With the rise of Agentic AI, Uncle Ben’s “with great power comes great responsibility” warning has never felt more relevant. AI agents can gather information, use tools, make decisions, and take action with limited human direction. Everybody’s talking about them, but ask 10 people what an agent is and you’ll get 10 different answers. So what actually makes a system agentic, how is it different from Generative AI, and where does human responsibility still lie?

In this session, we’ll cut through the hype by looking at how AI agents are being used in the real world, and what happens when they go wrong. Through interactive scenarios where an agent is given a goal, a prompt, and access to tools, we’ll unpack why a seemingly good result still went sideways. Along the way, we’ll talk candidly about AI costs, layoffs, hiring trends, and the future of work.

By the end, you’ll understand LLMs, RAG, MCP, RLHF, context, and context windows through practical examples. You’ll see what Agentic AI can do, where it falls short, and why the growing field of AI Engineering still needs humans in the loop.

Slides: https://segunakinyemi.com/slides/agentic-ai-technical-audience/
Format: 45-60 minute talk (no laptops) or workshop (laptops required) for technical and non-technical audiences, from college students to working professionals