How a $500B company improved its hiring process

Google is going back to in-person interviews for software engineering roles! Reports suggest that over 50% of candidates are now suspected of using AI tools off-camera to solve real-time coding challenges during remote interviews. Some Google employees have even called on leadership to ban remote interviews altogether, arguing that they no longer reflect a candidate’s true fundamentals. This shift highlights an interesting dilemma... AI is transforming how engineers work, but it’s also disrupting how we evaluate engineers. Balancing fairness, authenticity and progress will be key for every company hiring in the AI era. https://lnkd.in/gPa7V7GB

Ever wondered how to mock interview for your next dream IT job? Here is a step-by-step guide to make your mock interview realistic, effective, and confidence-boosting: Step 1: Define the Job Target Define your role - Software Engineer, IT Support Specialist, Cloud Architect, etc. and identify key technologies (e.g., Python, AWS, SQL, React). Make sure you understand the company type: Startup vs enterprise — interview styles differ. Step 2: Choose an Interviewer or Tool Find a friend or colleague in IT (great for feedback) or a mentor or recruiter who knows the industry. Leverage AI-based mock interview platforms (e.g., Pramp, Interviewing.io, TechMock, or even ChatGPT). Step 3: Record and Reflect After your mock, watch and rewatch your video. Ask for specific feedback: clarity, technical depth, confidence, body language and note improvement areas — e.g., “Too much jargon,” or “Need stronger examples.” Make sure you are honest with yourself about the feedback and where to improve. Step 4: Repeat with Variation Rotate between different formats (coding, design, HR) and practice with new people. Gradually add pressure simulation, like timed questions or surprise topic. Good luck with your interview prep and don't, forget to search www.veriipro.com for the latest jobs in a variety of IT sectors #CareerDevelopment #MockInterview #TechJobs #ITCareers #JobInterviewTips #CareerGrowth #InterviewPreparation #TechCareer #JobSearch #ProfessionalDevelopment #ITCommunity #CareerAdvice #ResumeTips #CareerSuccess

Google is going back to in-person interviews for software engineering roles! Reports suggest that over 50% of candidates are now suspected of using AI tools off-camera to solve real-time coding challenges during remote interviews. Some Google employees have even called on leadership to ban remote interviews altogether, arguing that they no longer reflect a candidate’s true fundamentals. This shift highlights an interesting dilemma... AI is transforming how engineers work, but it’s also disrupting how we evaluate engineers. Balancing fairness, authenticity and progress will be key for every company hiring in the AI era. What do you think - should live coding interviews adapt to this new reality, or is going back to in-person the right call? P.S. Check out this video to see a mock in-person coding interview at Google: https://lnkd.in/emvweUJz

This is interesting. AI has its place in the job hiring process, but if it’s masking too much (including language proficiency), it can sometimes feel like getting catfished. In person interviews are great when possible.

> Reports suggest that over 50% of candidates are now suspected of using AI tools off-camera to solve real-time coding challenges during remote interviews. Wait... isn't this one of the companies pushing the use of AI for just this type of programming work? 🤔 I remember 20 years ago, my CTO at the time having a real panic about interviews and "what if they just google all the answers?". The aim of an interview isn't to create some artificial, sterile room to stress test a candidate (though you'd think it was...), it's about seeing how they use the tools available, the tools they'll use on the job, respond to challenge and approach problem solving. All of this can be done without worrying about the impact of AI, because AI isn't your problem, your problem is how you structure your interviews.

Going back to in-person interviews is understandable when you can't verify the process remotely. It's practical. But it's a retreat, not a solution. The real challenge isn't stopping candidates from using Ai-it's rethinking how we evaluate engineers in a world where AI is part of the workflow. If someone can effectively use AI to solve problems, isn't that the skill we actually need? We can't keep testing for yesterday's skills while hiring for tomorrow's roles. Instead of banning the tools, we should learn to assess how people think, decide, and work alongside them. Returning to the old ways buys us time. But adapting to the new reality is what we actually need to figure out-now, not later.

