In Google I/O 2026 the conversation is no longer just about models that answer: it’s about agents that act. Google unveiled Gemini 3.5 Flash and a wave of tools to create, deploy, and orchestrate agents — from desktop to Android — with the aim of moving developers from prompts to real agent workflows.
What changes for developers
Can you imagine not only asking the AI to generate text, but handing it complete tasks and having it execute them reliably and quickly? That’s exactly what Google is pushing with this batch of announcements.
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Gemini 3.5 Flashpromises to be faster: Google says it runs four times faster than other frontier models and outperformsGemini 3.1 Proon almost every benchmark. In practice, speed means more responsive agents and less frustrating interactive flows. -
New agent-first approach: Antigravity and Managed Agents aim to turn ideas into productive apps without you building all the infrastructure from scratch.
The bet is clear: less friction in infrastructure, more time to iterate on agent logic.
Antigravity: the ecosystem to build agents
Antigravity evolves into a full ecosystem for developing agents. If before you only had APIs and models, now there are layers designed for production.
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Antigravity 2.0 (desktop app): an agent-centered interface, with dynamic subagents for parallel workflows, scheduled tasks, and connections to Google AI Studio, Android and Firebase.
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Antigravity CLI: for those who prefer the terminal. Create agents instantly without a GUI. Google suggests
Gemini CLIusers migrate here. -
Antigravity SDK: programmatic access to the same harness Google uses, optimized for Gemini models. Ideal if you want to run agents on your own infrastructure.
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Enterprise integration: connect Antigravity directly to Google Cloud projects to simplify workloads at scale.
Also, Google launches a Google AI Ultra subscription from 100 USD/month with 5x higher usage limits in Antigravity than the Pro plan, plus a 100 USD credits promotion (valid until May 25, 2026). If you’re thinking production, that’s relevant for cost planning.
Managed Agents in the Gemini API
The big headline is being able to spin up an agent with a single API call. These Managed Agents are powered by the Antigravity harness and Gemini 3.5 Flash.
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Persistent, isolated environments: each interaction creates an environment you can resume in later calls, with files and state intact. That makes multi-turn sessions that actually keep context much easier.
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Code execution and tool use: agents can reason, use tools, and execute code inside an isolated Linux environment.
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Easy customization: define instructions and skills with markdown files and use ready templates in Google AI Studio Playground.
If you’ve ever thought about agents to automate admin tasks or run software tests, here’s the technical capability to do it with less infrastructure pain.
Google AI Studio: from prototype to mobile and production
Google AI Studio integrates more deeply with Antigravity and the Google ecosystem:
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Mobile app for Google AI Studio (pre-register): capture ideas from your phone and arrive at the desktop with a working prototype.
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Workspace integration: agents can call Google Workspace APIs and embed results into your apps.
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Export to Antigravity: one click to take Studio projects to local development and production, keeping all context.
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Native support for Android and Play Console: you can now generate Android apps with prompts and publish them directly to a test track from Studio.
Imagine recording an idea on your phone, seeing a prototype in minutes, and testing an app on Android without wiring up complex pipelines. That speeds up the creation loop.
Build with Gemini XPRIZE: 2M USD hackathon
Google launched the Build with Gemini XPRIZE, a global competition with 2,000,000 USD in prizes. The goal is to incentivize real solutions using Gemini and the announced tools: from reducing food waste to scientific research.
Finalists will present at the Moonshot Gathering in Los Angeles this September. If you’re a developer or lead a team, it’s an opportunity to build something with visibility and funding.
And what does this mean for you?
If you’re a developer: less time patching infra and more time designing agent logic. If you work in product: prototype faster and ship to production with less friction. If you’re an entrepreneur: new windows for agent-powered products that used to need larger infrastructure investments.
Not everything is magical: there will be security, governance and operational cost challenges, especially when agents run code and handle production data. But the trend is clear: AI stops being a black box of answers and becomes an active engine inside applications.
The simple question left is: what agent will you build first?