Provided by Pamela Skillings of BigInterview
| It *truly* is tough out there. New roles attract hundreds of applicants within hours and people need to apply for dozens (or sometimes hundreds) of jobs before hearing back. I’m not surprised job seekers are trying to move faster. With AI tools that can generate resumes, cover letters, and entire applications in seconds, it’s easy to fall into a numbers-game approach. But there’s something fundamentally wrong about it. |
| I understand the impulse. In many ways, tools like ChatGPT or Claude write faster and better than the average person. They use fancy language, don’t make spelling and grammatical mistakes, and can instantly come up with professional sentences that might take you hours to write. When you’re worried about paying bills and applying for multiple roles in a day, speed feels like the only sensible strategy. Technology is here to make our lives easier, right? But let me tell you what’s happening on the other side: too many applications now look almost identical. We recently opened a role at Big Interview and, like many hiring teams, we included a short application question: “Please provide an example of how you organize and prioritize daily outreach activities.” When the responses started coming in, something stood out immediately. Roughly 90% of them sounded the same. Take a look. It’s a real screenshot of our incoming data: |
| The choice of words varied slightly, but the structure, answer length, and tone were nearly identical. It was clear they were made with AI tools with little or no personalization. It’s really easy to tell. |
- The answers are generic and the language is vague. Think “ensure consistent activity while adjusting priorities”.
- There are lots of polished words, but very little substance about the candidate
What you see vs. what the hiring teams see
| On your side of the process, using AI can feel like a genius efficiency hack. But on the hiring side, it often looks like several candidates submitting the same application with only their names swapped out. When hiring managers read applications like those, something important gets lost: the real person behind the resume. I’m not saying you shouldn’t use AI. On the contrary, I’m a big believer that technology can help job seekers work smarter. But there’s a difference between using AI as a helpful tool and letting it do all the thinking for you. I was intrigued enough to try a quick experiment. I asked an AI tool to answer the same application question, but this time I uploaded a “fake” resume and asked for a response tailored to that specific background. The answer was still a little AI-sounding, but more specific: I batch my outreach by channel and persona. For example, from 9:00 to 11:00 AM, I am in “phone mode” targeting CTOs only. This allows me to get into a specific rhythm and keep my language technical and sharp without resetting my brain after every dial. From 11:00 to 12:30, I switch to “writing mode” for follow-up emails. I live by my calendar blocks — if it’s a calling block, I don’t even have my email tab open. Notice the difference. There’s a sense of how the person actually works. You can picture their day and their process. You get a glimpse of their habits and approach. That’s the kind of detail that helps a hiring team imagine you in the role. Unfortunately, most AI-generated applications strip away precisely those details. |
| What this ultimately means for you |
| The result is a strange paradox. Candidates are applying faster than ever before, but many applications are becoming less memorable. And when everything sounds polished but generic, hiring teams naturally gravitate toward the rare application that feels real and stands out from the noise. That’s why one of the most effective strategies in today’s job market may sound surprisingly old-fashioned: Slow down and do it yourself. Instead of sending 50 identical applications, focus on fewer roles and invest a little more thought into each one. Things to pay attention to: Tailor your resume to each role — Read the job description carefully, look at requirements and treat those phrases like keywords you will then use in your application. Adjust your answers to open-ended questions (if there are ones) — Don’t accept what AI gives you without making any edits. Change answers so that it sounds more like the way you really speak. Share a short example from your actual experience — In my example above, “phone mode”, “writing mode” and exact times “9:00–11:00” are small details, but they make a big difference. When hiring managers see specific details (how you solved a problem or what you consider your biggest wins) it instantly separates you from the generic responses. That doesn’t mean you have to avoid AI entirely, but you do need to give it enough context to work with. If you simply ask for a generic answer, that’s exactly what you’ll get. But if you feed it enough information to explain your experience, provide your resume, and manually refine what it gives you, you can work with AI to make your application sharper. At Big Interview, we’ve been thinking a lot about this challenge, which is why we built AI tools specifically for job seekers. Instead of giving you generic AI output, our resume and cover letter tools are designed specifically for job applications. |
| You can upload the job description, share details about your background, and the system helps you tailor your materials to that role. The goal is to help you highlight the experience you already have and present it in a way that makes sense to hiring managers. Rooting for you always, Pamela Skillings Author, Career Coach, Co-founder of Big Interview |
The Office of Career Strategy provides resume, cover letter, and interviewing tools through Big Interview and Big Resume to students of Yale College, GSAS, and Postdocs.
