To play devil's advocate, the correct use of the word would be when multiple AIs are coordinating and handing off tasks to each other with limited context, such that the handoffs are dynamically decided at runtime by the AI, not by any routine code. I have yet to see a single example where this is required. Most problems can be solved with static workflows and simple rule based code. As such, I do believe that >95% of the usage of the word is marketing nonsense.
You nailed an interesting nuance there about agents needing to make their own decisions!
I'm getting fairly excited about "agentic" solutions to the point that I even went out of my way to build "AgentOfCode" (https://github.com/JasonSteving99/agent-of-code) to automate solving Advent of Code puzzles by iteratively debugging executions of generated unit tests (intentionally not competing on the global leaderboard).
And even for this, there's actually only a SINGLE place in the whole "agent" where the models themselves actually make a "decision" on what step to take next, and that's simply deciding whether to refactor the generated unit tests or the generated solution based on the given error message from a prior failure.
I actually have built such a tool (two AIs, each with different capabilities), but still cringe at calling at agentic. Might just be an instinctive reflex.
I think this sort of usage is already happening, but perhaps in the internal details or uninteresting parts, such as content moderation. Most good LLM products are in fact using many LLM calls under the hood, and I would expect that results from one are influencing which others get used.
