An Interaction Is All You Need — Ivan Leo, Google DeepMind
Ivan Leo introduces the Gemini Interactions API and Managed Agents, addressing the architectural gap between simple model completions and complex, multi-step agentic workloads. The new APIs enable robust, stateful, and multimodal pipelines by introducing the `interaction ID` for context preservation and the `environment ID` for persistent, remote sandboxes. This allows developers to build sophisticated agents that can autonomously reason, use mixed tools, and handle complex data types (image, video, audio) without managing underlying infrastructure.
Key takeaways
-
State Management via Interactions API
8:51
The new API uses a persistent `interaction ID` to maintain context across multiple API calls, replacing the difficulty of manually managing thought signatures and ensuring performance consistency with the Gemini series of models. (5:31)
-
Persistent Remote Sandboxes (Managed Agents)
15:01
Managed Agents utilize the Anti-Gravity harness to provide persistent, remote sandboxes via an `environment ID`. This eliminates the need for developers to manage infrastructure or context preservation between agent runs. (9:01)
-
Advanced Multimodality and Tooling
10:21
The API supports chaining different modalities (image, video, audio) and mixing built-in tools (e.g., Google Search) with custom tools in a single, complex workflow, all managed by the new steps data model. (6:21, 8:21)
-
Security and Scalability
Security is enhanced with a man-in-the-middle proxy that intercepts outbound calls, preventing credential leakage even if the model is prompt-injected. The system supports up to 1,000 named agents without additional storage costs. (11:20)