PublicSelf started with a straightforward idea: help people create intentional personal images, test looks, and build brand assets through AI. When I began, image models moved slower. I thought there was enough runway to build a structured tool before the major platforms made personal image generation effortless for everyone.
That assumption was wrong.
The rapid evolution of large model providers has erased that buffer. Many standalone product opportunities from a year ago are now standard features inside ChatGPT, Gemini, and Midjourney. For PublicSelf to survive as a commercial product, it can't just generate images; it has to win on a much more specific problem.
Because of this, the project's purpose has shifted.
It is still a functional workflow tool exploring identity consistency, reference images, and multi-model integration. But it has also become my R&D lab. Building a web app, a mobile version, and the infrastructure to handle prompt structures and quality control is incredibly labor-intensive. Even if it doesn't become a massive commercial hit, this work keeps me close to the tech.
There are still viable paths forward. PublicSelf could pivot into a highly focused niche, serve a specific creative community, or succeed as a curated, guided workflow layer that native tools ignore.
For now, I'm treating it as an internal engine.
I don't know its final shape yet, and that uncertainty is real. PublicSelf might become a standalone product, it might become infrastructure for my other projects, or it might just remain a powerful tool for my own use. Either way, the build is worth it—it's teaching me exactly where the shift from single-prompt generation to repeatable, intent-driven visual workflows is heading.
