Its a buzz term they've been using to obfuscate the fact that every piece of LLM slop needs a human to review it, thus costing more time and money than hiring a competent human straight out.
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Laugh as business spend billions on software that doesn't work. Cry as those same businesses fire staff to cover the cost of broken software.
Like, they can't even run pass maths tests or run a vending machine business. How do you expect one or a suite of them to manage your product lifecycle?
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I'm not impressed.
AI agents are a dream.
One that's pretty far from reality.
They don't work at all right now, and there's no evidence they'll work reliably enough to be useful anytime in the next decade or more.
Nothing to be excited about. All what those "agents" do is to Connect to LLM. There has been added more logic as in the past.
But still. It is a LLM. They get fundamental set ups. After launch they have to undergo dozens of risk assesment to meet governance Standards - that are actually pretty basic for the time being.
"Agentic AI" is nothing more than a new fancy word for investors and stock market. Those "agents" a very far away from being actually ready (as if those companies Care). Even creating this around a LLM needs a lot of know how and from my persoective it is just Not sustainable as of now.
Has anyone done anything yet with 'agentic ai' that couldn't be done better/faster/easier in other ways? So far, I've mostly seen 'I spun up 20 agents to google how to make a tuna casserole on twenty search engines and one more to summarize the results. Please, ignore that this burns as much compute power as our entire office does on a random Tuesday and produces pretty much the same result as if I had just searched once and read the free AI summary, which in turn is slightly worse than if I had searched it with no AI involved and just read the first link.'
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I don't even like giving deterministic software access to my system. Now imagine all the bad things that can happen when you give access to non-deterministic software.
Cool concept in theory, SUPER annoying and risky because in federal use because there is no "undo button" for all the mistakes the agent will make though
I've written a couple.
My job requires a lot of troubleshooting, almost to the point of reverse engineering. I've spent many hours reading and getting through logs.
Now I have an agent who can one-shot stuff half of the time, and n-shot the 4/5 other times. And it learns from experience.
I enjoyed experimenting with it, and now it's a timesaver for my team.
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