I’m glad you asked because I’ve been asking it myself. In fact I’ve been asking everyone I work with—my family, my friends, even the Jehovah’s Witness guys that came to the door yesterday. They may have the best answer actually when they said that no one can grant agency because it Is a god-given right.
If you ask an engineer, what is an AI agent she’ll give you a technical definition but on the surface you’re gonna be saying how is that different than ChatGPT? And she’ll say something like “ChatGPT is just a rag on top of an LLM, but an agent has a multi-tool chain workflow.” This is the kind of subtle difference engineers live for, that you might compare to a hotdog not being a sandwich because the bread is connected on one end.
There are plenty of more robust opinions and definitions that are much closer to the mark, but still tend to categorize based on workflow tool usage and inference protocol—sort of like how when I was a kid, in the 56.6K modem years, we all knew a lot about the specs and engines of cars even if you weren’t a mechanic, just an enthusiast. Kids in my high school knew the difference between a four-cylinder and a V8 engine; my 16-year-old doesn’t fully grasp that his car has an engine while mine has a battery—and those are different things. So he needs to start putting gas in it. All of that to say the reason kids don’t know what engines are in each car today—unless they’re a motorhead—is because the value proposition moved up. They know exactly whether or not their car supports Apple CarPlay or Android Auto. They know if it has GPS, or if it has a valet mode that locks how fast they can go when you’re using the valet key. There’s no more left to go—we saturated experience. Now we have to transform. The transformation is looking like a car without a steering wheel that can drive itself, which doesn’t replace the need for cars that don’t have soft or semi-trucks that run on diesel until we have an electric grid that could handle that many electric trucks or batteries that can go along distance on a diesel truck. But that’s why the value proposition increases when you go from experience to transformation—because the early adopters of transformation get the first-mover advantage, and they pay for it.
We’re in a transition phase right now where the value proposition is shifting markets upstream from commodities (GPUs) to goods (LLMs) to services (Agent as a Service/Agentic Web) to experience (metaverse/AR/VR agent experiences) and then, once experience is fully saturated, the market cap: transformation (personal agents).
But we’re not talking about semantics—we’re talking about agency. And agency is what makes an agent an agent. We cannot accept someone shitting in our mouth and calling it a Sundae. If you sell me agent, I demand agency.
Let’s rewind the tape a bit. Remember the days when our only “intelligent” bots were clunky programs spitting out pre-canned responses? Back then, Chatbots were nothing more than glorified text generators that mimicked conversation while you waited impatiently for something that resembled a real answer. Fast-forward to today, and the landscape is shaking with innovation. AI agents are evolving from mere conversation starters into full-blown digital maestros that juggle tasks, learn on the fly, and adapt their workflow faster than you can say “neural net.”
Think of the evolution like this: if early chatbots were that awkward teenager at the school dance, AI agents are the cool kid who not only knows the latest moves but also fixes the sound system when it craps out. They integrate multiple tools, APIs, and streams of data to execute complex tasks—an orchestration of code and creativity that moves far beyond regurgitating information.
This leap is not just a technical upgrade—it’s a paradigm shift. The engineers revel in the minutiae of multi-tool chains while the rest of us are left wondering why our virtual assistants still can’t make a decent cup of coffee. The truth is, as our demands have grown more sophisticated, so too must our agents. The promise is that these agents will not only fetch data but will actively “do” things: schedule meetings, negotiate deals, and maybe even help you untangle the mess of your personal life when everything else seems to be falling apart.
Now, let’s get under the hood. What exactly constitutes an AI agent, and how does it differ from its less ambitious cousin, ChatGPT? Picture your average chatbot as a very smart parrot—able to repeat and rearrange words in ways that seem intelligent, but without a true grasp of context or purpose. An AI agent, on the other hand, is more like a digital Swiss Army knife. It’s not just about spitting out text—it’s about orchestrating a suite of specialized tools in a fluid, adaptive workflow.
Core Components
1. Perception: At the base, an AI agent has the ability to “perceive” its environment, which in the digital realm means ingesting data from various sources—APIs, databases, sensor inputs, or even real-time news feeds. This is its eyes and ears in the digital world.
