Master the future of artificial intelligence with autonomous agents that think, plan, and execute complex workflows
“AI Agents are programs where LLM outputs control the workflow.”
In practice, this describes an AI solution that involves any or all of these components working together to create autonomous, intelligent systems.
Orchestrating sequential and parallel LLM interactions for complex reasoning
Enabling language models to interact with APIs, databases, and external systems
Creating spaces where multiple LLMs collaborate, compete, and evolve
Coordinating activities and workflows through autonomous decision-making
From foundational concepts to advanced implementations, discover the essential resources and tools to build intelligent AI agents that can reason, plan, and execute in the real world
Essential theoretical foundations covering agent definitions, autonomy, and the key principles of building effective AI systems.
Hands-on notebook tutorial to create a simple AI agent that explores commercial applications through sequential LLM calls.
Learn how to coordinate multiple LLM calls for complex reasoning workflows and decision-making processes.
Building agents that can interact with APIs, databases, and external systems to perform real-world tasks.
Creating collaborative environments where multiple AI agents work together towards common goals.
Advanced planning algorithms and coordination strategies for autonomous agent behavior.
Industry implementations and lessons learned from deploying agentic AI systems at scale.
Design patterns, best practices, and architectural guidelines for scalable AI agent systems.
Join our community of AI practitioners and stay updated as we release cutting-edge content in the Agentic AI Series. The future of AI is autonomous, intelligent, and collaborative.