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AI Ambition: ArtCraft Cloned Photoshop and Now Wants to "Rebuild Everything"

AI Ambition: ArtCraft Cloned Photoshop and Now Wants to "Rebuild Everything"

ArtCraft drew significant attention when it used generative AI tools to reconstruct much of Photoshop's functionality as open-source software - a project that would have required years of traditional engineering effort compressed into a far shorter timeline. The move positioned the company as an example of how AI-assisted development can allow small teams to take on entrenched, decades-old applications.

CEO Brandon Thomas has been vocal about the fact that replicating Photoshop was not the end goal but a proof of concept. In interviews, he has framed ArtCraft's mission as something more sweeping: using AI to rebuild foundational software and internet infrastructure on more open terms. The phrase "take back the internet" reflects a philosophy that too much of the creative and technical web is locked behind proprietary walls, and that AI now gives smaller players the leverage to challenge that.

The technical approach ArtCraft used is worth noting. Rather than building feature by feature over many years, the team leaned heavily on AI code generation to accelerate the replication of complex tooling - layer management, masking, compositing, and other core image-editing functions. This method does not eliminate the need for skilled engineers, but it does shift the work toward directing and refining AI output rather than writing everything by hand. For the open-source community, the result is a usable alternative to software that has historically had no serious free competitor.

Whether ArtCraft can follow through on its larger ambitions is an open question. Rebuilding a single application is a contained challenge; rebuilding internet-scale systems is a different order of magnitude. But the company's Photoshop effort at least demonstrates that AI-assisted development has matured to the point where cloning sophisticated, proprietary creative tools is a realistic project for a small team. If that approach scales, it could have real implications for how creative software is built, distributed, and owned going forward.

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