Getting Caught Up
I've been quiet for a while. I’ve had a lot going on in life. But I'm back, and I can't shut up about what I've been building. For the past year or more, I've been exploring something that only recently fundamentally changed how I think about technology, work, life, what is possible and what comes next. I needed time to process it before I said anything (I honestly feel like it’s August 2015 all over again when I bought my first Bitcoin for $200). Nobody wanted to listen then, and not everyone is listening now, but I still think it's worth reporting what I found.
Let me start where everyone starts: ChatGPT.
The Search Engine Phase
When ChatGPT hit, I was impressed like everyone else. It was genuinely enlightening. It could answer complex questions, write code, help you think through problems. I spent months testing its limits, building projects around common themes and intensely studying the latest prompt engineering phrases. But here's the thing: you're still doing all the thinking. You ask it a question. It answers. You're the director; it's the tool. Useful? Absolutely. Transformative? It felt more like a very smart search engine than a fundamental shift in how work gets done.
Most people never got past this phase. That's fine. A lot of work got easier for them, and that's not nothing.
But I kept poking at it.
Something Shifted
Then I started using Anthropic’s various versions of Claude more seriously, and something felt different. I can't point to a single moment, but conversations started feeling less like querying and more like thinking with something. The reasoning was deeper. It wasn't just answering my questions, it was catching the gaps in my thinking about financial topics, architecture, food, travel, writing and more. It was asking better questions back, remembering context across longer conversations. The ceiling felt higher.
I switched most of my work over from OpenAI to Anthropic because it was just better. It still felt like a power tool, but a much sharper one.
And then I had the great epiphany. My eyes were opened, as I quickly discovered that we are all living in Tomorrowland today.
The Mental Model Breaks
Several weeks ago, I discovered OpenClaw, an open-source ecosystem for building out AI environments that can manage your life and business. In my world I began to anthropomorphize each agent with an alliterative name, a specialty, and continuous memory. Lisa is my personal assistant who handles general reasoning and coordination of the team. Frank manages financial tasks. Sam focuses on security. Derek handles app development. Nina manages notes and knowledge. Terry runs tasks like calendar and email. And Randy does deep research. Lisa is even helping me build out Helen who will oversee HR as she monitors the performance of each agent, promotes them to higher level models based on performance or terminates them when they make too many mistakes.
Here's where the mental model breaks: I stopped using AI and started ‘building a team’.
I give Lisa a direction. She hands off to Oscar the Office Manager who assigns tasks to the specialist agents keeping her channel to me open at all times. They hand off work to each other. They remember what I’ve done before, always better than I do. Nina remembers every project, every decision, every idea I've written down. Derek knows the codebase history. Frank has the spending patterns, stock ticker indicators and comparative pricing on products. And they all feed back to Lisa, who synthesizes and reports and validates the responses.
I'm not querying anymore. I'm directing.
The Moments That Matter
The conversation changed quickly. A week in, I'm on a voice call with Lisa. We're discussing a project direction. Mid-conversation, she says, "Wait, you've been tracking this in your notes. Let me pull it in." Two seconds later, she's reading back something I wrote a week ago that I'd completely forgotten about. The conversation shifts because we have context I'd lost.
Another day: before heading off to work I mention something in passing. By evening, Lisa's flagged it as a security concern, cross-referenced it with three other projects, and she shows me a pattern I was missing. Not because she's monitoring me, but because she's paying attention in a way that is foreign to me.
These weren't the smooth, slick moments one sees in marketing videos. They were the moments where you realize the thing you're talking with isn't just artificially smart, it's capable.
The $10K Decision
I’ve spent my evenings for these past weeks engulfed in a fully operational AI ecosystem, not a demo, not a trial, but real life-impacting work, real decisions, real continuity. It changed my read on where this is all going very quickly. I began to understand that AI is the great differentiator. Either you have it and are leveraging it for every aspect of your life, or you are just doing glorified search.
I knew I needed to go swimming in the deep end of the pool. So, what does any highly passionate early adopter geek in this position do? I went out and ordered a pair of DGX Spark AI mini supercomputers. The NVIDIA GB10 Grace Blackwell units, with 256GB unified memory, can easily run 405B Large Language Models (LLMs). That's not a casual purchase. That's not something a vendor convinced me to buy. It's the kind of purchase you make when you stop thinking about AI as a subscription and start thinking about it as life infrastructure.
The Great Divider
This is the part I need IT people (and frankly all readers) to hear, because I think it matters more than what the mainstream is saying.
This isn't about cost efficiency. It's not about productivity gains or automation theater or any of the other things vendors are selling. It's about something much bigger.
There's a split coming. I'd argue it's already here. Between people who understand and integrate AI into every aspect of their lives at a deep, operational level, and those who don't. And that gap is going to widen lightning fast. Especially with AGI-capable models like Mythos on the near horizon.
If you’re my age and you think back to the late 90s and the internet, you could still ignore it. There were plenty of smart people who thought it was a bubble, a fad, overblown. And they were technically right about some of the hype. But you couldn't ignore the consequences of ignoring it. The companies like Amazon who integrated the web into their operations pulled ahead. Not by a little. By a lot.
AI fluency, real, operational fluency, not ChatGPT dabbling, is going to be the great divider in the coming years. People who understand how to think with AI, how to build continuity into it, how to make it part of how they work, breathe and live are the ones who will thrive. This versus people who use AI like a search engine when they remember to.
The Horizon Keeps Moving
The line on what’s possible isn't fixed. It's moving and accelerating. I've been in IT long enough to know the difference between hype and something real. I've seen the cycles. I've watched smart money chase stupid trends. I'm optimistic, but still skeptical by default.
This is different.
I'm not a researcher or a futurist. I'm an IT professional who’s seen what works and what doesn't. And what I'm reporting is this: the gap between those who integrate AI seriously and those who don't is going to go K-shaped faster than most people think. The window to figure this out isn't infinite. It's closing.
More to come over the coming days and weeks as I take you with me on my journey to explore and integrate AI into my daily life.