AI Agents

Master the tool-use agentic design pattern. Learn how agents decide when and how to use tools, handle tool results, and chain multiple tools together.

Build AI agents that select and invoke external tools. Learn tool definition, parameter extraction, result handling, and error recovery patterns.

Master the router pattern for AI agents. Learn how LLMs decide execution paths, implement conditional logic, and build intelligent routing systems.

Learn how the reflection pattern enables AI agents to review and improve their own work. Implement self-critique, iterative refinement, and quality assurance.

Master the ReAct pattern - the fundamental loop of Reasoning and Acting that powers effective AI agents. Learn implementation, examples, and best practices.

Learn how the planning pattern enables agents to tackle complex tasks through strategic decomposition, goal setting, and adaptive execution.

Design and implement multi-agent systems. Learn orchestration patterns, agent communication, task delegation, and building collaborative AI teams.

Master the multi-agent design pattern. Learn how to build systems where specialized agents collaborate to solve complex problems together.

Create a multi-agent deep research system using Linkup, CrewAI, and Ollama. Build agents that collaborate to research complex topics comprehensively.

Learn how to build systems where multiple AI agents collaborate. Patterns for coordination, delegation, and collective intelligence.

Create an AI financial analyst using CrewAI, Ollama, and MCP servers. Build agents that analyze markets, evaluate investments, and generate reports.

Step-by-step guide to building a functional AI agent from scratch. Learn the core patterns, implement tools, and deploy your first agent.