Google Cloud Next ‘25 Developer Keynote in 15 minutes
AI Summary
Summary of Google Cloud Innovations in Software Development
- Introduction to Google Cloud’s Agentic Applications
- New tools: Agent Development Kit, Agent Engine, Agency Space.
- Aimed at building applications that enable user-agent collaboration.
- Enhanced Developer Productivity
- Utilization of Code Assist and Cloud Assist agents to streamline development and cloud operations.
- Innovations powered by Gemini models with multimodal support.
- Demonstration of New Features
- Introduction of new UI in AI Studio.
- Features include native image editing and Google search integration.
- Examples of practical applications such as kitchen remodels using Gemini.
- Defining Agents
- Agents perform goal-based operations using AI models.
- Creating agents involves defining an instruction, selecting tools, and utilizing models.
- Vertex AI serves as the platform for building and managing AI agents.
- Building an Agent
- Steps for creating an agent with ADK: Connect to Gemini, define an instruction, and utilize tools like Analyze Building Codes.
- Tools use retrieval-augmented generation (RAG) for processing requests.
- Deployment
- The agent engine simplifies deployment and provides security controls and monitoring.
- Agent Space allows developers to build and register agents centrally.
- Demonstration of Multi-Agent Systems
- Showcased integration of multiple agents (proposal, permits, materials) using ADK.
- Improved debugging through Cloud Assist Investigations.
- Expanding Agents Across Ecosystems
- Introduction of the Agent-to-Agent Protocol (A2A) for connecting agents from different systems.
- Integration with IDEs
- Gemini available in various IDEs to assist with coding tasks directly.
- Support for multiple models through Vertex AI Model Garden, including Llama and Claude.
- Future Directions in Development
- Emphasis on orchestrating agents to improve software development workflows.
- Preview of projects, task assignments, and automation capabilities within development environments.
- Conclusion
- Encouragement for developers to leverage these tools to innovate in software development.
- Focus on immediate applications of AI technology for current projects.