How to Tell a Real AI Agent from a Rebranded Bot

Aimee: You know that feeling when a word just sort of catches fire. Right Now for me, it feels like that word is AI agent.

Craig: Oh, definitely. It's everywhere.

Aimee: Exactly. You see it in marketing, tech news, maybe even popping up in work meetings. But honestly, when you try to actually pin down what it means…

Craig: It gets really fuzzy fast.

Aimee: Yeah. The Wall Street Journal even pointed this out, didn't they? That there's just no single clear definition floating around.

Craig: And Prem Natarajan over at Capital One, he had a great analogy, he called it the “elephant in the room…”

Aimee: Right, because everyone's describing a different piece of it.

Craig: That's basically the problem. The term AI agent is. Well, it's becoming almost meaningless because it's stretched so thin.

Aimee: So you've got simple chatbots that just follow a script.

Craig: Or maybe some slightly fancier automation tools.

Aimee: Yeah.

Craig: They're all getting slapped with the AI agent label.

Aimee: And that makes it tough, especially for listeners, maybe making tech decisions, trying to figure out what's really capable.

Craig: Incredibly difficult. It obscures the real potential of genuine AI agents.

Aimee: Okay, so that's our mission today. Then let's try and cut through some of that hype.

Craig: Offer some clarity.

Aimee: Yeah. Give people the tools to sort of tell the difference between a real AI agent and well, maybe just a cleverly rebranded bot.

Craig: So you can make informed choices—avoid the noise.

Aimee: Exactly. And to help us do that, we're going to lean on the perspective of Zach Bartholomew. He's the VP of product at Perigon. He offers a pretty useful way to think about this.

Craig: He does. Bartholomew gives a really practical definition. He says it's, “software that can perceive its environment, plan out how to respond and take meaningful action, largely on its own.”

Aimee: Okay. Largely on its own. That sounds like the crucial part.

Craig: It really is. It highlights that key element, autonomy.

Aimee: So when we say largely on its own, we're separating it from systems that just run through a pre-programmed list of steps.

Craig: Precisely. Or systems that need a human to every single action.

Aimee: Right? No constant click here to approve.

Craig: Exactly. Bartholomew’s definition draws a clear line. A true AI agent isn't just reactive, it's proactive. It can actually set its own objectives, figure out the steps needed…

Aimee: …and do it independently.

Craig: Largely independently. Yeah.

Aimee: So it's more than just responding to a queue. It's about seeing what's happening, learning from it.

Craig: Learning, adapting its strategy based on that learning,

Aimee: And then acting on those decisions without needing the go-ahead every single time.

Craig: You got it. That's the core. Learns, adapts, acts autonomously.

Aimee: Okay. And I guess that explains why the term is so popular now. That capability sounds really powerful.

Craig: It is exciting. There's huge potential there, but of course that popularity creates a big incentive for, well, for vendors.

Aimee: To just slap the label on anything that automates something.

Craig: Pretty much, even if it doesn't truly have that deep autonomy we're talking about. It's good marketing, right?

Aimee: It reminds me of calling cruise control a  self-driving car.

Craig: That's a great analogy. Yeah. Yeah. Both automate something, but they're worlds apart in actual

Aimee: Capability. And Bartholomew points out, this causes real headaches for IT leaders, doesn't it? Trying to figure out what's genuinely autonomous versus…

Craig: …versushat he calls, I think advanced macros or LLM driven automation basically souped up versions of existing tools, maybe with some language processing added on.

Aimee: Okay, so distinguishing between those isn't just about getting the definition right. It's more serious than that.

Craig: Oh, absolutely. Bartholomew is really clear on this. The risks of not being able to tell the difference are significant.

Aimee: What kind of risks are we talking about beyond just being a bit confused by the marketing buzz?

Craig: Well, think about it from a CIO's perspective. Bartholomew puts it bluntly, CIOs can waste budget on software that doesn't deliver true autonomy.

Aimee: Okay. So wasted money first off…

Craig: And then that leads to frustrated teams, wasted resources, and a loss of confidence in AI.

Aimee: Right? If you buy something expecting it to act independently and it constantly needs help or breaks down…

Craig: Your team gets disillusioned, right? The tool doesn't deliver, the investment feels wasted, and maybe people become skeptical about the next AI initiative too.

Aimee: So it erodes trust. This isn't just semantics, it's actually about making bad strategic bets.

Craig: Exactly. Potentially very costly ones.