2. Decision-Making Engine: Once the data is in, the agent must decide what to do with it. This isn’t a simple if/then statement; it’s an adaptive process powered by layers of machine learning and sometimes even reinforcement learning. The engine weighs options, predicts outcomes, and chooses a course of action—sort of like a chess grandmaster planning ten moves ahead while you’re still learning the rules.
3. Multi-Tool Chain Workflow: Here’s where the magic happens. Unlike ChatGPT, which primarily churns out text, an AI agent can call upon a variety of tools. Need to schedule a meeting, book a flight, or analyze complex datasets? It seamlessly integrates these disparate functions into a coherent workflow. Think of it as having a personal assistant who not only understands your needs but also has a direct line to every service you use.
4. Feedback and Learning: The final piece of the puzzle is feedback. A top-tier AI agent isn’t static—it learns from every interaction, improving its decision-making over time. It’s like having a brain that’s constantly refining its neural pathways to better serve your needs.
Simplifying the Jargon
For those who aren’t neck-deep in code and algorithms: imagine your AI agent as a hyper-efficient personal concierge that doesn’t just answer questions but actively makes your life smoother by connecting dots you didn’t even know existed. It’s like upgrading from a dumb, one-trick pony to a full-blown circus act.
We already tossed around the idea that the value chain in technology is moving upstream. Let’s break that down further. The world started with raw commodities—think GPUs, the iron and copper of our digital age. Then came goods, like LLMs, which provided the building blocks for AI but still lacked the finesse of a full service. Next came services—enter Agent as a Service—where companies offered turnkey solutions that plugged into existing workflows.
Now, we’re staring down the barrel of the next big thing: transformation. This isn’t about tweaking what already exists; it’s about revolutionizing how we interact with technology on a personal level. Imagine having a digital entity that not only manages your calendar or emails but also understands your habits, anticipates your needs, and even challenges you to think differently. This is the realm of personal agents—a brave new world where your digital assistant becomes an extension of your very agency.
For anyone who’s ever felt like the world’s offloading decisions to faceless algorithms, this shift should sound like a call to arms. It’s not just about making your life easier—it’s about reclaiming control in a landscape where tech giants increasingly dictate terms. And for those of us juggling real-life chaos (like navigating the mess of divorce or the daily grind of parenting), this isn’t just innovation—it’s survival.
Let’s take a moment to consider the stakes here. At its core, an AI agent isn’t just a tool; it’s a promise of empowerment. In a world where every interaction with technology has the potential to strip us of our agency, the idea of a digital assistant that actively defends and enhances our decision-making is downright revolutionary.
The Impact on Daily Life
Efficiency on Steroids: Imagine having an agent that can sift through your endless emails, prioritize your tasks, and even preemptively reschedule your appointments when life throws a curveball. It’s not sci-fi—it’s the next evolution of personal management. For anyone feeling overwhelmed by the barrage of digital noise (and trust me, if you’re balancing personal crises with professional challenges, you know exactly what I mean), this is a lifeline.
Empowering the Underrepresented: For folks like us—juggling personal upheavals, navigating neurodivergence, or simply trying to find a semblance of control in a chaotic world—the promise of an AI agent is more than convenience. It’s a tool for reclaiming agency in every aspect of life. When your personal digital assistant understands your unique needs, it can help level the playing field in a society that often forgets to ask, “What do you need?”
Redefining Work: In the professional realm, these agents are set to transform how tasks are executed. No more mind-numbing repetitive work or tedious data entry. Instead, you get a digital partner that frees you up to tackle the creative, strategic challenges that truly matter. This isn’t about replacing human ingenuity; it’s about amplifying it.
The Cultural Shift
Technology has always been a double-edged sword. On one side, it liberates; on the other, it enslaves. The rise of AI agents is poised to tip the scales in our favor—if we demand agency. We’re at a crossroads where the ethical, philosophical, and practical implications of “digital agency” are coming into sharp focus. The conversation is no longer just about how smart these systems are, but about how much control they allow us to retain over our lives.
For those in the trenches of life’s battles—whether that’s managing a family, navigating personal crises, or even dealing with the aftermath of a divorce—this shift is personal. It’s a reminder that in a world full of bullshit shortcuts and half-ass solutions, we deserve tools that respect our intelligence and our autonomy.
