12,000 applied, 450 interviewed, 0 hired: India’s tech hiring crisis, where AI can’t help

In a Reddit post that has gone viral, an unnamed tech company in India recently revealed a startling recruitment experience: despite receiving over 12,000 applications for junior developer and QA roles, it was unable to hire even a single candidate after conducting 450 interviews.

The company, which shared its ordeal on the r/developersIndia subreddit, disclosed that it had posted job listings on LinkedIn for junior frontend/backend developers and QA roles, offering a lucrative package of up to ₹20 lakh per annum. Yet, after multiple rounds of resume screening and interviews, it ended the process without extending a single offer.

A Growing Concern: AI Without Understanding

In the now widely shared post, the firm stated, “We even allowed candidates to use GPT to solve problems. However, when we ask about time or space complexity, or an explanation of the code they just wrote, many are unable to respond.” The issue, they concluded, wasn’t candidates using AI tools like ChatGPT, but their lack of understanding about what they were submitting.

The term “vibe coding”—used to describe those who appear competent by copying code without understanding its logic—has quickly become shorthand for a growing crisis in the tech hiring landscape.

“This makes it extremely difficult these days to find a developer who truly understands what they've written,” the company lamented.

According to the company, it rejected over 10,000 applications outright due to poor skill alignment or incomplete resumes. The remaining 2,000 applicants were shortlisted, but only 450 were interviewed, and none were deemed fit for hire.

The firm admitted it was beginning to question whether its hiring bar was too high, or if this reflected a deeper crisis in developer readiness.

The post read, “We’re starting to question whether we’re making mistakes in our hiring process, or if it’s just high time for junior devs to realise the importance of actually understanding the code before pasting it from GPT.”

The Internet Reacts: Mixed Opinions

The post quickly drew comments from all corners of the tech community. Some users were critical of the interview process itself, suggesting that the hiring panel may be at fault.

“You seriously need to evaluate your interview process. Either your recruiting team is bringing you bad developers or your process is having issues,” one user commented.

Another added, “There are serious expectations mismatch. Don’t blame the candidates alone.”

Yet others agreed with the employer’s core concern: that many junior candidates lack basic coding fundamentals. One Redditor noted, “Candidates nowadays are missing on core fundamentals. Your HR team can try to implement a resume shortlister and a tech assignment round before F2F.”

A different user pointed out, “People are not ready to accept that candidates are not good and just relying on AI without understanding basic things. Everybody is blaming either hiring process or budget issues.”

The incident has reignited an industry-wide conversation around hiring in the age of AI. While AI tools like ChatGPT have become widespread aids for developers, their misuse in interviews is clearly alarming hiring managers.

The firm, however, clarified its stance on the use of AI: “The entire point is people are going to use AI anyway in their jobs, so there’s no point telling them not to use it in interviews. The candidate should understand the solution and the logic behind each and every line, that is our only concern.”

As AI increasingly integrates into workflows, job seekers must focus on fundamentals. Strong grasp of core concepts like data structures, algorithms, and system design remains essential—not just to get hired, but to build lasting careers in tech.

Recruiters, on the other hand, are being urged to rethink their approach. Suggestions include more practical, project-based assessments, evaluating learning agility, and implementing structured upskilling pathways for early-career talent.

In an era where tools can write code but can’t explain it, understanding—not output—has become the real differentiator.