OpenAI Agents SDK: Build Multi-Agent AI Systems in Python

OpenAI Agents SDK: Build Multi-Agent AI Systems in Python
.MP4, AVC, 1920x1080, 30 fps | English, AAC, 2 Ch | 9h 52m | 5.36 GB
Instructor: Gopi Donthireddy

• Build and configure production-ready agents using the OpenAI Agents SDK in Python
  
• Equip agents with function tools, hosted tools, and structured outputs to complete real tasks
  
• Stream agent responses in real time and manage runs with RunConfig and context objects
  
• Orchestrate multi-agent systems using handoffs, triage routing, and parallel execution
  
• Protect agent pipelines with input and output guardrails that block invalid requests
  
• Debug and monitor agents using built-in tracing, the OpenAI dashboard, and lifecycle hooks
  
• Track token usage and cost across multi-agent runs to control spend in production
  
• Build a complete multi-agent research assistant combining tools, handoffs, guardrails, and tracing
  

• Basic Python. Comfortable with variables, functions, loops, and classes. No async/await experience required; it's introduced gradually as the course progresses.
  
• A free OpenAI platform account with API access. Usage is pay-as-you-go and billed separately from Udemy; the full course typically costs only a few dollars in API calls.
  
• A free Google account for Google Colab. Every notebook runs in the browser; no local Python install, IDE, or virtual environment needed.
  
• Any computer with a modern browser and internet connection. No powerful hardware or GPU required.
  
• No prior experience with AI agents, LLM frameworks, or the OpenAI API required. This course starts from your very first agent.
  

• Build and configure agents using the OpenAI Agents SDK, from your first agent through advanced configuration and structured outputs
  
• Equip agents with function tools, hosted tools, and multi-agent handoffs to complete real, multi-step tasks
  
• Stream agent responses in real time and manage runs with full control over configuration and context
  
• Orchestrate multi-agent systems using handoffs, triage routing, and parallel execution with asyncio
  
• Protect agent pipelines with input and output guardrails that block invalid requests before they cost you time or money
  
• Debug and monitor agents using the SDK's built-in tracing, the OpenAI dashboard, and lifecycle hooks
  
• Track token usage and cost across multi-agent runs, a skill most courses skip entirely
  
• Build a complete multi-agent research assistant from scratch, combining every concept from the course into one capstone project
  

• Python developers who want to move beyond single LLM API calls and build autonomous, tool-using agents
  
• Backend or software engineers exploring agentic AI who want a structured, hands-on path instead of scattered tutorials
  
• Developers already using the OpenAI API directly who want a framework that manages the agent loop, tool calls, and handoffs for them
  
• AI or ML engineers moving from model training into agent orchestration, guardrails, and production observability
  
• Anyone who has tried LangChain, CrewAI, or similar frameworks and wants to learn OpenAI's own first-party Python SDK instead