Demystify AI - Clarity on LLMs, RAG, and More

Feeling confused by all the buzzwords in AI? LLMs, RAG, token limits, vector embeddings, LangChain, MLOps—it’s a storm of acronyms that makes even smart professionals feel left out. This session is designed to bring you clarity, fast.

Whether you’re a product manager trying to spec an AI feature, a founder exploring GenAI opportunities, or a student overwhelmed by blog posts—you’ll leave this call feeling 10x clearer. We’ll decode -

1. What LLMs really are (beyond “it’s like ChatGPT”)
2. How Retrieval-Augmented Generation (RAG) works and when it’s useful
3. What embedding models do and how they’re used
4. Trade-offs between fine-tuning, adapters, and prompting
5. Latency, context window, token pricing—all the stuff nobody explains
6. What stack to use if you're building (OpenAI, Claude, Ollama, etc.)

I’ll customize the conversation to your level and your goal. No gatekeeping, no jargon soup—just clear thinking for smart people who want to speak the AI language fluently.