Agentic AI - The Technology & Progress

Most technologies arrive twice. First as a toy - impressive, a bit magical, and mostly useless outside demos. Then as an appliance - boring, reliable, everywhere.

Agentic AI is in the awkward middle phase: past “toy,” not yet “appliance.” You’ve probably felt the shift already. A chatbot that answers questions is neat. A system that can open your calendar, check constraints, book the meeting, message attendees, and update the CRM without you babysitting each step? That’s different. Agentic AI doesn’t just respond. It acts.

An agent can take a goal - “onboard this customer,” “resolve this support ticket,” “prepare this compliance report” - break it into steps, decide what to do next, use tools and software on its own, check its work, and keep going until the task is done or it needs help. It’s less like a chatbot and more like a junior colleague: someone who can operate software, follow procedures, and escalate when things get weird.

That shift matters because most real work isn’t a single prompt. It’s a chain of decisions, actions, and checks spread across systems, files, and people. The promise of agentic AI isn’t smarter answers. It’s delegation - software that doesn’t just advise humans, but does work on their behalf.

Over the past two years, agents have gone from chaotic demos to early production systems inside banks, tech companies, and large enterprises. They’re still fragile. They still fail in strange ways. But something important has changed: autonomy is no longer theoretical.

In this edition, we’ll unpack how agentic AI actually works, what breakthroughs made it possible, where the technology really stands today, and what still needs to happen before “AI coworkers” become boringly normal.

By the end, you should be able to explain agentic AI to a smart 15-year-old - and to your CTO.