🤖 How to Build AI Agents with OpenAI & Python | Agentic AI Fundamentals

Stop relying on single prompts. In this lesson, we build a professional 3-step Agentic AI workflow to automate customer support using Python and OpenAI.

You’ll learn how to:
In this hands-on lab, we move beyond simple chat and start building autonomous systems. You’ll see exactly how to chain multiple LLMs together to create a production-ready support ticket system.

Key concepts covered:

Multi-Step Orchestration: How to use one LLM to generate data, a second to classify it, and a third to resolve it.
API Configuration: Setting up OpenAI, Anthropic, and Gemini keys for agentic workflows.
Efficiency with GitHub Copilot: How to use AI assistants to write cleaner Agentic code, faster.
The "Messages List" Structure: Why this format is the universal standard for OpenAI, Anthropic, and Gemini.

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🎓 Full Course HERE 👉 https://community.superdatascience.com/c/agentic-ai-1-fundamentals

💼 LinkedIn: https://www.linkedin.com/company/superdatascience/

📬 Contact: support@superdatascience.com

⏱️ Timestamps

00:00 – API Key Setup Recap
00:35 – Explaining the Agentic Workflow
01:20 – Initializing the OpenAI Client
01:50 – Creating the Messages List
02:40 – Using GitHub Copilot Efficiently
03:20 – Formatting Input for LLM APIs
04:05 – Preparing to Call the OpenAI API

🧠 Hashtags

#AgenticAI #OpenAI #PythonAI #PromptChaining #LLMs #AIAgents #GenerativeAI #PythonDevelopment #AIWorkflow #AIEngineering
#Python #MachineLearning #SoftwareEngineering #GenerativeAI #GitHubCopilot #AIWorkflow

Видео 🤖 How to Build AI Agents with OpenAI & Python | Agentic AI Fundamentals канала Super Data Science