Episode 2: Foundations of agentic AI
The second episode of our Agentic AI and agentic workflows series, on what agentic AI really means — reframing agents as coordinated systems that reason, remember, act within clear boundaries, and pursue complex goals on their own.
In this episode we explore the rise of agentic AI and what it really means for the future of intelligent systems. Rather than treating AI as a single model or chatbot, we reframe agents as coordinated systems that can reason, remember, take action, and operate within clear boundaries to accomplish complex objectives on their own. We walk through how these agent-driven approaches differ from traditional automation and prompt-based interactions, and why that shift matters as AI moves toward more autonomous, goal-oriented behavior.
We also unpack the core ideas behind how agents sense their environment, decide on next steps, execute actions, and improve over time, bridging theory with real-world impact. Along the way we highlight how these concepts are already shaping practical solutions across technical operations and business workflows, offering a grounded look at where agentic AI is headed and why it is becoming foundational to modern AI systems.