There’s a fear running through every industry right now: AI is coming for my job.

Writers, designers, coders—they’re all worried about ChatGPT and Claude. Especially when a new model drops and demonstrates capabilities that seemed impossible six months ago. Each release ratchets up the anxiety: How long until this thing can do what I do?

But after a year of building heavily with these tools, I think this framing misses the point entirely.

AI isn’t replacing jobs. It’s replacing how jobs get done.

And the skill that’s emerging as universal? AI Engineering.

“The Hottest New Programming Language Is English”

Andrej Karpathy—former Tesla AI Director, OpenAI founding member—put it perfectly:

“The hottest new programming language is English.”

This isn’t a joke. It’s the new reality.

The ability to clearly articulate intent, break down problems, and iterate on AI outputs is becoming the core competency across every role. Whether you’re deploying infrastructure or designing a logo, the workflow is the same: define intent, prompt the system, validate the output, iterate.

That’s engineering. And everyone is doing it now.

What “AI Engineering” Actually Looks Like

Let me make this concrete with examples from my own work.

Cloud & DevOps → Prompt Engineering

In The Speed of AI-Assisted Development, I fixed a Python Lambda function, debugged a GitHub Actions pipeline, and deployed a new frontend—all in under an hour. I didn’t write the MIME parsing logic or look up the S3 CLI flags. I described what I needed. The agent wrote the code.

When I consolidated my domains using CloudFront Functions, I didn’t memorize the request.headers.host.value syntax. I defined the architecture—“redirect these hosts to this target with a 301”—and engineered the prompt to get working code.

The engineering wasn’t typing. The engineering was:

• Choosing the right architecture (CloudFront Function vs. S3 redirect buckets)
• Validating the AI’s logic against edge cases
• Orchestrating the deployment

Content Creation → Prompt Engineering

When I write for this blog, I’m often acting as an editor-in-chief for an AI staff writer. I provide structure, context, and voice. The AI drafts. I refine.

When I need visuals, I don’t open Photoshop. As I explored in AI Image Generation, I engineer the prompt—tweaking negative prompts, adjusting seeds, iterating until the output matches my vision.

Same discipline. Different domain.

Every Role Is Becoming AI Engineering

Think about what’s actually happening across industries:

Traditional Role	New Reality
Software Engineer	Orchestrating coding agents, validating AI-generated code
DevOps Engineer	Prompting infrastructure agents, reviewing IaC outputs
Writer	Directing LLMs, editing AI drafts for voice and accuracy
Designer	Engineering image generation prompts, curating outputs
Manager	Using AI for strategy synthesis, communication drafting

The job titles may stay the same. But the core skill is converging: the ability to effectively collaborate with AI systems.

That’s AI Engineering.

The Question That Matters Now

As I wrote earlier today in Ask Better Questions or Get Left Behind, Jensen Huang’s advice cuts through the noise:

“How does AI help me do my job better?”

Not hypothetically. Not someday. Today. In your role.

The people who keep asking that question—and keep refining their ability to work with AI—are the ones building leverage. Everyone else is just using a smarter Google.

The Human Stays in the Loop

Does this mean humans become irrelevant? No. As I discussed in Humans in the Loop in the AI Era, this shift makes human oversight more strategic, not less.

When AI handles execution, humans provide:

1. Judgment — Is this output correct? Appropriate? Good?
2. Context — What’s the real problem we’re solving?
3. Direction — Where should we go next?

AI isn’t replacing your job. It’s promoting you to Lead Engineer of your own AI workforce.

Final Thought

The hottest programming language is English.
The emerging universal skill is AI Engineering.

And the question isn’t whether AI will change your job.
It’s whether you’ll learn to engineer with it—or get left behind.

Jensen Huang on Using AI Early in Your Career

“The people who stand out aren’t the ones asking AI random questions, they’re the ones asking how AI helps them do their job better.”
— Jensen Huang, CEO of NVIDIA

That line hits harder in today’s market than it would have a few years ago.

Right now, unemployment for ages 20–24 has jumped to ~9.2%, a level usually seen during recessions. New grads are competing in a market where credentials matter less and leverage matters more.

AI isn’t the advantage by itself.
Knowing what to ask is.

The Wrong Way to Use AI (Most People Are Here)

Most people treat AI like:

• A smarter Google
• A code generator
• A homework helper
• A content writer

So they ask:

• “Explain Kubernetes”
• “Write this function”
• “Summarize this article”
• “Make me a resume”

That might save time.
It does not create leverage.

The Right Question (The One Jensen Is Pointing At)

Instead of asking:

“What can AI do?”

Ask this, persistently:

“How does AI help me do my job better?”

Not hypothetically.
Not someday.
Today. In my role.

That single question reframes AI from a tool into a multiplier.

The Question, Applied to You

Here’s how that question looks when you actually operationalize it.

If You’re a Student or New Grad

Wrong question:
“Can AI explain this topic?”

Better question:
“How can AI help me learn this faster than everyone else?”

Best question:
“How can AI help me build proof that I can already do this job?”

Concrete uses:

• Turn lectures → interview-ready explanations
• Convert assignments → portfolio artifacts
• Simulate interviews weekly
• Build tiny demos instead of just studying

Outcome:
You stop competing on GPA and start competing on evidence.

If You’re an Engineer

Wrong question:
“Can AI write this code?”

Better question:
“How can AI help me ship higher-quality systems faster?”

Best question:
“How can AI turn me from a ticket-closer into a systems thinker?”

Concrete uses:

• Pre-think designs before reviews
• Generate test strategies & edge cases
• Turn vague tasks into clear plans
• Document decisions and tradeoffs

Outcome:
You look senior earlier, because you think in systems, not snippets.

If You’re a Manager / SDM

Wrong question:
“Can AI help me write emails?”

Better question:
“How can AI help me lead people better?”

Best question:
“How can AI multiply my impact across people, projects, and stakeholders?”

Concrete uses:

• Draft clear feedback (especially hard feedback)
• Prepare for tough conversations
• Translate strategy → execution plans
• Produce crisp weekly updates that build trust

Outcome:
Less chaos. More clarity. Higher trust.

If You’re a Builder or Founder

Wrong question:
“What startup ideas does AI have?”

Better question:
“How can AI help me validate ideas faster?”

Best question:
“How can AI compress learning loops so I fail or win quickly?”

Concrete uses:

• Write landing pages in minutes
• Simulate customer objections
• Generate outreach messages
• Scope MVPs aggressively small

Outcome:
You test markets, not fantasies.

The Meta-Question (This Is the Cheat Code)

No matter your role, the question always reduces to this:

“If I keep asking AI better questions than everyone else, what compounds for me in 12 months?”

• Better judgment
• Faster execution
• Stronger communication
• Sharper intuition
• More optionality

AI rewards clarity of intent, not curiosity alone.

Why This Matters Right Now

In a weak job market:

• Average effort doesn’t stand out
• Credentials decay faster
• Titles matter less than output

AI creates a brutal divide:

1. People who use it to think
2. People who use it to ask

Jensen Huang’s advice isn’t about prompts.
It’s about ownership of your trajectory.

Final Takeaway

Don’t ask AI to replace your work.

Ask AI to:

• sharpen your thinking
• compress your learning
• multiply your impact
• leave artifacts behind

The people who win won’t be the ones who used AI the most.

They’ll be the ones who asked the right question early,
and kept asking it every day.