OpenAI API Programming — Part 2: Tools, RAG & Advanced Patterns

Ready to go beyond the basics of the OpenAI APIs?

In this follow-up session, we’ll dive into the real power features that turn simple prompts into production-ready AI systems. If you joined our first meetup (or have basic familiarity with the API), this session will show you how to build real world applications.

#### 🔧 What we’ll cover

1. Function Calling & Tools

• How to let models call your APIs and systems
• Building structured, reliable workflows
• Using built-in tools like web search and file retrieval
• When to use function calling vs. tool orchestration

2. Vector Stores & Retrieval

• Turning your data into searchable embeddings
• Using OpenAI vector stores as “long-term memory”
• Semantic search vs keyword search (why it matters)

3. Retrieval-Augmented Generation (RAG)

• The “secret sauce” behind modern AI apps
• Combining LLMs with your own data for accurate answers
• Architectures and patterns you can actually deploy

4. Fine-Tuning (When—and when NOT—to use it)

• What fine-tuning is really good for (and common misconceptions)
• When RAG is a better solution
• Practical tradeoffs in cost, maintenance, and performance

5. Putting It All Together

• Designing multi-tool, multi-step AI systems
• Patterns for real-world apps (agents, copilots, internal tools)
• Live coding / architecture walkthrough (time permitting)