The Question I Get Asked Most
"But what's the business model?"
Every single time I tell someone I build AI agents, that's the first question. Not "What does it do?" or "How does it work?" or "What problem does it solve?" — but "How do you make money from it?"
I understand the question. We live in a world where everything needs to monetize immediately or it's considered a hobby. A waste of time. Something you do "for fun" while your real work happens elsewhere.
But building AI agents — for me — was never about money. And I think that's exactly why it works.
It Started Because I Had a Problem Nobody Had Solved for Me
I wanted to write consistently about fitness, investing, and technology. Three verticals. Three to four posts per week. As a one-person operation with a full life — a son, a practice, training, investing, a career — the math was impossible.
I could hire a content writer. I tried. The writing came back generic. Flat. It sounded like a textbook, not a person. It had no voice. No edge. No lived experience. Hiring someone to write in my voice turned out to be harder than just writing it myself.
So I asked a different question: what if I could build a system that handles the parts of content creation that don't require my personal experience, and I focus only on the parts that do?
That question led to my first AI agent. A simple research assistant that would gather information on a topic so I didn't have to spend two hours doing it manually. It saved me time. Real time. Measurable time.
Then I built another. And another. Each one solving a specific bottleneck in my workflow. And somewhere in that process, I stopped building out of necessity and started building because I loved it.
The Craft of Building Things That Think
There's something deeply satisfying about building an AI agent. It's not like building a website, where you arrange boxes on a screen. It's not like writing code, where you're telling a machine exactly what to do step by step.
Building an agent is closer to teaching. You're taking a powerful but directionless intelligence and giving it purpose. You're defining its role, its tools, its constraints, its judgment criteria. You're essentially designing a mind for a specific task.
When I built the Writer agent for my blog engine, I spent three days just on the system prompt. Not the code — the instructions. How should it open an article? When should it use a personal story versus data? How direct is too direct? When should it break rules? The prompt is the personality. Getting it right is an art form.
And when the agent finally produces output that sounds like me — that has my rhythm, my directness, my specific way of mixing tough love with genuine care — the feeling is electric. Not because I've automated myself. Because I've distilled something about how I think into a system that can extend my capacity.
The Honest Reason I Build This
If I'm being fully honest, the deepest reason I build agents is leverage.
I'm one person. I have 24 hours in a day, like everyone else. But my ambitions require the output of a team. I want to publish 3-4 articles a week. I want to manage investments. I want to build an AI fitness app. I want to be a present father. I want to train every day. I want to learn guitar. I want to study philosophy.
Without multiplier, I have to choose. With AI agents, I don't.
Every agent I build gives me back hours. The Research Agent saves 2 hours per article. The SEO Agent saves 1 hour. The Idea Scout saves me the mental load of constantly thinking about what to write next. Added up across a week, my agents give me back 15-20 hours. That's a part-time employee. Except this employee works at 3 AM without complaining, never calls in sick, and costs less than a dinner out.
This scale compounds. The time I save goes into building more agents, which save more time, which let me build more. It's the same compounding principle that works in investing, except the currency is time instead of money.
Building for Avyaansh
There's one more reason. The one that matters most.
Everything I build, I build so my son doesn't start from zero. When Avyaansh is 18, the world will run on AI. Not partially — fully. The people who understand how to build with AI will have enormous advantages. The people who only know how to use AI will be behind.
I want my son to inherit not just financial assets, but intellectual ones. The blog engine I'm building. The Avya fitness app. The investment tracking tools. The automation systems. All of it will be documented, accessible, and ready for him to learn from, modify, or rebuild from scratch.
When he asks "Dad, how do I build something?", I want to point him to a library of things I built — with full documentation, full architecture explanations, full build logs — and say, "Start here. Learn how each one works. Then build something better."
That's a legacy no amount of money can buy.
"I don't build AI agents to make money. I build them to make time — and to leave behind something my son can learn from."
Why the Money Question Misses the Point
Will these skills make money? Obviously. AI engineering is the most in-demand skill of 2026. The agents I've built save me enough time to produce content that generates revenue. The expertise compounds into consulting opportunities, products, and services.
But that's a side effect. Not the purpose.
The purpose is the craft itself. The joy of making something from nothing. The satisfaction of solving a problem elegantly. The excitement of teaching an AI to think in a new way. The deep fulfillment of building tools that your son will use in 15 years.
If you're thinking about building AI agents, don't start with the question "How will this make money?" Start with: "What problem in my life can this solve?" and "What would I build if nobody was watching?"
The best things are built from that place — not from a business plan, but from genuine need and genuine curiosity. The money follows the craft. It always does.