S1E1 What Is Agentic AI, and Who Are We?

Episode 1 — “What Is Agentic AI, and Who Are We?”Episode 1 introduces the world of AI-Shed and the core idea behind the series: agentic AI—systems that don’t just react, but decide, adapt, and collaborate with humans.Alessandro opens by explaining AI-Shed as a creative hangar: a meeting point for engineers, designers, philosophers, and curious minds. The goal is to explore how intelligent systems are reshaping the way society builds, decides, and imagines the future. The origin of the name AI-Shed is presented with humor: if Apple had a garage, AI-Shed has a shed.He then welcomes Giovanni, long-time collaborator and systems engineer. Together, they define agentic AI as the shift from automation to autonomy: systems with goals, environmental awareness, and initiative. Examples range from fictional companions like JARVIS to real-world technologies such as predictive logistics systems and adaptive digital twins. They link this type of intelligence to Bayesian reasoning, uncertainty management, and systems engineering principles.Throughout the discussion, they highlight how science fiction has shaped engineers’ imagination—from Her and Ex Machina to WALL-E—not because fiction predicts reality, but because it reveals what is at stake when machines interact with humans.The episode also stresses the importance of responsible design, embedding ethics and context into systems from the start rather than as late add-ons.Before closing, Alessandro and Giovanni show how agentic AI already exists in everyday tools: email assistants that learn patterns, note-taking AI that builds personal knowledge graphs, adaptive workflows that plan tasks autonomously. They encourage listeners to try a small experiment: choose a repetitive task and delegate it to an adaptive AI system rather than a fixed automation.The episode concludes by linking agentic AI to systems engineering: understanding how autonomous components fit into larger structures. This sets the stage for Episode 2, which will dive into the cautionary tale of Therac-25 and the importance of system-level thinking in AI.

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