Jörg Neumann
On a Secret Mission: Developing AI Agents
#1about 5 minutes
The evolution from chatbots to autonomous AI agents
AI agents represent a shift from simple chatbots by operating independently based on triggers and using data, tools, and memory.
#2about 5 minutes
Exploring OpenAI's built-in tools and APIs
OpenAI provides powerful built-in tools like Code Interpreter and Web Search, supported by an evolving set of APIs for agent development.
#3about 4 minutes
Getting started with the OpenAI Agents SDK
The Agents SDK simplifies development by providing a clear structure for defining an agent, its instructions, and running it synchronously or asynchronously.
#4about 2 minutes
Integrating custom Python functions as agent tools
The Agents SDK allows you to easily extend an agent's capabilities by decorating a standard Python function and assigning it as a tool.
#5about 2 minutes
Using built-in tools like web search
Agents can be equipped with pre-built functionalities like the web search tool to access and process up-to-date information from the internet.
#6about 1 minute
Managing conversational history in agent interactions
Maintain context across multiple turns in a conversation by collecting the message history and passing it as a chained list to the agent.
#7about 3 minutes
Routing tasks with the handoff workflow pattern
The handoff pattern uses a central triage agent to analyze a request and delegate it to the most appropriate specialized agent in a team.
#8about 3 minutes
Building cross-functional collaborative agent teams
Create a collaborative team where a primary agent orchestrates complex tasks by using other specialized agents as callable tools.
#9about 3 minutes
Implementing guardrails to control agent behavior
Guardrails act as programmable input or output filters that check agent messages against predefined rules to ensure safe and appropriate responses.
#10about 1 minute
The conceptual shift in modern AI development
Building effective AI agents is less about mastering complex APIs and more about applying the right architectural concepts and patterns.
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Matching moments
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02:48 MIN
Understanding the core components of agentic AI systems
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Defining AI agents as collaborative teammates
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Defining agentic AI and its role as a colleague
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Tracing the evolution from LLMs to agentic AI
Exploring LLMs across clouds
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Understanding the shift to the agentic era
Event-Driven Architecture: Breaking Conversational Barriers with Distributed AI Agents
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The future of AI as a colleague in the workplace
Leading efficiency, empathy, and the human experience with AI
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The future of AI protocols and agent ecosystems
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