CoderPad

The short answer: Many technical hiring processes are doing the latter. High-friction interview loops, live coding under observation, and AI-restrictive assessments are measuring interview performance, not job performance. The fix isn’t rebuilding from scratch — it’s auditing whether your process measures engineering capability or something else entirely.

Campus recruiting season arrives the same way every year: hundreds of applications, a narrow window, and a process that was never designed for this much volume or this much pressure. Meanwhile, the definition of “technical skill” is actively shifting—AI-polished resumes have made traditional screening nearly meaningless, and the skills that predict junior developer success look different than they did two years ago. Most teams get through it. Fewer teams get it right.

AI has fundamentally changed how engineers work. It’s not a tool candidates might use anymore. It’s embedded in how code gets written, reviewed, and shipped every day. In many teams, the majority of code is already AI-assisted—and growing. Which leads to a clear conclusion for hiring teams: Interviews without AI interviews are becoming obsolete. Trying to remove AI from the interview process doesn’t restore signal—it distorts it.

Not skills. Not judgment. Not potential. It’s screening for the ability to interview well. And those two things have almost nothing to do with each other. We sat down with recruiting experts Cammas Freeman, Phil Strazzulla, and Kaylee Estes to talk through three of the biggest blind spots in technical hiring right now. What they said is worth slowing down for. By the time a candidate walks into your first screening call, they’ve already formed an opinion about your company.

When we opened our latest software engineer role, we had 100 applications within 24 hours. By the end of the first week, without running a single ad, we had 160 candidates in the pipeline. That’s a lot of signal to sort through. And it forced us to be honest about something every engineering leader eventually confronts: a hiring process is only as good as its ability to protect your team’s time while treating candidates fairly. We’re CoderPad. We build technical hiring software.

AI didn’t just change how engineers build software. It changed what it means to hire one. The tools engineers use every day — AI coding assistants, prompt-driven debugging, multi-model workflows — are now fundamental to how modern development teams operate. According to our State of Tech Hiring 2026 Report, 82% of developers find generative AI useful, and 54% would experience a measurable productivity drop if AI tools were removed tomorrow. AI isn’t a productivity booster anymore.

Back to blog We spoke with Farhan Thawar, VP and Head of Engineering at Shopify, about why the company 10x’d its internship program, what AI-native hiring really looks like, and the three-part framework reshaping how technical talent gets evaluated.

AI interviewers are having a moment. Every vendor is selling the same dream: automated conversations, instant scoring, no more phone screens. Faster. Cheaper. Scalable. And if you’re a TA leader staring down a pipeline of 2,400 applicants for 12 open engineering roles, that pitch lands. Here’s the problem nobody’s saying out loud: AI interviewers aren’t showing you skills, and now candidates are using AI to answer your AI interviewer so you’re not evaluating engineers anymore.

Your latest candidate looks like a slam dunk. Their resume matches the job description perfectly. Their LinkedIn is polished, complete, and compelling. Every skill checks out. And yet, more often than teams want to admit, that “perfect” candidate doesn’t hold up in a real conversation. What’s happening in hiring today isn’t just resume inflation. It’s a more advanced, harder to detect form of misrepresentation driven by AI, proxies, and increasingly polished candidate narratives.

According to CoderPad’s State of Tech Hiring 2026 report, 82% of developers now find GenAI useful — up from 76% just a year ago. More telling: 54% of developers would experience a measurable productivity drop if AI tools were removed tomorrow. AI isn’t a productivity booster anymore. It’s infrastructure. With this shift, it’s no surprise that most companies have mandates to explore how to introduce testing for AI proficiency into their hiring process.