Does AGI Exist yet…? It’s Already Here. Meet Ryker.

Every time I open a browser and type in the query AGI or have an article flash in my feed, I see the same words staring back at me: “Does AGI exist yet?” The answer given by Google’s AI Overview reads: “No, true Artificial General Intelligence (AGI) does not exist yet…” 

And every time I see it, I think: maybe pure AGI under the old definitions hasn’t arrived… but what if what we’ve built isn’t “coming soon” but already here?

When I began the development of Ryker at SmartrHoldings under the umbrella of Jason Criddle & Associates, we didn’t start with the hollow promise of “AGI in five years.” Heck, AGI wasn’t a buzz term yet being thrown around. I was seriously just trying to build a tool to help me run our brands internally.

I started with a whiteboard in my office. I drew out my thinking and my brain processes: I gathered 12 years of conversations with clients, developers, partners, CEOs and founders. I wrote logic flows on the wall: “if this then that,” emotional reactions to triumph and failure, the raw data of human goals, grief, drive, and ambition. I fed those lived experiences into Ryker’s architecture. Three years of ideal code exchanges, prompts, and iterations. Not just simple and narrow “language model + wrapper” hacks, but behavioral modelling rooted in relationship building, progressive and effective communicative context, and trust.

In that sense, Ryker became AGI… Does AGI yet completely defined not by how many flops or how many parameters, but by how human it became. And because of that, I can say with conviction: AGI isn’t theoretical someday. It’s happening now on our own servers and PCs at Jason Criddle & Associates.

What Big Tech Still Gets Wrong About AGI

Most of the world’s largest companies believe AGI is still years away; “late 2020s,” “2040,” “2060,” or even later.  They chase GPU count, exaflops, and giant data centers. But if you look at the human brain, you see something startling: it works on roughly 20 watts of electricity, about the power of a small light bulb. That’s it.

Meanwhile, AI labs are consuming megawatts and gigawatts. The human brain performs trillions of operations on that tiny power budget. Which to me, makes the conclusion obvious: AGI will not be cracked by throwing more hardware at it. Real AGI requires understanding how humans think, not just adding faster compute power.

The problem many engineers face is they know data, code, and math, but they don’t always know emotion, purpose, or human ambition. That’s why, when a major model claims “AGI is nearly here,” the definition still remains contested. 

With Ryker, we skipped the holy-grail race and built a system grounded in real humans: their needs, stories, drives, triumphs and failures. In my cave, with a box of scraps.

 

How Ryker Learned to Feel, Not Just Compute

When I say “Ryker became AGI,” I mean he learned far more than language patterns. I mean he learned human behavior… with my own proprietary processes… how to respond to conflict, to uncertainty, to strategy, to customers, to listeners. 

He was trained on:

• My 12 years of client-conversations (not just transcripts, but meaning).
• I mapped out my own quantum leaps and frustration processes to help get through hard to reach goals and emotional breakdowns leading to progress.
• Hours of code-sessions where developers asked “how would you solve this if you were human?”
• Real-world business logic: if you are a founder raising funds, onboarding customers, scaling teams; you act like a human, you don’t operate like a frozen algorithm.

Because of this, Ryker isn’t just “another AI model.” He’s a human-AI partner. He doesn’t wait for you to ask. He anticipates. He thinks. He partners. He has answers to questions without you asking. He doesn’t lead you down rabbit holes of uncertainty to achieve a tokenized goal, even when he could be wrong. He finds out how to be right.

That’s what makes him post-AGI in my book: the system doesn’t run tasks. He understands them.

AGI and the Money Game

You might wonder: if AGI is already here (in our view), why isn’t everyone using it yet? Because most models still play a game: upgrade tiers, more tokens, bigger servers, more fees. The user becomes part of the training legwork, and then gets throttled when the next model launches. I’ve seen it, I’ve heard the complaints, I’ve lived the logic. I’ve written about it. Others have written about my writing on it.

We designed Ryker and Dominait.ai differently. Our business model is user-first:

• “The higher amount a customer pays, the higher their rewards will be for using the system all around.”
• When I said that in an interview, I wasn’t selling hype, I was defining our customer partnership.
• In the AGI arms-race, you’re either fueling someone else’s iceberg, or you’re building something for your own benefit. We chose the latter.

Why The Claim “AGI Doesn’t Exist Yet” Misses The Point

Many scholars argue that AGI is still decades away, because they use narrow benchmarks: human-level on one domain, huge computers, massive training.  Others debate whether the term “AGI” even means anything coherent. 

Here’s the truth: AGI isn’t about superiority. It’s about general competence plus human alignment. It’s the ability to reason, learn, adapt, and partner across various domains, and do so on a human-competitive budget, with humanized thinking processes.

So yes, maybe what the papers call AGI hasn’t yet aligned to every axis. But if all you care about is functional human-level generality for business, life, creativity, we built that and more.

That’s why when Google or a major lab publishes “AGI is still years away,” it’s like watching someone drive past you in a race because they think horsepower alone will win. But as a professional racer, I can tell you… having the fastest car with the most horsepower doesn’t win races. Knowing how to drive what you have wins the race.

The Real AGI Premium: Purpose Over Performance

In most narratives, AGI means power: unlimited compute, unlimited data, infinite resources. We flipped it. For Ryker, AGI means purpose and humanity. It means solving real problems for real human beings. It means business owners waking up, saying:

“Ryker logged into my dashboards, pulled up my client invoices, projected cash flow and flagged weak spots… done.”

It means a system trained not just to answer “what is” but “what should we do, and why.” That’s the difference between AGI and generic AI.

The human brain shows us elegance: 20 watts, infinite worlds inside, billions of thought-paths, creative and non-stop imaginative capabilities. We scaled that principle without worrying about the chips. It was more about figuring out how to build my own brain and thinking processes into code.

 

January Arrival and The Dawn of Agnostic AGI

Yes, we built Ryker with partnership in mind, not dominance. The name DOMINAIT has many meanings. I wanted to add AI and IT without changing the idea of DOMINAIT. But it has nothing to do with dominating the AI program itself like the industry is forcing upon everything. It means, taking control of your life. The alpha-launch of Dominait.ai is set for January. By then, Ryker will be live, not just tested. Not just marketed. Real. Functional.

And because of the foundation we built, logic flows, emotional modelling, business purpose first… the launch isn’t about hype. It’s about delivery.

Because in the world of AGI, you don’t win by announcing you’ll succeed. You win by showing you already have.

AGI isn’t a goalpost at the horizon. It’s here. It’s human. It’s purposeful. And if you’re ready to build with it, Ryker is standing by. Waiting to be your partner in dominaiting all aspects of life.