style portrait idea.
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Lovable turned into a $300,000/month business without prior funding, offering non-technical users a software creation platform.
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The platform’s success story reflects a new economy for both non-technical founders and large enterprises creating value with AI.
On a small island off the coast of Sweden, a man named Damien had a simple idea. He wanted a Renaissance-style portrait of his dog, the kind of thing you’d hang on a wall like old-world royalty. He had no engineering background. He had no funding. What he had was a prompt and a platform called Lovable.
Today, that experiment is a business generating $300,000 a month.
“I couldn’t believe it at first,” said Anton Osika, founder and CEO of Lovable, recounting the story on a recent episode of The AI Download with host Shira Lazar. “But he has so many people who want portraits on their wall of their dogs. It’s a painting that is making $300,000 per month on this business.”
It is, Osika says, just one of hundreds of stories like it.
Lovable, the Stockholm-based startup that launched its product in late 2024, has grown into one of the fastest-expanding companies in the history of software by a number of measures. It reached $100 million in annual recurring revenue faster than any company on record, crossed $200 million around its one-year anniversary, and was at $300 million ARR by the time Osika spoke with Lazar in early 2026. The company’s recent funding round valued it at $6.6 billion.
The platform works by letting users describe what they want to build in plain language, then generating a fully functioning, deployable web application from that description. The output can include payment processing, email functionality, AI integrations and a live domain, without any code written by the user.
“The 99% were never able to create software,” Osika told Lazar. “But now anyone can create software. They just need an idea and they need to start.”
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The term that has emerged for this kind of conversational, iterative development process is “vibe coding,” a phrase attributed to AI researcher Andrei Karpathy. The underlying idea, as Osika traces it, is that natural language has become a functional programming interface. For people without technical backgrounds, that shift matters because access to software development has historically required either capital, coding skills, or both.
“A lot has stopped me as a creative in the past from building,” Lazar said during the interview. “Because you would need to raise money, maybe hire tech folks, engineers. That has slowed a lot of us down, or not even slowed us down. Stopped people.”
A New Economy for the Non-Technical Founder
The users building on Lovable are not limited to individuals with side projects. Enterprise adoption has grown alongside consumer use. Osika pointed to Exp Realty, a global real estate company with 80,000 agents operating across dozens of markets, as one example. The company had been quoted a year-long timeline and millions of dollars to rebuild its marketing platform through traditional channels. After finding Lovable, the team rebuilt it themselves.
“They built out a full platform where they could save $2 million,” Osika said. “And this is a very large company.”
Other organizations Osika referenced include Microsoft, HCA Healthcare and several Fortune 100 companies that have incorporated Lovable into internal workflows. The user base across the platform spans entrepreneurs building their first products, designers and product managers at large companies, and professionals in fields like healthcare creating tools specific to their own operations.
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“We’re seeing dozens of really large companies who are using Lovable,” Osika said. “Most of them just sign up and they see, ‘Wow, this is creating so much value in my role at the company.'”
Lovable now reports more than 300 million monthly visits to applications built on its platform, with more than 130,000 new projects created each day.
The question of what AI-powered tools like Lovable mean for workers in technical and adjacent fields comes up consistently in public conversations about the sector. Osika addressed it directly in his conversation with Lazar.
“There’s this ‘always going to take jobs’ mindset. I think this is the wrong perspective,” he said. “It’s a fixed pie mindset. And we’re now like baking entirely new pies that you can take a slice of.”
His position is that tools like Lovable create economic opportunity rather than simply eliminating it, citing the founders using the platform to build businesses in categories that did not previously exist. He acknowledged that some roles will shift, and suggested that leaning into new capabilities rather than defending current ones is the more durable response.
“If you are in one of the roles where AI is impacting, like, ‘Oh, it’s going to do this thing automatically,’ then especially I think you should lean into what is very exciting about what you can do now with AI,” he said.
How that transition plays out in practice, particularly for workers whose roles are disrupted faster than alternatives emerge, is a broader question Osika did not fully resolve. His framework was optimistic and structural, shaped by a belief that technology historically creates more economic activity than it displaces, even when the transition period is difficult for individuals. That view is shared by many in the AI industry, and contested by labor economists and researchers who study the pace and distribution of automation’s effects.
“A lot of people are just building because they love to create,” Osika said. “It’s very rewarding to have an idea or be creative and then being able to express that.”
Lovable launched with eight people and has maintained a relatively lean team structure through its growth. Osika described this as both a product of the tools available to them and a deliberate cultural choice.
“I spend a lot of my time with a great leadership team, and I care a lot about culture and how we work together,” he said. “That means creating an environment where people can just autonomously take decisions and use their best judgment to improve the product.”
The traits he hires for center on intrinsic motivation and initiative. “In our company values we talk about ‘driver, not a passenger,'” Osika said. “Some people are very good at thinking end-to-end and being proactive about solving problems, instead of just saying, ‘Oh, this is how it is, I’m going to wait until someone else takes the initiative.'”
He also named adaptability as a core attribute, particularly in an environment where the tools and possibilities are changing faster than any fixed expertise can track.
As Lovable’s platform has grown, so has the question of what safeguards govern what gets built on it. Osika described a set of security measures baked into the product architecture, including vulnerability scanning across all projects, a controlled process for handling API credentials, and automated screening for applications that may attempt to deceive or manipulate users.
“We make the software building security from the ground up,” he said. “All the software is scanned for vulnerabilities, and you can only put in API secret keys in a safe way.”
He also addressed privacy concerns about how user data is handled. “If you put something into Lovable, unless you actively set it to share, it is going to be only for you,” Osika said. “It’s not like we’re putting it into the AI. Then it learns it either.”
On the broader question of AI safety at the systems level, Osika acknowledged the risks that come with building increasingly capable AI, while expressing confidence in the ability of humans to maintain meaningful oversight.
“If we’re building intelligence that’s more intelligent than humans, and we give it a lot of control, and we don’t have a system where humans are fundamentally in control, then there’s a risk,” he said. “But as long as there is humans who are in control of AI, and we’re already using AI to become better at understanding what future do we want, I think that’s going to be the way that we play much more positive-sum games.”
Lovable has been rolling out agentic features that allow users to queue multi-step tasks and let the platform operate independently for longer stretches, including testing and iterating on the application it just built.
“You can ask people to go out and work for like 10 minutes, for 20 minutes,” Osika said. “You can queue up — like, I wanted you to do all of these things.”
The broader roadmap, as Osika described it, points toward software that is not just built by AI, but continuously informed by it, with AI embedded inside the applications themselves rather than only in the process of creating them.
“We’re going to see a new type of interaction between the software applications that you built and the AI, where you can access it like you do now, and you also can talk to an AI that has context about the application you’re in,” he said.
The goal Osika has articulated for Lovable since its founding is to become the single destination for anything a person might want to accomplish with software. Whether a platform can hold that position as the tools and competitors around it evolve is an open question. But for the users building on it today, the practical reality is already a meaningful shift from the world that came before.
“A new tool to create economic opportunities,” Osika said. “It’s like a new economy.”
Watch the full interview with Anton Osika on The AI Download at https://youtu.be/jr9ESVOtyMo
Shira Lazar hosts The AI Download on YouTube and all major podcast platforms. She is also the CEO and founder of WhatsTrending. Subscribe to her weekly newsletter, The Alpha, at shiras-newsletter.beehiiv.com.
