Google Brings Key Updates to AI Agents, Announces Gemini 2.5 Flash
At the Google Cloud Next 2025 event on Wednesday, Google announced numerous key updates regarding AI agents. The newly announced tools, protocols and frameworks help developers and enterprises effectively build, connect, and deploy agentic systems across their ecosystems. Furthermore, the company also announced another family in the Gemini 2.5 family of models—the Gemini 2.5 Flash. Google’s New Agent Development Kit and Agent2Agent Protocol To begin with, Google announced the new Agent2Agent (A2A) protocol, which facilitates the connection of AI agents within an enterprise ecosystem. The protocol enables AI agents to communicate with one another, irrespective of the framework or vendor on which they are built. “A2A facilitates communication between a ‘client’ agent and a ‘remote’ agent. A client agent is responsible for formulating and communicating tasks, while the remote agent is responsible for acting on those tasks in an attempt to provide the correct information or take the correct action,” Google stated. Moreover, A2A is an open protocol that complements Anthropic’s Model Context Protocol (MCP), which helps connect data sources with AI systems. The company has already established partnerships with over 50 organisations, including Deloitte, Accenture, Oracle, Salesforce, and others, to collaborate on the protocol. At the event, Google announced the Agent Development Kit (ADK), an open-source framework for designing AI agents and multi-agent systems while maintaining control over each other. While it currently supports Python, more languages will be supported later this year. The company also announced ‘Agent Garden’, a collection of pre-built agent patterns and components to ‘accelerate’ the development process. ADK also allows agents to be connected directly to enterprise systems. “This includes over 100 pre-built connectors, workflows built with Application Integration, or data stored within your systems like AlloyDB, BigQuery, NetApp and much more,” Google said in the announcement. New Agent Engine to Deploy AI Agents With Ease Moreover, the company announced Agent Engine, which allows developers to deploy AI agents built using any framework and AI model. “No more rebuilding your agent system when moving from prototype to production. Agent Engine handles agent context, infrastructure management, scaling complexities, security, evaluation, and monitoring,” it added. Agents hosted on Agent Engine can also be registered on Google Agentspace, for which the company also announced a few updates. Google Agentspace offers an enterprise search agent that answers questions using company data, alongside a central hub for custom AI agents that help employees research, create content, and automate tasks. Google also announced that, starting today, Agentspace will be integrated with Chrome Enterprise edition. This means employees can utilise its search capabilities directly from Chrome. Google is also introducing a new Agent Gallery, which gives employees a single view of all available agents across the enterprise. In addition, the company is also introducing an Agent Designer in preview, which offers a no-code interface for creating agents that connect to enterprise data sources to complement various tasks. Gemini 2.5 Flash is Here Moreover, at the event, Google announced the Gemini 2.5 Flash model. It will be available on Google’s Vertex AI and Google AI Studio. Google promotes the Gemini 2.5 Flash as a “workhorse model”, designed for low latency and cost efficiency. The model is also said to adjust reasoning time based on query complexity. Users can control reasoning by adjusting speed, accuracy, and cost. The Gemini 2.5 Flash is the successor to the Gemini 2.0 Flash, which outperforms Llama 3.3 70B and OpenAI’s GPT-4o mini models. Recently, Google released the Gemini 2.5 Pro, which leads several benchmarks as the top frontier AI model. Furthermore, numerous developers across the internet have hailed the Gemini 2.5 Pro as the best AI model for coding. To help users choose the appropriate model, Google is also introducing an experimental Vertex AI Model Optimiser that generates the highest quality response for each prompt based on the desired balance of cost and quality. Google also announced that Gemini will be available on Google Distributed Cloud (GDC), with public preview starting in Q3 2025. The company has partnered with NVIDIA to bring Gemini models to NVIDIA Blackwell Systems. GDC extends Google Cloud’s infrastructure and services to on-premises data centers and edge locations, enabling organisations to run applications closer to their data sources. Furthermore, Google unveiled the seventh generation of its tensor processing unit (TPU), Ironwood. The TPU supports two configurations—one with 256 chips and another with 9,216 chips. Ironwood’s performance/watt ratio is two times greater than the sixth generation, Trillium. Ironwood also offers 192 GB per chip, six times that of Trillium.
The company announced several new techniques and frameworks to build and deploy AI agents.
The company announced several new techniques and frameworks to build and deploy AI agents. 
["AI (Artificial Intelligence)", "Google", "Google Gemini"]
["Anthropic", "Gemini 2.0", "TPU", "OpenAI", "AI", "GPT-4o", "Google Gemini", "Python", "Gemini 2.5", "multi-agent systems", "Google", "R", "AI (Artificial Intelligence)"]
["AI", "GPT-4o", "OpenAI", "Anthropic", "Gemini 2.5", "Gemini 2.0", "multi-agent systems", "TPU", "Python", "R"]
Supreeth is an engineering graduate who is curious about the world of artificial intelligence and loves to write stories on how it is solving problems and shaping the future of humanity.