How to Build Multi-Agent AI Systems in Minutes with Vertex AI Agent Designer
Most businesses struggle to create specialized AI agents that can handle complex, domain-specific queries. Google's Vertex AI Agent Designer changes everything - letting you visually design complete multi-agent systems that automatically route queries to the right specialist, with zero coding required.
What is Vertex AI Agent Designer?
Building specialized AI agents traditionally required teams of developers and machine learning engineers. Vertex AI Agent Designer changes this by providing a visual interface where you can design complete multi-agent systems in minutes.
Available in Google Cloud's Vertex AI platform (currently in preview), this tool lets you define main agents and specialized sub-agents, configure their behaviors, select models, and connect tools - all through a simple drag-and-drop interface.
Key advantage: The system automatically generates all the underlying code for your designed agent architecture, ready for enterprise deployment. This eliminates months of development work while maintaining full customization capabilities.
Healthcare Agent System Demo
The demo shows a practical healthcare application with three interconnected agents:
- Main Healthcare Agent: Serves as the primary interface
- Patient Agent: Handles hospital and general patient information
- Doctor Agent: Specializes in physician-specific queries
This architecture demonstrates how complex domain knowledge can be partitioned among specialized sub-agents while maintaining a unified user experience. When a user asks "find me some good doctors in Las Vegas," the system automatically routes this to the Doctor Agent, which then provides location-specific physician information.
Creating Agents and Sub-Agents
The creation process is remarkably simple:
Step 1: Define Your Main Agent
Start by naming your primary agent and providing a clear description of its overall purpose. In the demo, this was a "Healthcare AI Agent" with the description "provide healthcare related information."
Step 2: Add Sub-Agents
Click "Add Sub-Agent" to create specialized agents. The demo added:
- Patient Agent: For hospital and general patient information
- Doctor Agent: Specifically for physician-related queries
Step 3: Configure Agent Details
For each agent, specify:
- Name and description
- Brief summary of purpose
- Behavior definition
- Model selection
- Any required tools
Note: While the demo uses simplified descriptions for speed, production implementations would include detailed behavior definitions to ensure precise agent specialization.
How Agent Routing Works
The system automatically routes queries to the most appropriate agent based on content analysis. In the healthcare demo:
- A query about "doctors in Las Vegas" went to the Doctor Agent
- When refined to "cardiology doctors," the same agent provided specialty-specific results
- Patient-related questions would route to the Patient Agent
This automatic routing happens without any explicit programming - the system understands which agent is best suited for each query based on their defined purposes and behaviors.
Testing Your Agent System
Vertex AI Agent Designer includes an immediate preview feature:
- Click "Preview" after designing your agents
- Enter test queries as if you were an end-user
- Observe how queries route between agents
- Verify response quality and specialization
The demo shows this with the healthcare system - asking about Las Vegas doctors successfully routed to the Doctor Agent, which then provided location-specific physician information including patient reviews.
Iterative refinement: The preview lets you test and refine agent behaviors before deployment. You can adjust agent definitions, add new sub-agents, or modify routing logic based on test results.
Automatic Code Generation
Once your agent design is complete:
- Click "Get Code"
- The system generates all necessary implementation code
- Code is ready for enterprise deployment
This eliminates the traditional months-long development cycle for multi-agent systems. The generated code includes:
- Agent architecture definitions
- Routing logic
- Model integrations
- Tool connections
You can deploy this directly or further customize it as needed for your specific production environment.
Industry Use Cases
While the demo focuses on healthcare, this approach works for any complex domain:
Financial Services: Main agent with sub-agents for banking, investments, loans, and fraud detection.
Customer Support: Primary agent routing to billing, technical support, and account specialists.
Legal Services: Main interface with sub-agents for different practice areas (corporate, litigation, IP).
The pattern works anywhere you need to combine broad accessibility with deep specialization - providing simple access to complex, domain-specific knowledge.
Watch the Full Tutorial
See the complete healthcare agent system demo from start to finish, including agent creation, testing, and code generation (starting at 0:45 in the video).
Key Takeaways
Vertex AI Agent Designer represents a significant leap forward in making sophisticated multi-agent AI systems accessible to businesses without specialized AI teams.
In summary: You can now visually design complex agent architectures, automatically generate production-ready code, and deploy specialized AI systems in days rather than months - all while maintaining full customization and control.
Frequently Asked Questions
Common questions about Vertex AI Agent Designer
Vertex AI Agent Designer is Google Cloud's visual interface for building multi-agent AI systems without writing code. It allows you to design complex agent architectures with main agents and sub-agents, define their behaviors, select models, and automatically generates the underlying code for enterprise deployment.
The tool is particularly valuable for creating specialized agent systems where different types of queries need to be routed to domain-specific sub-agents while maintaining a unified user experience.
You can create any type of specialized agent system. The demo shows a healthcare system with main healthcare agent, patient sub-agent, and doctor sub-agent.
Other examples could include:
- Customer service agents with specialized sub-agents for billing, technical support, and account management
- Financial services systems with sub-agents for different product types
- Legal service platforms with specialized practice area agents
The system automatically routes queries to the most appropriate agent based on the request content. In the healthcare demo, asking about doctors in Las Vegas was routed to the doctor sub-agent, which then provided specialized information about cardiologists in that location.
Routing happens through natural language understanding - the system analyzes the query content and matches it to the most relevant agent based on their defined purposes and specialties.
Yes, Vertex AI Agent Designer includes a preview feature that lets you test your agent system immediately after design. You can interact with it conversationally to verify routing and responses before deploying the generated code to production.
The testing interface simulates how end-users will experience the system, allowing you to:
- Verify query routing accuracy
- Check response quality from each agent
- Identify any gaps in agent coverage
You can select from Google's latest foundation models available in Vertex AI. The demo uses unspecified models, but in production you would choose models optimized for your specific agent purposes.
Model selection considerations include:
- Specialization (general vs. domain-specific models)
- Size and capability tradeoffs
- Cost and latency requirements
As of the demo, Vertex AI Agent Designer is in preview mode, meaning it's available to Google Cloud users but may have some limitations. Google typically rolls out preview features gradually before general availability.
To access preview features:
- You need an active Google Cloud account
- May require enabling specific APIs
- Some features might have usage limits during preview
Healthcare (as shown), financial services, customer support, legal services, and any field requiring specialized knowledge domains benefit greatly from multi-agent architectures.
Key characteristics of ideal use cases:
- Multiple distinct knowledge domains
- Need for specialized expertise
- Complex query routing requirements
- Desire for unified user experience
GrowwStacks helps businesses design and implement custom multi-agent AI systems using Vertex AI and other platforms. Our team can design your agent architecture, configure specialized sub-agents, integrate with your existing systems, and deploy the complete solution.
We offer:
- Custom agent system design for your specific needs
- Integration with your existing tools and data sources
- Performance optimization and testing
- Ongoing maintenance and improvement
Start with a free consultation to discuss your agent system requirements.
Ready to Build Your Custom Multi-Agent AI System?
Don't let complex AI development hold you back from delivering specialized, intelligent experiences to your customers. Our team can have your custom agent system designed, built, and deployed in weeks - not months.