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Welcome to today's SCALIS CareerHack newsletter! 🚀

Here's something most candidates don't know: before a human ever reads your résumé or shakes your hand, an AI system has already scored you. It's reviewed your LinkedIn activity, analyzed the language in your cover letter, and in many cases, watched a recorded video interview where it tracked your word choice, speaking pace, and facial expressions.

This isn't dystopian fiction. It's Tuesday.

The companies using these tools aren't the outliers anymore. They're the majority. And the jobseekers who are landing offers in 2026 aren't the ones fighting against this system. They're the ones who learned how it works.

Today, we're going to teach you how it works.

What the AI is actually evaluating

Let's start with the video interview, because it's where candidates lose the most points without realizing it.

When you record a one-way video interview, the kind where you answer questions alone into your camera with no human on the other end, the AI scoring it is not looking at your résumé. It's listening to your speech. It's analyzing sentence structure for confidence indicators. It's measuring how often you use filler words. It's noting whether your answers have a discernible beginning, middle, and end.

The single most punishing thing you can do in a video interview is ramble. These systems are trained on hundreds of thousands of interview recordings, and they have learned to associate concise, structured answers with high-performing candidates. Long, winding responses that loop back on themselves correlate, in the training data, with candidates who didn't get offers. So the AI scores them down.

The fix is almost embarrassingly simple: use the STAR method, every single time, without exception. Situation. Task. Action. Result. Keep each answer between 90 seconds and two minutes. End with a concrete outcome. The AI will love you for it, and so will the human who reviews the flagged top candidates afterward.

The résumé layer most people skip

ATS platforms, the applicant tracking systems that parse your résumé before any human sees it, have gotten dramatically smarter in the past two years. The old advice was "stuff your résumé with keywords." That advice will now get you filtered out.

Modern systems are doing semantic matching, not keyword matching. They understand that "led cross-functional teams" and "managed interdepartmental collaboration" mean roughly the same thing. What they're looking for now is specificity paired with relevance.

Here's the practical test: take the job description and paste it into a document. Underline every verb and every measurable outcome mentioned. Now look at your résumé. Does it contain similar verbs applied to similar scales of work? If the job description says "launched" and "scaled" and "drove," your résumé should reflect that kind of action-oriented language. Not because you're gaming a system, but because if that language genuinely describes your experience, the system will recognize it and so will the hiring manager.

Numbers are your best friend here. "Improved efficiency" means nothing. "Reduced onboarding time from six weeks to three" means everything. Quantify wherever you honestly can.

A word about AI-generated application materials

You already know this is happening everywhere. And you may be tempted to do it too. Paste a job description into ChatGPT, get a cover letter back in thirty seconds, send it off. Easy.

Here's the problem: recruiters read hundreds of applications. They have developed an almost preternatural ability to spot AI-generated prose. It has a specific cadence. It over-explains. It uses phrases like "I am deeply passionate about" and "leveraging my extensive experience." It is enthusiastic in a way that feels hollow, because it is.

More importantly, many companies are now running application materials through AI detection tools before they ever reach a human. If your cover letter gets flagged, it goes to the bottom of the pile, or out of the pile entirely.

Use AI as a thinking partner, not a ghostwriter. Have it help you brainstorm what to include, identify gaps in your narrative, or pressure-test your reasoning. Then write the actual words yourself. Your voice, your specificity, your story. That's what gets you the interview.

The human layer still matters more than you think

Here's the counterintuitive truth underneath all of this: the companies investing most heavily in AI screening tools are doing it so their human recruiters can spend more time on the candidates who make it through. Which means if you clear the AI layer, you're about to have a more substantive human conversation than you would have had five years ago.

That conversation is going to be less about your résumé and more about how you think. Recruiters using AI-assisted screening have already verified the basics. What they want to know in the human interview is whether you're intellectually curious, whether you handle ambiguity well, and whether you'll be honest with them when something isn't going right.

Prepare for that conversation. Research the company not just on their website but in the press, on Glassdoor, in their earnings calls if they're public. Find the genuine overlap between what they're trying to accomplish and what you actually care about. Walk in knowing what questions you want to ask them.

The candidates who are winning in this market aren't the ones who gamed the AI. They're the ones who used the AI layer as a filter that cleared the field, and then showed up as a real, specific, prepared human being on the other side of it.

That's the whole strategy. And you're already ahead of most people just by understanding how the game is structured.

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In this episode of Career Hack, Brandon Amoroso speaks with Alexa Mikhail, a senior health and wellness reporter at Fortune Well. They discuss the challenges of entering the workforce, the importance of networking and references, and how to ask the right questions during interviews. Alexa shares her personal journey from being laid off at CNN to finding her passion at Fortune, emphasizing the need for flexibility and intentionality in job applications. The conversation also touches on career growth, the significance of learning from experiences, and the importance of enjoying the journey.

Here’s What You’ll Learn:

• Navigating early career challenges can be overwhelming.

• Finding the right fit in job applications is crucial.

• Networking and references play a significant role in job searches.

• Asking the right questions in interviews can set you apart.

• Career growth requires self-reflection and proactive communication.

• Your 20s are a time for exploration and learning.

• It's okay to pivot and change career paths.

• Building relationships can provide valuable support in your career.

• Understanding company culture is essential for job satisfaction.

• Enjoying the process is just as important as achieving goals.

Follow SCALIS on social to stay updated with early career opportunities and exciting new trends!