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This week, I’ve been reflecting on what it feels like to interview in 2025, when both sides of the table are mediated by AI. 

A friend of mine recently told me an AI video interviewer kept cutting him off. Each time he tried to share real nuance, the algorithm demanded a shorter answer. The irony? He’s exactly the kind of person you want thinking through hard problems.

If you’ve felt that same frustration, whether as a candidate or a hiring leader, this edition is for you. Because the problem isn’t AI. It’s that we’ve forgotten how to see judgment.

The Interview Arms Race

The hiring process has turned into a technological arms race. Candidates use AI to sound smarter. Recruiters use AI to filter faster. And in between, the human signals the way someone reasons, adapts, and decides who gets buried.

The numbers back it up. Nearly nine in ten companies now utilize AI tools at some point in their hiring pipeline (World Economic Forum, March 2025). That means thousands of interviews are happening where no human ever listens to a full answer.

But there’s a deeper issue: the sameness problem.

Everyone is drawing from the same prompt libraries, using the same resume optimizers, and refining their phrasing into a similar, perfect rhythm. In a world of uniform brilliance, you stop believing any of it is real.

That’s why hiring teams are now re-learning an old truth: what stands out isn’t perfection, it’s the authenticity of a person. The moment someone speaks with lived context, trade-offs, or real texture, the conversation becomes real and not artificial (pun intended). 

How Candidates Can Stand Out Again

The candidates who are thriving right now aren’t the ones who hide their AI use; they’re the ones who integrate it transparently and then clearly explain their reasoning on top.

With the onset of AI-driven interviews, I see three fundamental shifts.

1. Trade perfection for proof

Don’t show the final version of your project. Show the thinking that got you there, the messy drafts, the failed attempts, the moment you caught an error your tool didn’t.

Tell stories with constraints, not just outcomes.

Instead of, “I built an automation that cut costs 40%,” try, “We had a three-week deadline, half the data was unreliable, and we had to choose between precision and speed. Here’s how I decided.”

That’s the kind of story no prompt can fake.

2. Turn AI into a co-pilot, not a mask

The best candidates treat AI like a creative sparring partner. They use it to simulate interview questions, analyze gaps, or pressure test answers, but they always add something AI can’t: judgment.

Say out loud how you use AI in the interview.

As an example, you could say, “I used GPT-4 to prototype three angles for this solution, but my final call came from testing real user data.” That line alone tells a hiring manager two things: you understand your tools, and you don’t outsource your brain.

3. Show the “why,” not just the “what”

Most interviews fall flat because candidates recite actions. The strongest ones reveal reasoning.

When you explain why you rejected one option or prioritized another, you build credibility that no resume can replicate.

Your real advantage is clarity of thought, not compliance with structure. 

How Hiring Teams Can See What’s Real

Hiring teams are just as frustrated. They’re drowning in optimized profiles, automated portfolios, and scripted answers that all sound “AI-safe.” But behind that fatigue is opportunity: to design interviews that measure thinking, not theatrics.

1. Listen for judgment, not jargon

When someone explains their decision process, how they balanced speed vs. accuracy, or when they overruled an AI suggestion, that’s your signal. Real thinkers narrate trade-offs. Pretenders narrate buzzwords.

2. Invite context, not perfection

The best interviewers now present candidates with complex problems that include missing data or ambiguous goals. Why? Because that’s what work actually feels like. When you see how someone navigates conflict and constraint, you see their true fluency in AI and in leadership.

One executive hosts live “co-thinking sessions” where candidates can utilize any AI tool they prefer. The goal isn’t the final answer; it’s the conversation around the problem. The moment the candidate starts asking better questions, the interview becomes real again.

3. Reward transparency over theater

A small but powerful shift: praise candidates who are open about their process, even if it includes AI. Those who can clearly say, “Here’s where I used it, and here’s where I didn’t,” are demonstrating that they understand control.

That’s the muscle we’ll need most in this next decade, not prompt fluency, but discernment.

My Disruptive Take

A significant misunderstanding about AI hiring is that it’s a battle between humans and AI. It isn’t. It’s a test of who can think clearly and be authentic when information and knowledge are accessible to everyone.

For candidates: don’t chase the illusion of perfection. Build portfolios, stories, and examples that show how you reason under constraint, how you made mistakes, and how you weren't perfect. Learn to actually tell your story, show your personality, not the one AI came up with for you. 

For companies: stop designing interviews that only reward polish. Build conversations that reveal judgment, flexibility, and curiosity.

Because in a world where every answer can be generated, clarity and courage are the new credentials.

If you'd like my printable interview prep sheet and AI era question toolkit, please reply to this email, and I’ll send them your way.

Sources

1. World Economic Forum, “Hiring with AI Doesn’t Have to Be Inhumane,” March 2025

2. SHRM, “2025 Talent Trends: AI in HR,” February 2025

3. Xu et al., “AI Self-Preferencing in Algorithmic Hiring,” arXiv, September 2025

4. Mujtaba & Mahapatra, “Bias in AI Video Interview Assessments,” arXiv, May 2025

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