Course
Building Scalable Agentic Systems
BasicSkill Level
Updated 12/2025Start Course for Free
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TheoryArtificial Intelligence1 hr 30 min10 videos29 Exercises1,750 XP10,003Statement of Accomplishment
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Design and Develop Agents for Scaling
Learn how to design and develop AI agents with scalability in mind, following the three pillars of agentic scalability: modularity, robustness, and adaptability. Discover what makes a successful agent in production, and why so many struggle to get there.Discover the Power of MCP and A2A
The Model Context Protocol (MCP) developed by Anthropic has revolutionized agent interoperability, creating a unified approach for connecting agents to data sources. The Agent-to-Agent protocol (A2A) developed by Google compliments MCP. Find out how these two frameworks can be combined to ensure your agent's integrations are scalable.Implement Agent Testing and Deployment Best Practices
Before pressing the big red button and launching your agent into production, you've got to mitigate the risks that come with scaling. Learn how to create a robust testing framework to capture issues with components, integrations, performance, and security. Decide which deployment type is right for your agent by looking at the needs of the use case.Feels like what you want to learn?
Start Course for FreeWhat you'll learn
- Assess testing, monitoring, and rollout strategies that support reliable, cost-effective deployment of multi-agent applications
- Differentiate network and supervisor multi-agent design patterns with respect to task delegation and communication flow
- Evaluate the suitability of interoperability frameworks such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) for given integration scenarios
- Identify common architectural components and design principles that enable scalability in AI agentic systems
- Recognize typical failure modes and risk factors that arise when deploying agents at production scale
Prerequisites
Introduction to AI Agents1
Designing Scalable Agents
Discover what makes a successful AI agent in production (and how many of them fail on the way!) Learn about the key agentic design principles to set up your agents for scaling, including robust infrastructure and tooling, modular design architecture, and continuous evaluation and feedback loops.
2
Developing Agents for Scalability
Learn about key strategies to ensure that your agent is being developed with scalability in mind. Gain insights into how the Model Context Protocol (MCP) and the Agent-to-Agent protocol (A2A) enable scalability through standardization.
3
Deploying Agents into Production at Scale
Time for production, but not so fast! Build a robust testing framework to give you confidence that the AI agent will continue to perform in production. Choose the best deployment strategy for your use case, and learn how to integrate real-time data sources with your agentic system.
Building Scalable Agentic Systems
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