Google has unveiled Gemini 3.0, its new generative AI, and "Antigravity" (1), a next-gen IDE powered by it. Google states that "Google Antigravity is our agentic development platform, evolving the IDE into the agent-first era," signaling a shift toward truly agent-centric development. Here, I’m going to task Antigravity with creating a "Bank Complaint Classification App." I want to actually run it to explore its potential.

1.Agentic Development with Antigravity

Antigravity is built on top of VS Code. If you are a VS Code user, the editor will look familiar, making it very approachable and easy to pick up. However, the real power of Antigravity lies in its dedicated interface for agentic development: the Agent Manager (shown below). Just enter a prompt into the box and run it to kick off "Vibe Coding." The prompt shown here is the very simple one I entered at the beginning of the development process. Antigravity also appears to be packed with various features designed to facilitate efficient communication with the Agent. For more details, please check the website (1).

2. Prompt Refinement and Improvement

Just because you start "Vibe Coding" doesn't mean you'll get perfect code immediately. I started with a simple prompt this time as well, but the process proved to be more challenging than anticipated. While Gemini 3.0 Pro often demonstrates human-level capability when handling HTML and CSS for website building, the framework used for this app—Google ADK—is a brand-new agent development kit that just debuted in April 2025. Consequently, there are likely very few code examples available on the web, and I assume it hasn't been fully absorbed into Gemini 3.0's training data yet.

It was quite a struggle, but as shown above, I managed to build a fully functional app via "Vibe Coding." To generate these files, I relied solely on natural language instructions; I didn't write a single line of code directly in the editor. However, I did include simple code snippets within the prompts. This is a technique known as "few-shot learning," where you provide examples to guide the model. I believe this approach is highly effective when Vibe Coding with Gemini 3.0 for Google ADK development. While this might become unnecessary as Gemini 3 is updated in the future, it’s certainly a technique worth remembering for now.

Bank Complaint Classification App using Google ADK

The screenshot above shows the "Bank Complaint Classification App" I developed. I verified its accuracy with some simple examples, and the results were excellent. It seems the internal prompts within the app were generated very effectively. Impressive work!

3. Summary of Building a Complaint Classification App with ADK

Total Time: 6 hours (starting from the Antigravity installation) to complete the app.
Execution: With the finalized prompt, the run time is just over a minute.
Manual Effort: The actual coding for Google ADK to make the app is only about a 20-minute task if done manually without vibe-coding.
Reasons for the Delay:
- I had to iterate on the prompts several times because Gemini 3 is still unfamiliar with Google ADK
- I had to explicitly instruct it on file structures and code syntax.
- I was also using Antigravity for the first time.
Conclusion: It is manageable once you understand Gemini 3 Pro's behavior regarding Google ADK.

So, what do you think?

It took a little longer because I wasn't used to the new IDE yet, but the combination of Gemini 3.0 Pro and Antigravity was outstanding. I could really feel its high potential. Since the execution speed itself is fast, next time I plan to challenge myself by "Vibe Coding" a multi-agent app. Look forward to it! That's all for today. Stay tuned!

You can enjoy our video news ToshiStats-AI from this link, too!

1) Experience liftoff with the next-generation IDE, Google, 19 Nov 2025

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