Demystifying AI Jargons
AI is evolving at an incredible pace. Every week brings new terms, frameworks, and tools, Agents, MCP, RAG, Context Engineering, Memory, Skills, Hooks, Steering Files, and many more.
With so much happening, it's easy to lose sight of what these concepts actually mean, when they should be used, and how they fit together. As a result, we often misapply them—or worse, blame the AI model or the tool when the real issue is choosing the wrong approach for the problem.
In this session, we'll cut through the buzzwords and explore the building blocks that power modern AI systems. Rather than focusing on definitions alone, we'll develop a practical mental model for deciding what to use, when to use it, and why.
Whether you're just getting started with AI or already building AI-powered solutions, you'll leave with a clearer understanding of the AI landscape and the confidence to choose the right abstraction instead of the most popular one.
"The map is not the territory — but without a map, every territory looks the same.
What we'll cover:
Prompting vs Context Engineering — understand when simple prompts suffice and when you need full context engineering
Tokens, Context Windows, and Steering Files — the foundational mechanics that shape AI behavior
Tools & MCP, Skills & Hooks — the interfaces that give AI systems real-world capabilities
Memory vs RAG — knowing which approach fits your use case
Agents & Multi-Agent Systems — when single-agent falls short and orchestration matters
A practical decision framework for choosing the right AI building block — move beyond hype to intentional design
Let's move beyond the hype and learn how to build AI systems with clarity, confidence, and purpose.