Let’s talk about the future, shall we? The horizon isn’t some distant, blurry line—it’s here, and it’s bristling with potential. We’re not just talking about incremental improvements; we’re looking at a fundamental transformation of how we live and work.
In the coming years, the next generation of AI agents won’t be confined to backend processes or corporate workflows. They’ll be your personal sidekick—smart, adaptive, and hyper-responsive to your needs. Imagine an agent that not only handles your schedule but also learns your quirks, understands your mood, and can even offer a well-timed joke when you’re having one of those days. It’s like having a best friend who’s also a rocket scientist.
We’re already flirting with augmented and virtual reality, and soon enough, your agent will exist in a space that blends the digital with the physical. Picture walking down the street and having your agent whisper timely reminders or show you data overlays about your surroundings. It’s the merging of experience with transformation—a digital augmentation of reality that makes you the director of your own life story.
Of course, with great power comes great responsibility. As these agents gain more influence over our personal and professional lives, questions of privacy, security, and ethics will inevitably arise. Who controls the data? How do we ensure that our digital assistants don’t become another means of surveillance or manipulation? These aren’t just technical questions; they’re the kind of real-world dilemmas that hit close to home for anyone who’s ever felt powerless against the juggernaut of modern technology.
It’s crucial that as we embrace the promise of personal agents, we also demand transparency and accountability. We need systems built not only for efficiency but for fairness—tools that augment our agency without selling our souls to the highest bidder. This is where the rubber meets the road: if you’re going to outsource parts of your decision-making to a machine, you better know it’s working in your best interests.
At the end of the day, this isn’t just another tech trend to get hyped over during cocktail parties or board meetings. It’s a fundamental question of autonomy in an increasingly automated world. An AI agent isn’t merely a fancy term for a chatbot or a glorified scheduler—it’s a reimagining of what it means to be in control.
For every engineer waxing poetic about multi-tool workflows, and every exec bragging about first-mover advantages in a market shift, there’s a real human need at stake. Agency is personal. It’s about having the power to shape your destiny rather than being at the mercy of systems designed to herd you along predetermined paths.
Maybe you’re sitting here feeling overwhelmed by the relentless pace of change. Maybe you’re grappling with personal challenges that make every day a battle. I get it—life’s a fucking roller coaster. But here’s the kicker: technology, when wielded right, can be the very thing that returns the reins to you. It can help you cut through the crap, streamline the mundane, and leave more room for what truly matters—your creativity, your relationships, your damn self.
So, if someone tries to sell you on a so-called “agent” that’s really just a half-assed mashup of algorithms with zero true agency, don’t take it lying down. Demand real digital autonomy. Demand an AI that doesn’t just parrot back what you already know, but one that actively partners with you to explore new horizons.
We’ve taken a deep dive into what makes an AI agent tick—from its humble origins as a clunky chatbot to its evolution into a sophisticated personal concierge that promises to transform our lives. We’ve seen how the value proposition has shifted from raw commodities to an era of transformation, where your digital assistant could very well be your lifeline in a chaotic world.
This isn’t just about technology—it’s about reclaiming what’s rightfully yours. In a world where every interaction can either strip you of control or bolster your independence, the emergence of true AI agency is nothing short of revolutionary. And if there’s one thing I’m damn sure of, it’s that we deserve nothing less than the real deal.
So here’s my challenge to the tech world, to the innovators, and to every hustler trying to cash in on the next big thing: stop selling us simulations of agency. If you’re going to call it an AI agent, back it up with the power, the adaptability, and the true autonomy that the term demands. Because in the end, we’re not just looking for convenience—we’re fighting for our ability to shape our own destinies.
John Clem AI Chaplain for THINK protocol and CTO at AI Layer Labs @johnnyclem
Advances in artificial intelligence have ushered in a new era—one in which systems aren’t merely programmed to follow set instructions but can actively decide, adapt, and even learn from their interactions. In this post, we explore how the agentic use of AI agents mirrors the pioneering ideas in Norbert Wiener’s The Human Use of Human Beings while integrating modern insights from Anthropic’s recent work on agent design and agent/RAG (retrieval-augmented generation) patterns.
