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Yudi here.

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Most students preparing for their first job think the interview is about telling their story well.

That used to work. But the job market has quietly shifted.

Over the past few months, I’ve been studying how candidates actually landed roles in the current market, especially in AI-focused companies.

Different backgrounds. Different companies. Different job searches.

But the patterns were surprisingly consistent.

And if you’re preparing for your first role, these insights matter more than anything generic like:

“Network more.”
“Apply more.”
“The market is tough.”

That advice doesn't help you make better decisions.

What actually helps is understanding how hiring decisions are really being made now.

Let’s break down what’s changing.

1. Interviews Are No Longer About Your Past

One of the biggest shifts is this:

Interviews are moving from storytelling → live thinking.

Earlier, interviews focused on questions like:

“Tell me about a time you solved a difficult problem.”
“Tell me about a project you're proud of.”

Now the questions look more like this:

“Here’s a problem our team is facing. How would you approach it?”

And they keep pushing deeper.

What would you build first?
How would you test it?
What assumptions are you making?
What experiment would you run?

In other words, companies want to see how you think in real time.

This is actually good news for students.

Because it means:

You don’t need 10 years of experience.

You need clear thinking and strong problem solving.

When I run mock interview sessions with students, this is one of the first things I notice.

Many candidates prepare answers.

Very few prepare thinking frameworks.

The ones who get offers are almost always the second group.

2. You Don’t Need an “AI Background”

A lot of students believe this myth:

“I can’t apply to AI companies because I haven't worked on AI.”

That’s rarely the real barrier.

Most companies already have people who understand the models.

What they need are people who understand:

• Users
• Product thinking
• Experiments
• Execution

In many cases, complementary skills matter more than domain expertise.

For example, someone who understands:

• growth
• user behavior
• product adoption
• experimentation

can be extremely valuable in an AI company.

Why?

Because building a powerful model is only step one.

Turning it into a product people actually use is a completely different challenge.

So instead of trying to pretend you’re an AI expert, the smarter move is:

Bring the skill they don’t already have enough of.

3. Effort Alone Won’t Differentiate You

Almost everyone builds prototypes now.

Thanks to AI tools, you can spin one up in 30 minutes.

Which means prototypes alone are no longer impressive.

What actually stands out is depth.

When hiring managers evaluate candidates, they often look for signals like:

Did this person understand our product deeply?
Did they research the market?
Did they think about distribution?
Did they think about commercialization?

In other words, did they show up as a candidate…

Or as someone who has already started the job mentally?

The difference is obvious in interviews.

And honestly, this is where I see many students underestimating what’s possible.

The tools available today allow you to learn something incredibly fast.

But only if you decide to go deeper than everyone else.

4. Most Students Start Their Job Search Backwards

Another pattern I see often.

Students start searching with a vague idea like:

“I want a product role.”
“I want a data role.”
“I want to work in AI.”

That’s too broad.

The better question is:

What should be different in your next role compared to today?

For some people, that answer might be:

• More ownership
• Working on AI-first products
• More technical exposure
• A faster learning environment

Once you define that non-negotiable difference, your job search becomes much easier.

Because you stop applying everywhere.

You start targeting the right environments.

And that clarity alone can save months of wasted effort.

5. The Candidates Who Win Show High Agency

If there’s one trait that consistently separates strong candidates, it’s this:

High agency.

They don’t wait for perfect instructions.

They figure things out.

They research deeply.
They build things quickly.
They experiment with ideas.

They treat the job search like a project, not a passive process.

This is also why some students progress extremely fast once they understand how the hiring game works.

Because they started operating differently.

My Perspective After Watching Hundreds of Job Searches

The biggest mistake first-time job seekers make is assuming:

“If I just apply enough, something will eventually work.”

But job searches rarely reward randomness.

They reward intentional preparation.

Over time, I started noticing something interesting.

The students who move fastest usually do three things early:

They practice thinking through real problems, not just memorizing answers.

They build evidence of how they work, not just talk about what they did.

And they approach the search like a system they are actively improving, not a waiting game.

That shift alone changes everything.

Not because the market becomes easier.

But because you start playing the game differently than most candidates.

If you're currently preparing for your first role, spend less time polishing stories.

Spend more time asking yourself:

“Can I demonstrate how I think?”

Because that’s the signal companies are really looking for now.

— Yudi J