At sixteen, he realized something important: genius meant nothing if you didn't use it.
For years, he'd been hiding his intelligence, keeping his head down, not wanting to stand out too much. But the more he learned, the more he saw the flaws in the world around him—problems that could be fixed if someone just had the right tools.
So, he decided to build them.
Mornings: School.
Afternoons: Self-study in physics, electronics, and computing.
Nights: Programming and hardware experiments in the garage.
It was exhausting. It was frustrating.
And he loved every second of it.
The First Code: Teaching a Machine to Think
His journey into coding started with a beat-up Commodore 64 that he convinced his parents to buy. It was slow, clunky, and primitive—but it was his.
His first program? A basic calculator written in BASIC. It wasn't much, but watching the computer respond to his instructions felt like a superpower.
But BASIC was too simple. He needed more control.
So, he moved on to Pascal, which forced him to structure his thinking. He learned about loops, conditionals, and memory management, absorbing everything like a sponge.
Then came C—the language real engineers used.
C was brutal. It didn't hold your hand. One missing semicolon and nothing worked. But once he got past the frustration, he saw its power. With C, he wasn't just making simple programs—he was bending the computer to his will.
The First Attempt at AI (And Why It Failed)
The idea came from frustration.
He was researching physics for a school project and realized something: finding information was slow and inefficient. He had to search manually, scan books, and cross-reference sources—it wasted hours.
What if he could build a program that searched for him?
His first attempt at an AI—Echo 1.0—was an absolute disaster.
It misinterpreted simple commands.
It couldn't tell relevant information from useless data.
It crashed constantly whenever he asked complex questions.
But failure didn't mean stopping. It meant learning.
He studied early AI research, especially expert systems—programs that mimicked human decision-making using if-then rules.
Instead of coding an AI that "thought" like a human, he built a knowledge-based system.
Echo 2.0: A Smarter (But Still Limited) Assistant
He rewrote Echo using LISP—the programming language used in early AI research.
This time, it worked better.
It could scan research papers and summarize key points.
It could cross-check sources and detect biased information.
It could suggest related topics, helping him research faster.
But it still wasn't true AI. It wasn't "thinking"—it was just following complex rules.
It was like training a very obedient librarian rather than an actual intelligence.
When he showed Echo to Dr. Langston, his physics teacher, the man just stared.
"You… you built this yourself?"
He nodded.
"This isn't high school work," Langston muttered. "Honestly, this isn't even college work."
For the first time, he realized he was doing more than just playing with code.
He was building something real.
From Software to Hardware
Writing code was one thing. Making machines think and act was another.
So, he started learning electronics.
His dad, Jack, had a toolbox full of old circuit boards, wires, and broken appliances. He took everything apart—radios, clocks, even their old TV—to see how they worked.
His first real project?
A motion-activated light system.
If someone entered a room, the lights turned on.
If they left, the lights turned off.
Simple—but effective.
His next challenge? A home automation system—years ahead of its time.
Using a Motorola 68000 microprocessor, he built a system that could:
✅ Turn lights on and off based on movement.
✅ Lock and unlock doors using a voice passcode.
✅ Adjust room temperature based on daily patterns.
When Monica saw it in action, she blinked.
"Okay. When exactly did you turn into a mad scientist?"
He smirked. "Somewhere between algebra and physics class."
Jack, on the other hand, was just happy his son was finally using tools.
"You know," Jack said, watching him solder a circuit board, "if this whole genius thing doesn't work out, you could always be an electrician."
He didn't bother responding to that.
The MIT Connection
By seventeen, he had outgrown high school teachers.
So, he found new mentors.
He started attending guest lectures at Columbia and MIT, sitting in on talks about AI, robotics, and physics.
At one event, Dr. Michael Reeves, an MIT professor specializing in artificial intelligence, gave a talk on early neural networks.
After the lecture, he waited in line to ask a question.
When it was finally his turn, he said, "Your model is impressive, but wouldn't it struggle with computational efficiency at scale? The learning algorithm isn't optimized."
Dr. Reeves raised an eyebrow. "That's… an advanced observation. Are you a grad student?"
"High school."
Silence.
Then, Dr. Reeves did something unexpected.
He laughed.
"Alright, kid. Tell me your name."
That conversation didn't get him immediate access to MIT's robotics lab—but it started a connection. Over the next few months, he kept in touch with Dr. Reeves, sharing ideas, getting feedback, and refining his understanding of AI.
The Missing Piece: Business
By eighteen, he had built:
✅ An advanced expert system (Echo 2.0).
✅ A functional smart home system.
✅ A deep understanding of coding, electronics, and AI research.
But something was missing.
One day, while watching MIT students work on a startup, he realized:
Brilliance wasn't enough.
Most geniuses stayed in research labs, publishing papers while companies made billions off their ideas.
He didn't want to be one of them.
If he wanted to change the world, he needed to understand business.
So, he added new topics to his self-education:
Economics—how companies grow and compete.
Finance—how investment works.
Negotiation—how deals are made.
At first, it was frustrating. He could build intelligent machines, but understanding balance sheets and market strategies? That was another story.
But just like with programming, he figured it out.
By the time he graduated high school, he wasn't just a scientist.
He was a future entrepreneur.
The Road Ahead
He had spent his childhood hiding his abilities.
Now?
He was going to use them.
The world wasn't ready for what he was about to build.
And he couldn't wait to prove it.