This talk explores AI agents as the next step beyond prompt‑by‑prompt assistants. Modern AI agents use large language models plus planning, tool‑calling, and memory to execute multi‑step workflows, not just answer isolated questions. The session explains, in accessible terms, what makes something an “agent” rather than a simple chatbot: the ability to decompose tasks, call APIs or tools, and maintain context over time. It then surveys real use cases, from automating repetitive knowledge‑work tasks to orchestrating complex enterprise workflows that blend human decisions with autonomous actions. For the technical audience, the talk briefly outlines typical agent architectures and how they integrate with RAG, vector search, and existing backend services. For everyone else, it focuses on capabilities, limitations, and where AI agents are realistically being used in 2025. Attendees will understand what AI agents can and cannot do today, and how they differ from the hype.