Build smarter AI agents with Parallelization and Orchestration workers architectures
In this hands-on workshop, you’ll learn to design and implement AI agent architectures that enable structured decision-making, task automation, and workflow optimization. AI agents can process inputs, make intelligent decisions, and take actions autonomously. By leveraging Langbase’s composable agent architecture, you will build scalable and efficient AI systems without the need for complex frameworks.
This session will focus on two key architectures used for structuring AI workflows:
Agent Parallelization – Parallelization runs multiple LLM tasks at the same time to improve speed or accuracy. It works by splitting a task into independent parts (sectioning) or generating multiple responses for comparison (voting).
Agentic Orchestration – The orchestrator-workers workflow has a main LLM (orchestrator) that breaks a task into smaller parts and assigns them to worker LLMs. The orchestrator then gathers their results to complete the task, making it useful for complex and unpredictable jobs.
In this session, you’ll learn how to:
Understand AI agents and their architectures
Implement agent parallelization for faster and more reliable workflows
Use orchestrator-worker workflows to split tasks, delegate to workers, and merge results
Define workflows that integrate multiple AI agents
Deploy and scale AI agents using Langbase
Everyone is welcome to join this event, whether you're an experienced developer or an aspiring AI engineer, no matter your background. Feel free to share the invite link with others.
To get the most out of the session, make sure you have a code editor and Node v20+ installed beforehand. You should also be familiar with basic JavaScript and using the command line.