Aimee: Okay. Okay. So we get the definition, autonomy, learning, action, and we get the risks of getting it wrong. So the big question, how do our listeners actually identify a true AI agent? How can they spot the real deal?

Craig: Right? In Perigon's perspective, Bartholomew’s perspective offers some really practical questions to ask. Almost like a checklist.

Aimee: A checklist, okay. I like that. What's on it?

Craig: First key question, can it plan and execute multi-step processes on its own?

Aimee: That goes straight to the autonomy point, doesn't it? Can it figure out A, then B, then C, to get to the goal without me telling it each step?

Craig: Exactly. It shouldn't need constant handholding for every little subtask. It needs to see the objective and navigate towards it.

Aimee: Makes sense. What's next on the list?

Craig: Second one, does it learn or improve over time?

Aimee: The learning and adaptation part…

Craig: Right? Is it static or does it actually get better, more efficient based on its experiences? That's a core part of intelligence.

Aimee: Okay, good one.

Craig: And the third…

Aimee: Crucial question, can it take meaningful action without human approval?

Craig: Meaningful action. So not just like formatting a cell, but making a decision that has a real impact.

Aimee: Precisely. This is a big dividing line between an autonomous agent and something that's still fundamentally just assisting a human.

Craig: Learning, independent action. These seem critical. Anything else?

Aimee: Yep. Two more good ones. Fourth, what kind of decisions can it make independently? This helps you gauge the scope of its autonomy.

Craig: So is it just tweaking small parameters or can it handle bigger, maybe more strategic choices?

Aimee: Exactly. Understand the boundaries of its decision-making power. And finally, number five, a very practical one. How well does it integrate with your current tech stack?

Craig: Ah, the plumbing question…because even the smartest agent isn't useful if it can't connect to anything…

Aimee: Right? It needs to actually work within your environment to deliver value. Okay. So that's a solid checklist. Plan and execute multi-step processes; learn over time; act without approval; what kind of decisions and integration; and I guess the rule of thumb is if you're getting a lot of no or well sort of answers to those.

Craig: Then you're probably not looking at a true AI agent. At least not in the sense we've been discussing. It might be useful automation, but not an autonomous agent.

Aimee: Gotcha. It sounds a bit confusing right now though. Is it always going to be the s murky?

Craig: Well, that's the hopeful part. Bartholomew is actually pretty optimistic here. He thinks things will get clearer.

Aimee: Oh, how so?

Craig: He expects that as we see more real world uses, more actual deployments and crucially success stories, the differences will become much more obvious.

Aimee: So, examples will help define the term better?

Craig: Exactly. He predicts, let me find the quote. Yeah. “Over the next year or two, I expect we'll see clearer definitions in real success stories that differentiate true AI agents.”

Aimee: Okay.

Craig: Capable of unsupervised learning and autonomous action from what are essentially more advanced forms of automation.

Aimee: Unsupervised learning, meaning it can figure things out without being explicitly trained on every single data point.

Craig: Right? It can find patterns and improve itself more independently as systems that can really do that start delivering results. It'll be much harder to confuse them with say, glorified chatbots or fancy macros.

Aimee: That's encouraging. So the fog might lift in the next year or two.

Craig: That's the expectation. But in the meantime…

Aimee: In the meantime, stay skeptical. Ask those questions we just went through.

Craig: Absolutely, ask the tough questions, demand evidence of that autonomy, and really prioritize solutions that genuinely deliver on that promise. Not just use the buzzword.

Aimee: Don't just trust the label. Look under the hood.

Craig: Precisely. Making those informed choices now, even while things are a bit hyped up, can prevent headaches down the road and maybe even give you an edge.

Aimee: Okay, so let's quickly recap. The absolute key thing defining a true AI agent is that autonomy, right?

Craig: Right. The power to perceive plan and act meaningfully on its own and critically to learn and adapt as it goes…

Aimee: Which separates it from simpler automation tools, even if they're marketed with the same AI agent term…

Craig: And using those key questions about multi-step processes, learning independent action, decision scope integration, that's the listener's toolkit for cutting through the

Aimee: Norm. Makes sense. Empowering yourself to make smarter choices.

Craig: Exactly.

Aimee: Okay, so as we wrap up, here's maybe a final thought to chew on. If we take this idea of truly autonomous AI agents, seriously, not just the hype, but the real potential. What does that look like in your world? Your job, your industry, maybe even just daily life? As these definitions sharpen and the tech matures, what brand new opportunities or maybe even challenges start to come into focus? Think beyond today's buzz and consider where genuine AI agency might actually take us.