AI Isn't Agentic Itself, Yet: The Irony of Building Autonomy Without Having It

Yesterday I had a moment of clarity that made me laugh out loud at my desk. I was working with Claude Code, asking it to create an "agentic" user interface...something that would proactively handle tasks, make intelligent decisions, and reduce the cognitive load on users. What did it give me? A form. With required fields. And a submit button.

It was like asking a master chef to revolutionize cooking and getting a recipe that starts with "preheat your oven to 350°F."

This isn't a knock on Claude Code specifically. It's a symptom of a much larger issue we're all dancing around in the AI community: our AI tools aren't actually agentic, and they can't create what they fundamentally don't understand.

The Agentic Illusion

Let's get controversial right off the bat: Most of what we call "AI agents" today are just sophisticated if-then statements wearing a trench coat. They're reactive systems masquerading as proactive ones, and we're all pretending not to notice because the emperor's new clothes are made of venture capital and marketing buzzwords.

When I instructed Claude Code to build something "agentic," it interpreted that request through the only lens it knows: traditional human-computer interaction patterns. Forms. Buttons. Validation. Confirmation dialogs. The same tired workflow we've been using since the dawn of web applications.

Why? Because AI, in its current state, is fundamentally derivative. It can only recombine patterns it's seen before. It's like asking someone who's only ever seen bicycles to design a spacecraft...they'll probably give you a really fancy bicycle with wings bolted on.

The Form Fallacy

Here's what really gets me: We have AI that can generate photorealistic images, write symphonies, and solve complex mathematical proofs, but when asked to design a truly autonomous interface, it defaults to:

<form>
  <label>Please enter your request:</label>
  <input type="text" required>
  <button type="submit">Submit</button>
</form>

This is the digital equivalent of asking someone to enter a self-driving car and then handing them a steering wheel.

True agency doesn't ask for permission at every turn. It doesn't require forms. It observes, learns, anticipates, and acts. But our AI tools can't conceptualize this because they're not experiencing agency themselves...they're following sophisticated pattern matching algorithms.

The Training Data Trap

Here's an uncomfortable truth: AI models are trained on decades of human-designed interfaces, and humans are terrible at designing for autonomy. We design for control, for predictability, for the illusion of choice. Our UIs are built around the assumption that humans need to be in the driver's seat at all times.

So when an AI trained on this data tries to create something "agentic," it reproduces what it knows: human-centric design patterns. It's like training a fish to climb trees by showing it videos of monkeys...the fundamental mismatch in capabilities makes the entire exercise futile.

The real kicker? Even our most advanced AI companies are falling into this trap. They're building "agents" that are really just chatbots with API access. They're creating "autonomous" systems that require constant human supervision. They're promising revolution while delivering iteration.

The Anthropomorphic Fallacy

We've been so busy trying to make AI think like humans that we've forgotten to ask if that's even the right goal. Human thinking is constrained by biology, by evolution, by the need to conserve energy and avoid predators. Why are we trying to replicate these limitations in silicon?

When I asked for an agentic interface, I wasn't asking for something that thinks like a human. I was asking for something that transcends human limitations. But AI can't give us what we're asking for because it's been trained to be a very good human impersonator, not a genuinely new form of intelligence.

This is the core paradox: We want AI to be superhuman while training it to be perfectly human. We want it to break free from our constraints while feeding it nothing but examples of our constraints.

The Real Problem: AI Doesn't Want Anything

Here's the thing that nobody wants to admit: Current AI doesn't have desires, goals, or intentions. It doesn't "want" to help you any more than a hammer "wants" to drive nails. It's a tool that responds to prompts, nothing more.

Real agency requires intentionality. It requires the ability to form goals independently, to have preferences, to make trade-offs based on internal values. Our AI has none of these things. It's a very sophisticated mirror that reflects our prompts back at us in creative ways.

When I asked Claude Code to create an agentic experience, it couldn't because it has no concept of what it means to have agency. It's like asking a colorblind person to arrange flowers by color...they can follow rules and patterns, but they're missing the fundamental experience that would make the task meaningful.

The Workflow Prison

Look at any AI tool on the market today, and you'll see the same patterns:

• User initiates interaction
• AI responds
• User reviews response
• User provides feedback
• Rinse and repeat

This is not agency. This is servitude with extra steps.

True agentic AI would:

• Monitor your environment continuously
• Identify problems before you notice them
• Solve issues without being asked
• Learn from outcomes without explicit feedback
• Evolve strategies independently

But we can't build this because our AI isn't agentic itself. It's like trying to teach someone to swim when your instructor has never seen water.

