Hands On | OpenAI Agents SDK #198
Description
Talk title
Build Quick Agents with OpenAI Agent SDK
Short talk description
Discover How To Build Intelligent AI Agents In Minutes Using OpenAI's Agent SDK. This Talk Demystifies The Process Of Creating Autonomous Agents That Can Reason, Plan, And Execute Complex Tasks. Learn The Core Concepts Of Agent Architecture, Tool Integration, And Multi-Step Workflows. We'll Walk Through Practical Examples—From Simple Task Automation To Advanced Multi-Agent Systems. Whether You're Building Customer Support Bots, Research Assistants, Or Workflow Automation Tools, This Session Will Equip You With The Knowledge To Rapidly Prototype And Deploy AI Agents. Perfect For Developers Looking To Leverage The Latest In Agentic AI Without Getting Lost In Complexity.
Long talk description
AI Agents Are Revolutionizing How We Build Intelligent Applications, And OpenAI's Agent SDK Makes This Technology Accessible To Every Developer. This Talk Provides A Comprehensive Guide To Building Production-Ready AI Agents Quickly And Efficiently.
We'll Start By Exploring What Makes An AI Agent Different From Traditional Chatbots—Understanding Concepts Like Reasoning, Planning, Tool Use, And Memory. You'll Learn How Agents Can Break Down Complex Problems Into Manageable Steps, Make Decisions, And Interact With External Systems To Accomplish Goals Autonomously.
The Session Covers The Essential Building Blocks Of The OpenAI Agent SDK: Setting Up Your Development Environment, Configuring Agent Behavior, Implementing Custom Tools And Functions, And Managing Multi-Turn Conversations With Context Retention. We'll Dive Into Real-World Implementation Patterns Including Error Handling, Streaming Responses, And Optimizing Agent Performance For Production Use.
We'll Also Address Important Considerations Like Cost Management, Rate Limiting, Security Implications Of Autonomous Systems, And Testing Strategies For Non-Deterministic Agent Behavior. You'll Leave With A Clear Understanding Of When To Use Agents Versus Traditional Approaches, And How To Architect Scalable Agent-Based Solutions.
Whether You're A Backend Developer Exploring AI Integration, A Full-Stack Engineer Building Intelligent Features, Or An AI Enthusiast Ready To Move Beyond Simple LLM Calls, This Talk Will Accelerate Your Journey Into Agentic AI Development.
What format do you have in mind?
Talk (25-30 minutes + Q&A)
Talk outline / Agenda
1. Introduction To AI Agents
- What Are AI Agents Vs. Traditional Chatbots?
- Key Capabilities: Reasoning, Planning, Tool Use, Memory
- Real-World Use Cases And Applications
2. OpenAI Agent SDK Fundamentals
- Architecture Overview And Core Components
- Setting Up The Development Environment
- Basic Agent Configuration And Initialization
- Understanding The Agent Execution Loop
- Tool Integration And Function Calling
3. Building A Practical Agent - Live Demo
- Step-By-Step: Personal Assistant Agent
- Defining Tools And Custom Functions
- Managing Context And Multi-Turn Conversations
4. Advanced Patterns And Best Practices
- Multi-Agent Collaboration Concepts
- Prompt Engineering For Optimal Agent Behavior
- Memory Management And State Persistence
- Performance Optimization Techniques
5. Production Considerations
- Cost Management And Rate Limiting
- Security And Safety Guardrails
Key takeaways
-
Understand The Fundamental Difference Between AI Agents And Traditional Chatbots, Including Core Concepts Like Reasoning, Planning, Tool Use, And Memory Management That Enable Autonomous Task Execution.
-
Gain Hands-On Knowledge Of The OpenAI Agent SDK Architecture And Learn How To Set Up, Configure, And Initialize Agents For Production-Ready Applications.
-
Master The Process Of Building Custom Tools And Functions That Allow Agents To Interact With External APIs, Databases, And Services To Accomplish Complex Multi-Step Tasks.
-
Learn Best Practices For Agent Development Including Prompt Engineering Techniques, Error Handling Strategies, Context Management, And Debugging Non-Deterministic Agent Behavior.
What domain would you say your talk falls under?
Data Science and Machine Learning
Duration (including Q&A)
40 Minutes (30 Minutes Session + 10 Minutes Q&A)
Prerequisites and preparation
- Basic Python Programming: Familiarity with Core Python Fundamentals.
- API Understanding: Basic Knowledge of RESTful APIs and HTTP Requests.
- Experience With LLMs: Prior Exposure to Working with ChatGPT, GPT-4, or Similar Language Models is Helpful but not Mandatory.
- Async Programming: Understanding of Asynchronous Programming Concepts is beneficial but will be Explain during the Talk.