Blog
- After AI Can Code, What Should a Technical Interview Actually Test?
AI now solves the classic algorithm problem in seconds, and interviewers know it — in one survey, 81% of Big Tech interviewers said they had suspected candidates of using AI during interviews. But the three signals the LeetCode round was always a crude proxy for — is this person smart, is their technical foundation real, do they think in structures — matter more than ever, because directing and verifying AI is built on them. A fair look at both sides of the debate, and at the interview formats Meta, Google, Canva, and Shopify are actually replacing the ritual with.
- The Best AI Interview Assistant for Mac in 2026: What to Look For (and Why Native Beats a Browser Tab)
Most 'AI interview assistant' tools are web apps or browser extensions that happen to open on a Mac. A native macOS app is a different thing for a live interview: it captures system audio through Apple's own Core Audio Tap — no browser tab, no virtual audio driver, no bot in the call — can put the answer on a separate iPhone so nothing lives on the interview machine, and grounds each answer in your own résumé. This is a plain-language buyer's guide: the criteria that actually matter in a Mac interview copilot — audio capture, where the answer shows up, where it comes from, verifiable latency, honest billing, and local-first privacy — and an honest map of how interviewco.ai meets each one, including the macOS 14.4 requirement it depends on.
- What Interview Platforms Actually Watch For: Anti-Cheat on Zoom, CoderPad, HackerRank & CodeSignal
A plain-language explainer on how interview-integrity tooling actually works — and why the answer differs so much by platform. A Zoom or Google Meet call detects almost nothing on its own; a live coding pad like CoderPad leans on a human interviewer plus keystroke-and-paste telemetry; and unmonitored assessments like HackerRank and CodeSignal replace the absent interviewer with browser lockdown, webcam proctoring, keystroke dynamics, and ML plagiarism and 'suspicion-score' provenance models. The unifying principle — process over product — and the integrity line interviewco.ai will not cross.
- Interviewing in Your Second Language Is a Different Test
A technical interview quietly tests two things at once: whether you can do the engineering, and whether you can perform it out loud, in real time, in a second language, under pressure. Those are different skills. Here is how interviewco.ai narrows the gap — accurate transcription of domain terms and accents, a summary line you can read in your own language, and answers grounded in your own résumé — without inventing experience you don't have.
- How a Real-Time Interview Copilot Actually Works on a Mac
A look under the hood of the interviewco.ai live interview copilot: how it hears the interviewer through macOS system audio with no browser tab or virtual driver, grounds each answer in a profile built from your own résumé, and puts the result where you choose — a quiet overlay on your Mac, or your iPhone as a separate second screen.
- AI Mock Interviews That Sound Like You, Not Like a Question Bank
How the interviewco.ai mock interview works: questions built from your résumé and the job you're targeting, a real interviewer's adaptive follow-ups, feedback that names what actually broke, and a practice loop that learns you round over round.
- Your Mind Going Blank in an Interview Is Not a Skill Problem
Why we built interviewco.ai: how a real-time interview copilot rebuilds confidence with mock-interview loops, profile-grounded answers, and follow-up awareness — and how the context engineering works under the hood.