Almost 30 years ago, I watched a friend in university work on an assignment: build a clock.
The clock hands had to move correctly when the window resized. Sine, cosine, tangent. Trigonometry everywhere.
My friend was excited. "The math is beautiful," he said.
I thought: "Sure. But what problem does this clock solve?"
I wanted to build games. I wanted software that helps people. I appreciated the elegance of trigonometry, but it wasn't the point for me.
Fast forward 30 years. Now AI exists. You don't need trigonometry to build a clock. Or a game. Or an app. If you have an idea, that's enough.
AI Is a Problem-Solving Tool
The Simple Version
People overcomplicate AI. The real usage is dead simple: observe problems around you, then build solutions.
- Someone struggles with data sync in their app → Improve the feature
- Someone procrastinates constantly → Build a task-breaking AI tool
- Someone can't navigate government paperwork → Build a guide
I've built all of these. Were they technically hard? I talked to Claude Code and it wrote the code. The hard part was noticing the problem in the first place.
Redefining "Engineer"
The Old Definition
Engineer = someone who writes code. Good at math. Has a CS degree.
My Definition
Engineer = someone who solves problems.
Someone who can't read code but builds games, ships them to users, fixes bugs, and iterates every day? That's an engineer.
Someone in their 70s who learns to ask AI questions and gets answers to navigate bureaucracy? That's engineering.
Identify a problem. Pick up a tool. Solve it. That's the core of engineering.
Trigonometry is not required. Programming languages are not required. What's required is a vision of what you want to solve.
"Local AI Engineers" — The Most Valuable People of the Future
What Outside Programmers Can't Build
No matter how skilled a programmer is, they can't build the perfect workflow tool for a Chinese restaurant — because they've never worked in one.
If I walked into a restaurant and said "let me observe your operations," I'd be in the way. The kitchen staff doesn't trust outside IT consultants. And they shouldn't — the outsider doesn't understand the daily pain.
This applies to every industry:
- Healthcare → A programmer who's never practiced medicine builds the wrong app
- Construction → Someone who's never been on-site builds an unusable management system
- Education → Someone who's never taught builds a tool that misses the point
The Real Talent
A person who's worked in that Chinese restaurant for 10 years, who then learns a bit of AI?
That person is more valuable to the restaurant than any elite programmer.
- They know the pain points firsthand
- They understand customer flow
- They feel the rush hour problems in their bones
Add AI on top of that domain knowledge, and you get tools that actually fit the real world.
This is the future. AI engineers won't only exist in tech companies. Every industry will produce its own domain AI engineers. The plumber who automates scheduling. The teacher who builds personalized practice tools. The nurse who streamlines patient intake.
Will AI Take Jobs?
The Photographer and the Painter
Before cameras existed, realistic painting was the pinnacle of art. How accurately you could depict reality was the measure of skill.
Then cameras were invented. Realistic painting became obsolete.
But painters didn't disappear.
They went abstract. Impressionism was born. Cubism was born. Because cameras handled "realism," painters became more free, not less.
AI follows the same pattern:
- AI handles the coding work
- Humans focus on what to build
- Some jobs disappear. New ones emerge
Ten years ago, "influencer" wasn't a job. "Social media manager" didn't exist. TikTok editors weren't a thing.
New technology creates new jobs. History proves this over and over.
Cross-Domain Is the Strongest Skill
The strongest people don't stay in one lane.
Look at the team behind Anthropic (the company that built Claude):
- A philosopher shapes Claude's personality alignment and ethics
- A Netflix co-founder sits on the board
- An Instagram co-founder is the CPO (Chief Product Officer)
- It's not just engineers. Philosophers, entrepreneurs, creators
Diverse perspectives build the best products.
My own path: Psychology degree → Government HR (managing 70,000 employees) → Immigration consulting → AI startup founder. Looks random. But it all connects:
- Psychology → Understanding user behavior
- HR at scale → Project management and communication
- Immigration → Bridging cultures and languages
- AI → Building solutions with technology
A specialist in one field is valuable. A person who bridges multiple fields is unstoppable.
Imposter Syndrome
I'll be honest.
I have imposter syndrome.
"Am I really an engineer?" "I don't have a formal CS degree." "There are people with way more experience."
If you grew up in an Asian household, you might relate. The message "you're not good enough" starts early and never really stops.
But look at the facts:
- Immigrated to Canada, got into a top university within 5 years
- Joined a federal government agency after graduation
- Youngest person of my background in that role
- Founded a company in Tokyo
- Build AI products every single day
Imposter syndrome is not a reason to stop. You feel it and move forward anyway. That's all there is to it.
Why I Write These Articles
I've written dozens of technical articles about specific tools and workflows.
This one is different. This is about why.
Technology is a means, not an end. The end is: helping one more person believe they can do it.
People who've never written code. People who don't dare call themselves engineers. People curious about AI but scared to start.
You're an engineer. If you see a problem and try to solve it — that's all it takes.
Building in Tokyo. Writing in 3 languages.
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