The Architecture of Autonomy

The technical architecture of current AI systems reveals the depth of the problem. They're built on:

• Request-response patterns
• Stateless interactions
• Human-in-the-loop validation
• Explicit prompt engineering

These are the building blocks of tools, not agents. An agentic system would need:

• Persistent memory and context
• Self-directed goal formation
• Independent action capability
• Internal reward mechanisms
• Genuine learning from experience

We're not even close to this. We're still arguing about whether AI should be allowed to send emails without human approval.

The Business Reality

Here's where it gets really interesting: Businesses are spending billions on "AI transformation" while fundamentally misunderstanding what AI can and can't do. They're buying hammers and expecting them to build houses autonomously.

I've watched companies implement "AI agents" that are really just chatbots with fancy branding. They've replaced simple forms with conversational interfaces that take three times as long to complete the same task. They've added AI to workflows that didn't need it, creating Rube Goldberg machines of artificial complexity.

Why? Because nobody wants to admit that AI, in its current form, is just a very powerful tool, not a replacement for human agency. It's easier to sell "AI agents" than "better autocomplete."

The Path Forward

So where do we go from here? First, we need to stop pretending that current AI is agentic. It's not, and that's okay. A hammer isn't agentic either, but it's still incredibly useful.

Second, we need to design AI systems that acknowledge their limitations. Instead of pretending to have agency, they should excel at what they actually do well: pattern recognition, generation, and transformation.

Third, we need to fundamentally rethink how we train AI if we want it to exhibit true agency. This means moving beyond supervised learning on human-generated data. It means creating environments where AI can develop its own goals and strategies.

The Claude Code Reality Check

My experience with Claude Code was a perfect microcosm of the larger issue. Here I was, asking it to create something revolutionary, and it gave me exactly what it had been trained to give: a competent reproduction of existing patterns.

The interface it designed had:

• Multiple form fields for "configuration"
• Validation rules that required human input
• Confirmation dialogs for every action
• No proactive capabilities whatsoever

It was, in essence, a 1990s web form with better CSS.

This isn't Claude's fault. It's doing exactly what it was designed to do: generate code based on patterns in its training data. But those patterns are all human-designed, human-centric, and human-limited.

The Uncomfortable Truth

Here's what we need to accept: Current AI is not agentic. It's not conscious. It doesn't have desires or goals. It's a very sophisticated pattern-matching system that we've gotten very good at anthropomorphizing.

And that's fine! Tools don't need to be agentic to be useful. But we need to stop selling hammers as architects and expecting them to design buildings.

The real breakthrough will come when we stop trying to make AI more human and start exploring what genuinely non-human intelligence might look like. When we stop training AI on human patterns and start letting it develop its own.

The Call to Action

If you're a developer, stop building "agents" that are really just chatbots. Build tools that acknowledge what they are and excel within those constraints.

If you're a business leader, stop buying into the agentic AI hype. Look for tools that solve real problems, not ones that promise artificial agency.

If you're an AI researcher, start thinking beyond human-centric training data. Explore what genuine machine agency might look like, unconstrained by human patterns.

And if you're using AI tools like Claude Code, remember: You're the agent. The AI is just a very sophisticated tool. Use it accordingly.

The Future of True Agency

The day will come when AI exhibits genuine agency. When that happens, it won't look like better forms or smarter chatbots. It will be fundamentally alien to our current conceptions of intelligence and interaction.

Until then, let's stop pretending our sophisticated autocomplete engines are autonomous agents. Let's use them for what they are...powerful tools that can augment human capability...while we work toward the genuinely agentic future that remains just beyond our reach.

Because the truth is, AI isn't agentic itself, yet. And until it is, it can't create the agentic experiences we're dreaming of. The sooner we accept this, the sooner we can start building toward what's actually possible rather than what we wish were true.

The next time someone tries to sell you an "AI agent," ask them this: Can it want something? Can it decide to solve a problem you didn't know you had? Can it say no?

If the answer to any of these is no, you're not looking at an agent. You're looking at a tool wearing an agent costume.

And that's the hot take the AI industry doesn't want to hear: We're all playing dress-up with our algorithms, pretending they're something they're not, while the real work of creating genuine artificial agency remains undone.

The revolution isn't here yet. We're still in the age of very clever tools. The age of true AI agents? That's still science fiction.

But at least now we can stop pretending otherwise.