What if you can build an Agent with it own computer in a single api call?
TL;DR · AI Summary
Gemini Managed Agents combined with the Interactions API enables AI agents to have secure Linux sandbox environments for executing code and managing memory autonomously.
Key Takeaways
- A single API call allows building an AI agent with its own computing environment
- Gemini Managed Agents provide a secure hosted Linux sandbox for enhanced safety.
- The Interactions API supports autonomous code execution and stateful memory mana
Outline
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Gemini Managed Agents and Interactions API enable creation of AI agents with independent computing environments.
This solution provides a secure hosted Linux sandbox for code execution and memory management.
Demonstrated at Google I/O how these technologies enhance AI capabilities effectively.
Mindmap
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查看大纲文本（无障碍 / 无 JS 友好）
- Gemini AI Agent 构建方案
- 核心技术组件
- Gemini Managed Agents
- Interactions API
- 运行环境支持
- Linux 沙箱
- 自主内存管理
Highlights
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What if you can build an Agent with it own computer in a single api call?
I showed how to use Gemini Managed Agents and the new Interactions API to give your AI a secure, hosted Linux sandbox to execute code and manage its own memory.
At my @Google I/O talk, I showed how to use Gemini Managed Agents and the new Interactions API to give your AI a secure, hosted Linux sandbox to execute code and manage its own memory. https://t.co/M0TNWkcQYQ" / X
Philipp Schmid on X: "What if you can build an Agent with it own computer in a single api call? At my @Google I/O talk, I showed how to use Gemini Managed Agents and the new Interactions API to give your AI a secure, hosted Linux sandbox to execute code and manage its own memory. https://t.co/M0TNWkcQYQ" / X
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Philipp Schmid 
What if you can build an Agent with it own computer in a single api call? At my
I/O talk, I showed how to use Gemini Managed Agents and the new Interactions API to give your AI a secure, hosted Linux sandbox to execute code and manage its own memory.
[Video 2](blob:https://x.com/66d647d8-9b09-4b19-8b7a-47da492475b4)
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