As models and harnesses improve, agents are taking on increasingly complex tasks that can run for hours or even days. But as we push agents to do more, this has surfaced a new operational problem: long-running agent workflows are fragile and incredibly hard to manage reliably and efficiently in production. Today, we’re introducing Agent Executor, […]
Introducing Agent Executor, Google’s distributed Agent Runtime Read More »
LLMs have become more powerful at smaller sizes, but deploying them to edge devices like smartphones remains a massive challenge. Today, developers have to optimize across a sprawling combination of accelerators, operating systems, and countless System-on-a-Chip (SoC) configurations, often relying on manual testing with just a handful of devices. Google AI Edge Portal helps solve
Benchmark and optimize LLMs on-device with AI Edge Portal Read More »
In just a short time, we’ve seen AI transition from simple chat interfaces to autonomous agents capable of function calling, code execution, and persistent terminal use. But to orchestrate these capabilities securely, agents need more than just intelligence — they need a robust, hyper-scalable, secure compute environment in which to execute code. Since our preview
Agent Sandbox on GKE is now available for everyone, and a first look at Agent Substrate Read More »
Ryan welcomes Jaime DeLanghe, chief product officer at Slack, to chat about how they’re preparing to integrate everybody’s agents in their chat application.
Pack your agentic stack in Slack Read More »
This is a new era — the agentic era – and the question is no longer, “what’s possible?” but rather, “what creates impact?” Today, organizations across industries around the world are swiftly moving from AI exploration and pilots to real-world use cases that drive impact, at scale. They are doing this with agents. In order
The agentic era: Architecting the blueprint for mission impact across the public sector Read More »
At Google I/O, we introduced a unified development toolkit featuring Antigravity 2.0 and the Managed Agents API, giving developers better ways to build locally and deploy securely to the cloud on a shared protocol layer. In this blog, we’re going to show you how Gemini Enterprise Agent Platform and the new developer tools shared at
What Google I/O ’26 means for developing agents on Google Cloud Read More »
At Google Cloud Next ‘26, we unveiled the blueprint for the Agentic Enterprise, sharing our eighth-generation TPUs, Gemini Enterprise Agent Platform, a fully reimagined Agentic Data Cloud, Workspace Intelligence, and security built for the AI era. Today at Google I/O, we’re delivering a new set of powerful AI innovations and models — and putting them
Everything Google Cloud customers need to know coming out of Google I/O Read More »
The modern software development landscape isn’t happening just on one surface — it’s happening across an entire ecosystem of agentic tools. Agents are being developed at an unprecedented scale, and these agents require direct access to enterprise data for context and grounding. However, the current tooling for building agents and managing data is heavily fragmented.
The modern software development landscape isn’t happening just on one surface — it’s happening across an entire ecosystem of agentic tools. Agents are being developed at an unprecedented scale, and these agents require direct access to enterprise data for context and grounding. However, the current tooling for building agents and managing data is heavily fragmented.
In the mining industry, accurate geological analysis is required for improving mine design and development. Traditionally, this involved labor-intensive and time-consuming on-site inspections of drill core samples, often conducted in remote and challenging environments. ALS GeoAnalytics has streamlined this process through its LITHOLENS platform, a machine learning (ML)-powered system that uses deep learning and machine
