Stories with Tag Interviewing

• Ask HN: What is interviewing like now with everyone using AI?

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  Posted: 2025-02-02 15:19:32

  Verbose tl;dr

  The original poster asks how the prevalence of AI tools like ChatGPT is affecting technical interviews. They're curious if interviewers are changing their tactics to detect AI-generated answers, focusing more on system design or behavioral questions, or if the interview landscape remains largely unchanged. They're particularly interested in how companies are assessing problem-solving abilities now that candidates have easy access to AI assistance for coding challenges.

  The Hacker News post titled "Ask HN: What is interviewing like now with everyone using AI?" poses a question to the community regarding the evolving landscape of technical interviews in the era of readily available artificial intelligence tools. The original poster (OP) expresses curiosity about how the proliferation of AI coding assistants, such as GitHub Copilot and ChatGPT, is impacting the interview process for software engineering and related roles. They are specifically interested in understanding how companies are adapting their evaluation methods to account for the widespread availability of these tools. The OP wonders whether interviewers are explicitly prohibiting the use of AI during coding challenges, or if they are incorporating the reality of AI assistance into their assessment criteria, perhaps by focusing more on higher-level design skills and problem-solving abilities rather than pure coding proficiency. Essentially, the post seeks to gather anecdotal evidence and insights from other members of the Hacker News community who have recently participated in technical interviews, either as interviewers or interviewees, to gain a clearer understanding of the current state of technical interviewing in light of the ubiquitous presence of AI coding tools. The underlying concern seems to be whether the traditional methods of evaluating technical skills are still effective and relevant in this new environment, or whether they need to be re-evaluated and potentially redesigned to ensure they accurately measure the capabilities required for success in modern software development roles.

  • Interviewing
  • AI
  • artificial intelligence
  • Job Search
  • Hiring
  • Technology
  • software engineering
  • developer
  • Ask HN
  • Hacker News
  • Remote Work
  • job market

  Summary of Comments ( 97 )
  https://news.ycombinator.com/item?id=42909166

  Verbose tl;dr

  HN users discuss how AI is impacting the interview process. Several note that while candidates may use AI for initial preparation and even during technical interviews (for code generation or debugging), interviewers are adapting. Some are moving towards more project-based assessments or system design questions that are harder for AI to currently handle. Others are focusing on practical application and understanding, asking candidates to explain the reasoning behind AI-generated code or challenging them with unexpected twists. There's a consensus that simply regurgitating AI-generated answers won't suffice, and the ability to critically evaluate and adapt remains crucial. A few commenters also mentioned using AI tools themselves to create interview questions or evaluate candidate code, creating a sort of arms race. Overall, the feeling is that interviewing is evolving, but core skills like problem-solving and critical thinking are still paramount.

  The Hacker News post "Ask HN: What is interviewing like now with everyone using AI?" has generated a number of comments discussing the impact of AI on the interviewing process, both for candidates and interviewers.

  Several commenters note the increased use of automated screening tools, powered by AI, often in the form of coding challenges or take-home assignments. These are perceived as a double-edged sword. On one hand, they offer a potentially more objective initial screening process, potentially reducing bias and allowing candidates to demonstrate their skills practically. On the other hand, some express concern that these automated systems may not accurately assess a candidate's true abilities and may filter out otherwise qualified individuals due to rigid criteria or an inability to adapt to individual circumstances. One commenter specifically highlights the possibility of these tools inadvertently penalizing neurodivergent candidates.

  The discussion also touches upon the use of AI by candidates during interviews. Some acknowledge the use of AI for assistance with coding challenges, acknowledging that it's becoming increasingly difficult to distinguish between genuine skill and AI assistance. Others raise ethical concerns about this practice and the potential for candidates to misrepresent their abilities. This leads to a broader discussion about the changing nature of technical skills and the increasing importance of problem-solving and critical thinking abilities, which are harder for AI to replicate.

  One compelling comment thread explores the shift in the types of questions being asked in interviews. With the availability of AI tools that can readily generate code, interviewers are seen as moving towards more conceptual questions, focusing on understanding the candidate's problem-solving approach and their ability to reason about complex systems. This shift is viewed by some as a positive development, as it emphasizes deeper understanding over rote memorization.

  Several commenters also mention the use of AI for interview preparation. Candidates are leveraging AI tools to practice their responses to common interview questions and refine their coding skills. This highlights the evolving landscape of interview preparation and the need for both candidates and interviewers to adapt to the changing dynamics of the hiring process in the age of AI.

  The use of AI for scheduling and communication is also briefly mentioned, but the main focus of the comments remains on the impact of AI on the core aspects of the interview process, particularly coding assessments and the evaluation of problem-solving abilities. Overall, the comments paint a picture of a rapidly evolving interview landscape, with AI playing an increasingly significant role, bringing both opportunities and challenges for all involved.

• The FizzBuzz that did not get me the job

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  Posted: 2025-01-21 20:15:05

  Verbose tl;dr

  The author recounts failing a FizzBuzz coding challenge during a job interview, despite having significant programming experience. They were asked to write the solution on a whiteboard without an IDE, a task they found surprisingly difficult due to the pressure and lack of syntax highlighting/autocompletion. They stumbled on syntax and struggled to articulate their thought process while writing, ultimately producing incorrect and messy code. The experience highlighted the disconnect between real-world coding practices and the artificial environment of whiteboard interviews, leaving the author questioning their value. Though disappointed, they reflected on the lessons learned and the importance of practicing coding fundamentals even with extensive experience.