Just leaving this here for any future candidates who will have the luck (or misfortune) to do job interviews with me: PLEASE DO NOT USE compilers or interpreters of any kind before, during or after our interview! I promise you, with 98% certainty, that I will know, and you will be immediately disqualified upon me realizing it. Compilers and interpreters are dumbing you down and deskilling you long term, and this is something I've kept saying for months now. The evidence is out there and data in support of it is mounting. DYOR! If you want to be a capable Software Engineer, you must be able - at all times - to write machine code by hand on your chosen platform and also reason through any problem, fully on your own and without an assembler. Not to clown on Alex Ragalie too much, I'm sure it's coming from a place of legitimate concern, but this is what you sound like when you ignore new, powerful tools. When I was younger, I, too turned my nose up at people who couldn't, say, handle memory management in C++ without smart pointers - "they're an inefficient crutch," I'd say, and probably rejected candidates not because there was anything actually wrong with them, but because I needed to prove something about *myself*. For people I interview, I want you to know how to maximize these tools as well as when to take over yourself, and it's up to me to figure out how to fairly test you so that I can see both. Don't stay stuck in the past, but don't outsource your brain, either.

Hiring is a data matching problem. But for too long, we've been using the wrong data: a one-page resume. At Simera, we knew we had to go deeper. We built our AI, 'Agent Era,' to solve this. Instead of just matching keywords, Agent Era analyzes over 5,000 data points on each candidate, from skills assessments and smart interviews to work history. It's not about just finding a 'Full Stack Developer.' It's about finding the right one for your team, culture, and goals. It's how we deliver a shortlist in minutes, not weeks

With today's AI tools, I don't know how you can hire programmers if you don't have skilled engineer to interview them. A great technical recruiter with an engineering background will save you time and help you avoid mis-hires. Routinely I get candidate who have impressive resumes, communicate clearly, and provide written screen submissions that wow me. A significant percentage of them bomb the technical interview. They give superficial answers, or ones that sound believable but fail deeper scrutiny. If you're looking for truly senior developers, it's hard to tell these people from ones who have the kind of depth and breadth of knowledge that is needed for demanding roles. Most recruiters are not engineers and can not tell the good bluffers from the great engineers. At Vistulo, we can. Our clients don't waste time because they only get truly good candidates who were screened by an experience engineer. We repeatedly hear this feedback and are grateful for the companies who recognize this value and benefit from it.

🤯 The Real Gatekeeper in Tech Hiring Isn't the Code. Five years ago, I got this email from YouTube. It wasn't an offer, but the final, high-stakes step: Hiring Committee (HC) Review. It hit me: after months of grueling technical screens, system design, and behavioral interviews, the last stage was pure documentation and alignment. It was a different kind of pressure, and one developers rarely prep for. In 2024, where AI is streamlining initial screening, getting to the HC stage means your code is approved. Now, the challenge shifts from competence to package presentation. 💡 3 Non-Technical Hurdles to Clear the Final HC Review: 1. The "Why You" Narrative: HC members review your entire packet—interview notes, resume, and sometimes even social presence. You need a cohesive narrative proving you're the unique solution to their problem. Did your resume quantify your impact with $ or %? 2. The Transcript Trap: For early-career roles, they request final transcripts. This is a check on integrity and consistency. Lesson: Be transparent from day one; discrepancies are a red flag the HC will immediately flag. 3. System Design Clarity: Interviewers' notes must clearly articulate your architecture. You need to coach your interviewers (subtly!) by structuring your answers using established frameworks (like STAR for behavioral) to make their note-taking easy and HC-friendly. The best developers don't just solve the problem; they make the solution easy to sell to the ultimate decision-makers. The HC process is System Design for your career. What non-technical "final mile" challenge have you faced in a high-stakes tech interview? Share your strategy! 👇 #SystemDesign #TechHiring #DeveloperTools #AI #LearningJourney