5 Things Every AI Engineer Should Know About Agent Sandboxes Originally shared by Google Cloud Tech on X - September 1, 2026
Google Cloud Tech highlighted five critical considerations for AI engineers working with agent sandbox environments. These insights are crucial for anyone building secure, reliable AI agent systems.
Why This Matters Agent sandboxes are fundamental for:
Security isolation - Containing potentially unsafe agent actions Resource management - Controlling computational resources Execution boundaries - Defining safe operational limits Testing environments - Providing controlled spaces for agent development As someone working on AI agent systems at Google, these sandbox principles directly impact how we design memory architectures and agent runtime environments.
Give Your Agents Tools That Scale Down to Zero or Up to Infinity Originally shared by Google Cloud Tech on X - August 26, 2026. By @zeroasterisk and @Saboo_Shubham_.
An agent is only as capable as its tools, and in production those tools run as Model Context Protocol (MCP) servers. Every other layer of your stack scales to zero when it goes idle — until last month, a single MCP session pinned every tool call to one container.
Agent Plugins Package Your Skills, Tools, and More Originally published on Google Developers Blog - August 6, 2026
Google has announced Agent Plugins 1.0.0, a new vendor-neutral directory specification backed by major tech companies including Google, Amazon, and Microsoft. This standard aims to package Agent Skills and MCP (Model Context Protocol) servers into portable, interoperable units.
Key Highlights The specification standardizes the manifest (plugin.json) and utilizes a fixed directory layout, eliminating the need for developers to maintain separate wrappers or configurations to support different AI coding agents and IDEs.
Scaling AI Agent Infrastructure with the MCP Stateless Updates Originally published on Google Developers Blog - August 5, 2026, co-authored with Kurtis Van Gent.
The 2026-07-28 Model Context Protocol (MCP) spec removes protocol-level sessions in favor of a stateless core. Every tool call is now self-describing, which unlocks seamless horizontal scaling and lets tool servers run on standard HTTP routing infrastructure — no more sticky sessions, no more Redis clusters just to remember which pod holds a session.
Why We Built ADK 2.0 Originally published on Google Developers Blog - July 1, 2026, co-authored with Swapnil Agarwal and Frank Guan.
Next-gen agent development is here. ADK 2.0 is a ground-up evolution of the Agent Development Kit, aimed at making it far easier to build reliable, production-grade multi-agent applications.
Why This Matters Building agents at scale exposes gaps that don’t show up in prototypes: orchestration across many agents, human-in-the-loop checkpoints, dynamic routing, and resilience against failures.
Announcing ADK for Go 2.0 Originally published on Google Developers Blog - June 30, 2026, by Toni Klopfenstein and Sampath Kumar Maddula.
ADK for Go 2.0 introduces a brand-new graph-based workflow engine for composing complex, multi-agent Go applications, with idiomatic support for human-in-the-loop orchestration, dynamic routing, and built-in resilience — all on a unified runtime.
Why This Matters Go’s strong concurrency model pairs well with graph-based agent orchestration, and this release makes it much more natural to build production multi-agent systems in Go rather than bolting agent logic onto ad hoc goroutine pipelines.
How A2A is Building a World of Collaborative Agents Originally published on Google Developers Blog - June 18, 2026, co-authored with Frank Guan and Nick Losier.
The Agent-to-Agent (A2A) protocol is shifting AI development away from isolated, single-purpose tools toward a collaborative ecosystem — enabling secure, autonomous handoffs between agents and scalable workflows like FoldRun.
Why This Matters A2A is the connective tissue that lets agents built by different teams, on different stacks, actually work together safely.
A2UI + MCP Apps: Combining the Best of Declarative and Custom Agentic UIs Originally published on Google Developers Blog - June 17, 2026, by the Google A2UI Team, Ido Salomon, and Liad Yosef.
Three architectural patterns show how to combine A2UI’s declarative rendering with MCP Apps’ custom iframe environments, giving developers a way to build secure, performant, and brand-consistent agentic user experiences.
Why This Matters Declarative UI and custom iframe-based UI solve different problems — this piece lays out when to reach for each, and how to combine them.
Announcing the Agentic Resource Discovery Specification Originally published on Google Developers Blog - June 17, 2026, by Junjie Bu and Srinivas Krishnan.
Agentic Resource Discovery (ARD) is a new open specification for finding and verifying tools, skills, and agents across the web. The agent ecosystem works best when it’s decentralized — ARD gives agents a standard way to discover and trust resources without a single centralized registry.
Why This Matters Resource discovery and auth tiers are foundational for any multi-agent ecosystem to scale safely.
A2UI v0.9: The New Standard for Portable, Framework-Agnostic Generative UI Originally published on Google Developers Blog - April 17, 2026, by the Google A2UI Team.
A2UI v0.9 introduces a new Agent SDK, a shared web-core library, and cross-platform renderers, allowing AI agents to drive existing design systems on any device with low-latency streaming — all under a framework-agnostic standard for Generative UI.
Why This Matters Generative UI needs to be portable across platforms without locking developers into one framework’s rendering model.