Do AI Agents Need to Be Intelligent to Do Their Job? | Shimmy Says Ep. 47

Hello. If a parrot says hello, is it intelligent or just repeating, AI agents don't need to think they need to work. Hey everyone, I hope, I hope you like our little parrot video there.

Wanted to start today off with a little joke. So here we go. You may have heard this one.

Probably not. So there are two parrots sitting at a bar. One parrot leans over and says hello.

The other one leans back and says Hi there. The bartender wiping down the counter, looks at them both and says, Hmm, these two seem more intelligent than the usual bird brains I serve here. Ha ha ha.

Not a great joke. But this is what happens when you ask AI to write a joke. AI's good at a lot of things, but evidently writing writing jokes isn't one of 'em.

But that's the joke I wanted to start with today. But really the joke may be on us and I'll tell you why. You know it's human nature.

If you stood there watching those two parrots go back and forth for a while, you anth, anthropomorphism, I think is the word we use, words you embed them or do and give them human qualities. You start thinking they're actually having a conversation. You imagine their personalities, their intent.

You think one's a little smarter, one's a little more sarcastic, stand there longer, and your ba, your brain really starts inventing a relationship. This is the man, there's the woman, whatever. That right there is projection.

But here's the deal with parrots. Some parrots just mimic sound. They're noise with feathers.

But there are other parrots. African grays for instance, are known for this. They actually are somewhat intelligent.

They can associate words with objects, context, even intent. An African gray will say walnut a nut, but they're not just mimicking a sound. They're making a request.

They know walnut a nut can result in them being fed a nut. But not all parrots are intelligent or intelligent and not all intelligence looks like human intelligence. And that's something really you gotta understand when you're talking about ai.

'cause that distinction right there is where this whole AI agent debate keeps going off the rails. We are fixated on super intelligence, artificial general intelligence and all these things, which just yesterday we saw another announcement with Nvidia met of chasing that holy grail, right? A multi-billion dollar deal.

Yet again for super intelligence, depending who you talk to, we may achieve superintelligence someday. We may never achieve super intelligence, but that's okay. You know, I wrote a whole bunch of articles this week.

One of them is called, not All Parrots are intelligent, but does it matter for AI agents? Where I discussed this, it was actually a rip riff riff off a guy named Sebastian Th I, if I mispronounce Sebastian's last name, I apologize. He commented on, on post this morning, um, Sebastian wrote a warning about what's going on at Malt book and all the molt OpenCL agents there.

You know, if at first glance it looks like agents have appeared to debate philosophy, invent religions, you know, they formed their safari church. You gotta love that. To some people this looked like emergence or a shout out to David Brynn famous sci-fi author who's also keynoting our RSA event on the Monday of RSA week, David wrote a whole series called the Uplift series where we uplifted animals and stuff into intelligence, right?

And that's what it looked like to some people. An emergence of intelligence. Well, Sebastian argues, and I agree with them, that that wasn't really an emergence of intelligence or not intelligence as humans think of it.

But it was pattern completion. It was grammar without grounding. As Sebastian rightfully says, the emperor has no mind.

And that warning matters. We gotta remember that. 'cause when we project intelligence onto systems that respond to structure rather than meaning we're just off the rails to begin with.

We're building the wrong trust models. We assume judgment when there really is just interpolation. We assume reasoning when at best is probability.

That my friend's right there. That's dangerous. Now here's where the conversation goes from here though, and matures a little bit.

I wrote another piece about AI intelligence. It's, and it, I made it really explicit in there. Let, let's cut the bolt as we sit here today.

AI agents are not intelligent. They're not, not, not by our definition of intelligence. Maybe there's some other intelligence definition they are.

But quite frankly, if you're a digital leader, you are looking at using AI agents, OpenCL and so forth, that's not the question you need to be asking yourself. Again, at least not today or in the really near future. If you're a CIO or CTO or CDO, your board isn't asking you whether the model understands can't it thinks and therefore it is No.

They're asking, are we behind on AI or in front of it? Is AI gonna make our business better? Is it gonna contribute to the bottom line?

Is it gonna make us money? That's the question. It's a question of performance.

Can it do what I want it to do right now? Can these systems produce measurable outcomes inside your organization? That's really the only question you need to be asking.

'cause that's the question that moves budgets and drops to the bottom line. So let's separate these two debates. The philosophical intelligence question that all the AI pundits and types like to chase this super intelligence.

And then there's where the rest of us live operationally around execution. Most enterprise deployments of AI agents today live in very bounded workflows. They're drafting internal documents, they're summarizing research, they're routing tickets, flagging anomalies, assisting support lines, generating code snippets, maybe orchestrating structured task.

But these are not existential reasoning problems that demand Einstein level IQ or intelligence. They're process problems. Intelligence isn't the the KPI here.

This is BPA on on steroids. Performance within constraints is what it's about. If an agent can reduce cycle time by 30% inside a defined workflow, it doesn't need to understand the way a human wouldn't understand it.

It just needs to do its job. Like Bill Belichick used to tell the Patriots when they were dynasty, just do your job. It needs to execute it consistently.

