AI frontend work needs to function when the screen is empty, and that is where I want to start comparing Gemini. A good-looking interface full of content gets attention quickly. Remove the data and you discover whether anyone decided what the user does next. That part belongs in the request from the beginning.
In May 2026, Google introduced Gemini 3.5 Flash with a focus on agents and programming, available through its tools and API. Antigravity was among the access points. Revisiting that launch, my interest comes from a later conversation: in July 2026, I suggested trying Gemini for frontend work and comparing models by function. That suggestion opens an experiment; I have no result from it to announce.
In the same July conversation, I assessed Claude as good for backend work. That does not commit me to the same provider for every screen. I want to assign work according to what each option delivers, without making a model preference my personality. A project already has enough decisions without adding a fan club.
My next interface test starts with a small request: the same screen with and without content. The empty state needs to explain what is missing and offer a sensible action. When data arrives, the screen should remain coherent. These are two moments in the same task, easy to inspect without relying on excitement about the first image.
Then comes reading the code. I need to understand where to make changes when the request evolves. If an implementation choice helps the objective, its explanation can point to that connection. A justification that fits any interface just adds reading. The agent can skip the sales presentation for its own code.
I will also record where the comparison happened. Gemini in an API and Gemini inside a tool reach the work through different routes. Access to the project and available integrations belong to the experience. Otherwise, an advantage of the application turns incorrectly into a conclusion about the model.
My decision is to put Gemini into contention for a bounded frontend deliverable. I will count additional guidance and check whether I can keep changing the solution after the first response. If it handles the populated screen and returns the rest of the flow as homework, the task is unfinished. The next round starts with what was left out.