We’re sending a message to the world: make it yourself.

The future of enterprise software is everyone being able to build, without compromising on security. Today, we're making that possible with new @Lovable Enterprise capabilities: → Companies can deploy apps in their own AWS or Azure cloud → Keep AI inference within the EU → Manage access, security, and approvals centrally → Give IT full visibility and control The goal is simple: give everyone the freedom to build, while giving enterprises the control they need to ship. Read in full: lovable.dev/blog/enterprise-…

If history tells us anything, it's that the long-term impact of new technology is difficult to anticipate from its earliest applications. It took smartphones more than a decade to reach 80% of people in the US. One of the most important moments in smartphone adoption came in 2008, when Apple launched the App Store. What followed was an entirely new wave of companies. Uber, Instagram, and Spotify recognized what became possible when millions of people had a computer in their pocket. They built products around changing human behavior and created markets that barely existed before. There's an important distinction between advancing a technology and making it useful to society at scale. The existence of a powerful technology doesn't automatically translate into widespread adoption, just as the invention of the internet didn't immediately produce the digital economy we know today. It takes human and institutional behavior change to unlock the potential of new technology. The smartphone made new business models possible, but it was the applications that gave people more reasons to use the technology every day. We're in a similar situation with AI. We've made extraordinary progress in developing increasingly capable models. But we're much, much earlier in the transition than people realize. We're measuring intelligence, comparing models, discussing agents, and anticipating the next breakthrough. All of that is important, but technological progress, and behavioral transformation, don't happen at the same pace. If history repeats, today won’t be seen as the moment when we had already figured out AI’s most important applications. Instead, we’ll look back and see it as the moment when key foundations were established for new business models, habits, and industries that would emerge over the following decades. And I think right now is a rare moment because the possibilities created by technology are expanding faster than our understanding of what to do with them. The opportunity isn't simply to experiment with new software. It's to develop a deeper understanding of the world around us: how people behave, where existing systems fall short, and which problems remain unsolved. In this era, the most consequential changes to human behavior, and companies manifesting them, may not be built by those who understand AI best, but by those who recognize what becomes possible when technological capabilities meet a deep understanding of human needs. The greatest impact of a general-purpose technology is rarely determined by what its inventors imagined. It's determined by what millions of others eventually discover they can do with it. Humanity is just getting started.