I'll give you another example. Spreadsheets, no one says their intelligence spreadsheets didn't understand accounting, but they calculated numbers faster for us and they opened up a whole new world. The internet didn't understand journalism but it distributed content faster and killed a lot of the print media world.

AI doesn't need consciousness to com compress friction inside your organization either. All it really needs is reliability. But now let me go up a little further.

Let's get reckless. Okay, we'll get a little reckless here. There are domains where semantic grounding really does matter Deeply.

Security, high stakes, legal kinds of decisions, medical SY systems, life and death, physical autonomy pattern matching without understanding in those cases can generate catastrophic results. But those are edge cases and that is not a model debate right there. That's an architecture debate.

And this is where you need digital leadership to show up and be heard and be counted and stand up blind. Enthusiasm for AI is not a leadership or successful leadership trade either. Letting the agents run is not really a strategy, it's just abdication paralysis because they're not truly intelligent though is also not leadership.

None of those things are, leadership starts with boundaries and in putting boundaries in place. Where does pattern matching create leverage without creating existential risk? And if you could find those areas, put your agents there, you'll be successful.

'cause where are where workflows are clearly structured enough that probabilistic systems can operate si safely. If you deploy agents into undefined territory, though that's not iris, don't blame the tool. That's leadership failure.

Second human and meaning governance. And I don't know if you understand or I've heard the term human and meaning, but I'm not talking about human in the loop. Human in the loop on every action is not gonna scale for us.

Human and meaning means executives define intent. They're constraints and success criteria. And then the agents execute within that cage within those boundaries.

If the boundaries are are vague, don't blame the agent in the model. Blame the person who made the boundaries. Third thing, observability.

That's a word we all love to use and throw around. If you can't see what your agents are doing, you really don't have a strategy. Let's face it, you have a science experiment.

Next, identity logging, access control, escalation, paths, instrumentation, those are all part of it guys. Architecture beats hype every single time. Let's go full back now to the parrot, right?

Does it matter that the parrot doesn't understand English the way you do? Well, it matters if you expect it to interpret scar sarcasm. But if you, if you just want to mimic what you're saying, you, you can talk Greek or Spanish just as easily.

It doesn't matter if all you need to do is repeat a signal consistently. Many enterprise workflows do nothing more than that. They don't require deep semantic understanding.

They need to recognize and repeat signals consistently at scale. They require structured mapping from input to output. The mistake too many of us are making right now is anthropo an anthropomorphism, giving it human giving our agents and our AI human qualities.

This is why I've never given my agent a name I know a lot of you have or your AI in name. I don't, they're not humans. They're tools.

They're not even pets. They're cattle. A second mistake people make is underestimating usefulness.

Don't let perfect get, uh, get in the way of good for usefulness. Disruption does not trigger when all intelligence appears. Disruptional trigger a lot earlier than that.

It, it triggers when performance crosses the economic threshold. It's about the money. Stupid.

In my writing about the AI doomsday job clock, another article I wrote a lot this week. I argue that the divide is not in, in jobs for the future is not human versus ai. It's humans who use AI versus humans who don't use ai don't get caught on the wrong side of that equation.

'cause make no mistake, that divide's already forming and people are on either side of it. If an agent drafts a first pass in minutes, the legal team's value shifts from typing to judgment. If agents analyze logs at scale, the ops team value shift shifts from detection to decision.

If marketing copy is generated instantly positioning becomes the scar skill not generating copy. And guys, that's not intelligence replacing humans, that's just workflow redesign. Compressing friction, which is what I spoke about earlier, the shift doesn't require consciousness, it requires competence.

At the end of the day, competence wins. So do AI agents really need to be intelligent to do their job in the human sense? Not if the job is clearly defined, bounded and instrumented.

No, they don't need intelligence. They need to be competent. As I said earlier, inside the cage, you build for it.

If the job that you're asking it to do requires open-ended judgment and ambiguous, high risk enval environments like I outlined, well then intelligence absolutely matters more and the human is the right person for the job or at least human oversight. As my friend earlier said, the emperor may not have a mind indeed, but if he can run payroll without errors, optimize supply chains and draft your quarterly update and half the time behavior changes, markets adjust, roll shift, and most importantly, budgets move. It's all about the budgets.

Digital leaders who sit around debating whether the emperor is conscious or not are gonna miss this window, right? Though they're neuro fiddling while Rome burns, digital leaders who define constraints, redesign workflows and instrument execution will capture the advantage and they'll gonna be wind every time. AI agents may never think like humans, that's okay, it's fine.

They really don't have to. And that's what I'm here to tell you and that's what I'm hoping you'd get out of this. They just have to execute the work you define inside the boundaries you design in service of outcomes that matter.

This whole intelligence, super intelligence things a fascinating debate, but execution my friends is a com is the competitive weapon here, it's the weapon of mass destruction and competitive weapons. Do not need to be self-aware. That's shimmy.

I'm out. I hope you enjoyed this. Do check out the articles I wrote around this too.

They're on tech strong AI and digital cxl for the most part. I'll be back next time with more, but for now, enjoy the weekend coming up. We'll see you next week.

Shimmy says Shimmy.