Google's AI tools for developers and enterprise, and when to actually reach for each

Beyond the consumer surfaces most people know, the Gemini app and Gemini Notebook (formerly NotebookLM), Google offers a whole set of AI tools and interfaces built for developers and enterprise teams. At first glance, it's a lot to wrap your head around. AI Studio, Gemini Enterprise Agent Platform, the Gemini Enterprise app, Antigravity in its various forms. The names overlap, the marketing language overlaps, and it's not obvious where one tool's job ends and another's begins.

AI Studio is where you test a prompt, try a multimodal input, or compare models before committing to anything. It also builds full applications straight from a prompt, complete with backend infrastructure. When your app needs to store data or handle sign-ins, AI Studio provisions a database and authentication for you, either Cloud Firestore or Cloud SQL for a relational setup, and Firebase Authentication, without you configuring any of that by hand. It also connects to Google Workspace APIs, so an app you build there can work with a user's real Gmail, Docs, Sheets, or Calendar data. It supports mobile app development as well, for native Android apps.

Use AI Studio when you want to validate an idea or ship a lightweight web or Android app fast, with real backend support, and without provisioning any Google Cloud infrastructure yourself. This is the next generation of Vertex AI. Google folded Vertex AI's entire service catalog, model access, custom training, evaluation, pipelines, all of it, into what's now called the Agent Platform. If you go looking for Vertex AI in the console today, it redirects you here.

This is the one-stop shop for the full agent development lifecycle. You build with Agent Studio, the low-code visual builder, or the Agent Development Kit for code-first development in Python, Go, Java, or TypeScript. Agent Engine handles the managed runtime, Model Garden gives you access to over 200 models including Gemini and Claude, and the governance layer, IAM, VPC-SC, compliance controls, gives a production agent what it needs to survive a security review.

Use this when what you're building needs to act with real autonomy inside your enterprise environment, holding state and making decisions across steps. This is the surface your non-technical colleagues will actually touch. A SaaS chat interface, grounded search across Drive, SharePoint, and Jira, no-code agent creation for business users, all without opening the Agent Platform directly. If your job is to register, govern, and hand off an agent so people across the org can use it, this is the distribution layer.

The Agent Platform builds the agent. The Enterprise app is how it reaches an employee, packaged for their actual job.

Each piece in the bundle enables a different way of working with the same underlying coding agent.

Underneath all of them sits the same agent harness, the actual execution engine that runs code, executes shell commands, browses the web, and does the multi-step work autonomously. It powers the IDE, the CLI, and the SDK from underneath, so improvements to the core agent land on all three surfaces at once.

Once you know what each of these actually does, the overlapping names stop being confusing. AI Studio for prototyping and lightweight apps, the Agent Platform for production agents, the Enterprise app for distribution, Antigravity for the coding work itself. Pick based on what you're building and who it's for.