Agentic AI: Architecting Multi-Agent Systems on Google Cloud

Agentic AI isn’t theoretical anymore—it’s architectural. We’re watching intelligent agents move from proof-of-concept to production, with teams deploying multi-agent systems that reason, take action autonomously and preemptively, and collaborate toward shared goals.

At Cloudnyx, we see this as a defining shift in how enterprise systems are designed and deployed.  I can not overstate the impact agents will have in absolutely every aspect and corner of life.  This aligns with the broader trends we track across the evolving Google Cloud AI landscape.

As a Google Cloud Boutique with deep technical roots—and firsthand experience across product teams at both Google and SADA—we’re actively helping organizations explore what’s possible with the latest advancements in agent-based development

This post surfaces the core design principles for Multi-Agent Systems (MAS), the latest tooling from Google Cloud (including Agentspace and the ADK), and real deployment patterns emerging across industries.

Building Blocks from Google Cloud

Google Cloud has made meaningful strides toward making Agentic AI accessible—and production viable.

• Agentspace
  This was one of the biggest reveals from Cloud Next '25. Agentspace gives developers a centralized workspace to build, test, and manage agents with native integrations across GCP services. It eliminates infrastructure headaches so teams can focus on agent design. We’re already embedding it into our custom delivery pipelines at Cloudnyx.

• Agent Development Kit (ADK)
  The ADK lowers the barrier to entry for agent development. With pre-built libraries, patterns, and governance baked in, teams can move from prototype to production faster. We’re using the ADK to standardize how we build agentic systems across industries—from retail to healthcare to infrastructure.
  
  

Where Agentic AI is Already Working

The agent-first approach is gaining traction across several domains. Some of the most compelling examples from Cloud Next—and from our own projects—include:

• Infrastructure Automation
  Agents can proactively monitor system health, detect anomalies, and remediate issues without human input. This is a natural extension of traditional ops automation, but with context-aware intelligence baked in.
  
  

• Healthcare Copilots
  By assisting with clinical decision support, automating documentation, and surfacing insights from unstructured data, agents can augment care delivery while reducing admin overhead. We’re actively evaluating use cases with provider organizations.
  
  

• Enterprise Productivity
  From intelligent RAG-based copilots to agent-led research assistants, we’re seeing an explosion of interest in systems that can orchestrate across business tools, APIs, and LLMs to drive workflows forward with minimal prompt engineering.

These aren’t lab demos—they’re real systems solving real problems, and they’re possible because Google Cloud is delivering the platform and tooling to support them at scale.

Architecting for What’s Next

Agentic AI changes how we think about architecture. We’re no longer just deploying models; we’re designing systems of behavior. That requires:

• Clear agent roles and boundaries

• Strong governance around data access and action-taking

• Observability into agent decisions and interactions

• Flexibility to iterate as workflows evolve

Google’s announcements at Cloud Next '25 reinforced a central theme: infrastructure should enable experimentation, not slow it down. With Gemini 2.5 Pro, Agentspace, and the ADK, that’s now within reach.

How Cloudnyx Can Help

We’re a Google Cloud boutique, but more importantly—we’re a team that’s been in the room while these systems were being built. From cloud-native infrastructure to AI-native architecture, we know how to move from idea to implementation without losing momentum.

Here’s how we support Agentic AI initiatives:

• Strategic Planning
  We help you identify where agents can make a measurable difference—and where they shouldn't be used yet.
  
  

• System Design & Development
  We build modular, scalable MAS architectures using Google Cloud’s latest tooling and best practices.
  
  

• Deployment & Optimization
  From orchestration layers to observability, we ensure your system is production-ready from day one.
  
  

• Enablement & Training
  We upskill your teams to build and manage agentic systems, so you’re not dependent on external support forever.

If you’re exploring Agentic AI and want to move fast without cutting corners, we should talk.

Final Take

Agentic AI is more than a technical curiosity—it’s a systems-level shift. Google Cloud has laid the groundwork. Now it’s up to builders, architects, and enterprise leaders to put it into motion.

At Cloudnyx, we help organizations do just this.