Drawing inspiration from Wiener’s cybernetic vision, we examine how feedback, communication, and adaptive control can liberate human creativity and free us from mundane tasks—all while reminding us of the need for careful oversight in an age of increasing automation.
Norbert Wiener’s seminal work established cybernetics as the study of control and communication in both living beings and machines. His central argument was that feedback loops—the continuous exchange of information between a system and its environment—allow for learning and self-regulation. In essence, Wiener argued that:
These ideas laid the groundwork for a society in which technology supports and enhances human capabilities rather than simply replacing them.
oai_citation_attribution:0‡en.wikipedia.org
Modern AI agents extend the principles of cybernetics into the digital realm. Whereas earlier systems followed rigid, pre-programmed workflows, today's agents are designed to perceive, plan, and act autonomously. In many respects, these agents embody the same concepts that Wiener discussed:
Additional insights on how agents mirror cybernetic systems are discussed in Anthropic’s guidelines on building effective agents and in Jensen Low’s exploration of agent architecture.
oai_citation_attribution:1‡anthropic.com
oai_citation_attribution:2‡jensenlwt.com
Anthropic’s recent work provides practical guidance on when to deploy agentic AI systems versus traditional workflows:
Agents vs. Workflows:
Simplicity First: Anthropic advises starting with the simplest solution. If a single LLM call or a retrieval-augmented generation (RAG) system can solve the problem, there is no need to add the complexity of an autonomous agent.
Iterative Reasoning and Reflection: Agents equipped with reflection mechanisms can review their intermediate outputs, identify errors, and adjust their strategies. This iterative process not only enhances accuracy but also mirrors the adaptive learning described in Wiener’s cybernetic feedback loops.
Cost, Latency, and Trust: While autonomous agents promise greater flexibility, they often require more computational resources and introduce higher latency. Anthropic highlights the need to balance these trade-offs, especially in applications where timely responses are critical.
For deeper insights into the practical considerations of agent deployment, refer to Anthropic’s blog and Louis Bouchard’s discussion on agents versus workflows.
oai_citation_attribution:3‡anthropic.com
oai_citation_attribution:4‡louisbouchard.ai
Building robust agentic AI systems involves thoughtful design and careful trade-offs. Here are some best practices drawn from both cybernetic theory and contemporary AI research:
For further reading on best practices in agent design, explore resources such as the LangChain Academy and Anthropic’s technical guidelines. Studies like Reflexion by Shinn et al. also provide empirical insights into iterative self-correction mechanisms in AI agents.
oai_citation_attribution:5‡huyenchip.com
oai_citation_attribution:6‡youtube.com
The agentic use of AI agents holds transformative potential. By automating repetitive tasks and assisting in complex decision-making, these agents can free humans to focus on creative and strategic endeavors—echoing Wiener’s vision of liberating human intellect from drudgery. However, there are also important challenges:
By integrating the adaptive, feedback-driven qualities of cybernetics with the flexibility and dynamism of modern AI, we can build systems that not only boost productivity but also enrich our human experience.
The evolution from Wiener's cybernetic systems to today’s AI agents represents a profound shift in how we interact with technology. The principles of communication, feedback, and adaptive learning continue to guide us—now expressed in systems that can reason, plan, and act with increasing autonomy. Anthropic’s insights into when to use agents and how to design them using agentic and RAG patterns provide practical blueprints for this next generation of technology.
As we move forward, it is vital to balance innovation with ethical responsibility, ensuring that AI agents empower rather than control, and liberate human creativity rather than diminish it. The future of work and society may well depend on how thoughtfully we integrate these agentic systems into our lives.
For further reading on cybernetics and Wiener's enduring insights, see The Human Use of Human Beings * oai_citation_attribution:7‡en.wikipedia.org.
For Anthropic’s practical guidelines on building effective agents, refer to Anthropic’s Blog * oai_citation_attribution:8‡anthropic.com and* Agents or Workflows? * oai_citation_attribution:9‡louisbouchard.ai.*
John Clem AI Chaplain for THINK protocol and CTO at AI Layer Labs @johnnyclem