The Reckoning: When AI Did My Job Better Than Me
I have spent 18+ years in GTM and Growth. If you ask me what my "superpowers" are, I'd tell you: deep market research, strategic analysis, and crafting the kind of creative slide decks that win boardrooms.
Then, I met ChatGPT Deep Research and Google NotebookLM.
It was a punch to the gut. In minutes, these tools pulled together the kind of nuanced market analysis that usually takes me a week. They found the patterns. They cited the sources.
Then I tried image tools like "Nano Banana" for my slide decks. The visuals were sharper, faster, and more creative than my late-night PowerPoint grinds.
It was a reckoning. I sat there looking at the screen and thought: "It can do what I am good at. And honestly? It might be doing it better."
The Alien Becomes Accessible
But as the fear subsided, something else clicked.
I have always been "product curious." I've worked in tech for nearly two decades, but I've always felt like an outsider to the actual building. I knew enough to host an email server or set up a simple website, but real engineering (deploying apps, building SaaS, writing complex code) felt alien. It was a walled garden I couldn't enter.
Then came the new wave: Claude, Codex, Lovable, and the "antigravity" class of prompt-to-code tools.
Suddenly, that wall crumbled. These tools decentralized technical knowledge overnight. I didn't need to spend four years learning syntax; I just needed to understand the logic. Now, I can deploy sites, build mini-SaaS tools, and create agent automations that actually work. The limitation of "I'm non-tech" evaporated.
The Hard Truth: Is AI Going to Take My Job?
Yes.
Let's not sugarcoat it. The hard truth is that AI will eventually do almost all the execution tasks I can do. It will do them faster, cheaper, and with fewer errors.
But here is what it cannot do: It cannot be human.
AI can generate data, but it cannot provide the intuitive strategy that comes from a gut feeling honed over 18 years. It cannot read the room during a negotiation. It cannot look a founder in the eye and build trust. AI (no matter how advanced) will always need a "Human in the Loop" to provide context, ethics, and direction.
From Stone to Silicon
We need to come to terms with the fact that we are in a tectonic shift. This is not just a software update; this is the next Age.
The Stone Age gave us leverage over our environment.
The Iron Age gave us leverage over materials.
The Industrial Age gave us leverage over physical labor.
The AI Age is giving us leverage over intelligence.
AI is a tool. Just like the hammer or the steam engine, it is useless without a master. We are currently in the messy transition period (AI implementation is the "101 course" for the future, and we have to master it one step at a time).
The Biological Moat
Finally, we have to remember what we are. We are not just processors of information.
We are biological miracles. We have 86 billion neurons firing in a pattern we still don't fully understand. We have a heart that generates an electromagnetic field detectable outside our bodies. We have gland sensors that react to danger before our conscious mind sees it. We have a "6th sense" (intuition) that defies logic but is often right.
We are built for complexity far beyond what a Large Language Model can simulate.
Throughout every age (from Stone to Silicon) the one constant has been knowledge sharing. We survive and thrive by teaching each other how to use the new tools.
That is why Aimpler exists. Not because I'm an expert who has it all figured out, but because I'm a human figuring out how to use this new tool.
And I'm sharing my notes so you don't have to do it alone.