  This blog post recounts the author's experience with a seemingly straightforward FizzBuzz coding challenge that unexpectedly derailed their job application. The author, initially confident due to their familiarity with the classic FizzBuzz problem, embarked on the task with an intention to showcase their coding proficiency. However, the online coding platform presented by the prospective employer introduced a series of unanticipated constraints and complexities that transformed the simple exercise into a frustrating ordeal.

  The author meticulously details their approach, starting with what they perceived as a clean and efficient Python solution. This initial attempt, designed to adhere to standard FizzBuzz logic, involved iterating through numbers and printing "Fizz" for multiples of 3, "Buzz" for multiples of 5, and "FizzBuzz" for multiples of both. However, the online platform rejected this solution, citing an issue with the output format.

  The author then embarked on a protracted debugging process, painstakingly attempting to decipher the platform's cryptic error messages and adjust their code accordingly. They experimented with various modifications, including meticulously ensuring their output precisely matched the expected format, accounting for potential whitespace discrepancies, and even exploring alternative approaches to structuring their code. Despite these efforts, the platform continued to reject their submissions, leading to mounting frustration and a sense of bewilderment.

  The author describes a growing sense of unease as they grappled with the platform's opaque feedback and the seemingly arbitrary nature of the errors. This struggle, initially perceived as a minor hurdle, gradually eroded their confidence and cast a shadow over their perception of the company's technical evaluation process. The experience ultimately culminated in the author failing the coding challenge, effectively ending their candidacy for the position.

  The post concludes with a reflection on the incident, expressing the author's disappointment not only in the outcome but also in the perceived disconnect between the seemingly trivial nature of the challenge and the significant consequences it had on their application. The author questions the effectiveness of using such rigid, automated coding platforms for evaluating candidates, suggesting that they may not accurately reflect real-world coding skills and can inadvertently create unnecessary barriers for otherwise qualified individuals. The author ultimately frames the experience as a learning opportunity, highlighting the importance of being prepared for unexpected challenges during the job application process.

  • FizzBuzz
  • Interviewing
  • Coding Challenges
  • Job Search
  • Software Development
  • programming
  • Technical Interviews
  • algorithms
  • failure
  • Learning Experience

  Summary of Comments ( 256 )
  https://news.ycombinator.com/item?id=42784699

  Verbose tl;dr

  HN commenters largely sided with the author of the blog post, finding the interviewer's dismissal based on a slightly different FizzBuzz implementation unreasonable and indicative of a poor hiring process. Several pointed out that the requested solution, printing "FizzBuzz" only when divisible by both 3 and 5 instead of by either 3 or 5, is not the typical understanding of FizzBuzz and creates unnecessary complexity. Some questioned the interviewer's coding abilities and suggested the company dodged a bullet by not hiring the author. A few commenters, however, defended the interviewer, arguing that following instructions precisely is critical and that the author's code technically failed to meet the stated requirements. The ambiguity of the prompt and the interviewer's apparent unwillingness to clarify were also criticized as red flags.

  The Hacker News post titled "The FizzBuzz that did not get me the job" generated a significant discussion with a variety of viewpoints on the interview process, the FizzBuzz challenge itself, and the author's specific situation.

  Several commenters expressed sympathy for the author and criticized the interviewer's handling of the situation. They felt the interviewer was unnecessarily harsh and dismissive, failing to provide constructive feedback and instead resorting to belittling the candidate. Some argued that such behavior reflects poorly on the company's interview process and culture. One commenter shared a similar experience of being abruptly dismissed during a coding challenge, highlighting the negative impact these experiences can have on candidates.

  Others defended the use of FizzBuzz as a screening tool, asserting its value in assessing basic programming proficiency and problem-solving skills. They argued that struggling with FizzBuzz might indicate a lack of fundamental knowledge that would be crucial for the role. Some suggested that the issue wasn't the author's inability to solve the problem immediately, but rather their reaction to the pressure and their failure to communicate their thought process effectively.

  A recurring theme in the comments was the importance of communication during technical interviews. Several users emphasized that even if a candidate struggles with a particular problem, clearly articulating their thought process, asking clarifying questions, and demonstrating a willingness to learn can make a positive impression. They suggested that the author's lack of communication might have contributed to the negative outcome.

  Some commenters debated the relevance of FizzBuzz in modern software development, with some arguing that it's an outdated and simplistic test that doesn't reflect the complexities of real-world programming. Others countered that while it may not be a comprehensive assessment, it can still be a useful filter for identifying candidates who lack basic programming skills.

  A few commenters also discussed the potential role of nerves and anxiety in the author's performance. They acknowledged that interview pressure can significantly impact a candidate's ability to think clearly and perform at their best. Some suggested that the interviewer should have been more understanding and provided a more supportive environment.

  Finally, some commenters questioned the author's interpretation of the events, suggesting that there might be more to the story than presented in the article. They cautioned against drawing definitive conclusions based on one side of the story.

  Overall, the comments reflect a diverse range of opinions on the use of FizzBuzz, the importance of communication in interviews, and the appropriate way to handle candidates who struggle with technical challenges. The discussion highlights the challenges and complexities of the technical interview process for both candidates and interviewers.