Artificial intelligence agents are no longer confined to research labs. With the advent of advanced orchestration and memory systems, AI is now stepping confidently into real-world workflows.
At the forefront is Gemini 3, a technology that gives developers precise control over how agents reason, maintain state, and operate reliably. Instead of just conceptual models, Google is showcasing practical, open-source examples that highlight how Gemini 3 is transforming agentic AI across diverse sectors.
Building Scalable Agents with the Agent Development Kit
Google’s Agent Development Kit (ADK) is an open-source toolkit designed to bring the rigor of traditional software engineering to AI agent development. By leveraging Gemini 3, ADK orchestrates various specialized agents, think data gathering, code execution, or image generation, into unified workflows.
For example, the Retail Location Strategy sample combines search, analytics, and visualization, all managed by Gemini 3. Developers can easily customize and extend these workflows using the open ADK samples found in the Agent Garden.
Advanced Reasoning with Agno
Agno, previously known as Phidata, empowers developers to create robust multi-agent systems with integrated memory and tool support. In its Gemini 3-powered demo, Agno features a Creative Studio for image generation and research agents that ground their responses using Google Search and contextual URLs. This setup demonstrates how Gemini 3’s core capabilities enable agents to synthesize and analyze information for creative and research-intensive tasks.
Resilient Browser Automation
Browser Use bridges large language model (LLM) reasoning with practical browser automation. Using Gemini 3 Pro, it powers agents that can visually identify web form fields, upload files, and manage complex multi-step workflows. This multimodal approach makes automation more adaptable and robust, reducing dependence on brittle selectors and enabling reliable actions across different websites.
Enterprise-Ready Automation with Eigent
Eigent is tailored for enterprises, focusing on local-first, secure agent orchestration. By integrating Gemini 3 and the CAMEL framework, Eigent automates intricate business operations, such as Salesforce deal management, using specialized agent teams. Here, Gemini 3’s "thought signatures" help agents maintain state and reasoning across long, multi-step processes, minimizing context loss and operational errors.
Long-Term Memory in Social Agents with Letta
Letta is pushing the boundaries of AI memory management through its innovative memory hierarchy. In demos powered by Gemini 3, Letta deploys social agents that can sustain long-term, personalized interactions. By maintaining persistent, dynamic memory blocks for each user, these agents evolve their personas and behaviors, addressing the enduring challenge of context retention in conversational AI.
Personalized Interactions with mem0
mem0 provides a smart memory layer for Gemini 3-powered agents, enabling them to remember user preferences, histories, and nuanced context. Integration with the mem0-mcp-server allows agents to rapidly adapt to evolving user needs, resulting in more effective and responsive experiences. This tackles the traditional statelessness of LLMs, paving the way for more capable, memory-aware applications.
The Road Ahead for Agentic AI
The era of effective, real-world AI agents is here, driven not just by advanced models but by an ecosystem of supporting frameworks and tools. Gemini 3’s orchestration, memory, and multimodal strengths empower developers to build agents that reliably reason, remember, and act. Whether you’re interested in enterprise automation or personalized assistants, exploring these open-source examples and tools can help unlock the full potential of agentic AI. For more in-depth technical guidance, the Gemini 3 Developer Guide is an excellent resource.
Source: Google Developers Blog – Real-World Agent Examples with Gemini 3
How Gemini 3 Is Powering the Next Generation of Real-World AI Agents