Practical guides on coding interviews, AI system design, and how to communicate your thinking under pressure.
Three unrelated stories landed the same week, all pointing at the same shift: AI made writing code cheap and reviewing it the bottleneck. That bottleneck is exactly what your next interview is built to probe.
Everyone trained for the AI-assisted interview. Almost nobody is ready for the round where they pull the AI back out — and that is the round that now tells the company what is actually yours.
For a decade you prepped to write code from a blank editor. The 2026 interview drops you into someone else's 400-line file and asks what is wrong with it — and most candidates have never practiced reading code under pressure at all.
The scary part of the METR study was not that engineers were slower with AI. It was that they could not tell. That blind spot has a name in the hiring world — and the interview is designed to find it.
For years the coding interview tested whether you could write the algorithm from memory. In 2026, Google and Meta hand you an AI that already can. The thing they're grading is whether you can drive it — and that's a completely different skill.
Forty-one percent of all code written in 2025 was AI-generated. By late 2026, high-adoption engineering orgs will cross 50%. Technical interviews have already adapted. The question is no longer whether you can write the code. It is whether you own it.
Anyone can prompt a pipeline into existence. The data engineering interview is testing whether you understand what you built — grain, idempotency, schema evolution, failure semantics. Here is the rubric.
Meta is cutting 8,000 on May 20. PayPal is restructuring 4,760 roles around AI. Junior postings are down ~40% from pre-2022. The interview questions did not change. The expected answer did.
TLDR's headline this week: 'Software engineering may no longer be a lifetime career.' Before you panic, understand what's actually happening—and what separates the engineers who will thrive from those who won't.
The tech industry is shifting. Companies like Meta and Canva are now allowing candidates to use AI during interviews. Introducing the AI-Enabled coding interview type on Rubduck, plus voice improvements and new pricing.
Ever wonder what the interviewer is typing while you're trying to invert a binary tree? They aren't just writing 'pass' or 'fail'. They are scoring you against a highly standardized rubric. Here's exactly how it works.
We all know we're supposed to 'think out loud' during coding interviews. But what does that actually sound like? Here is a practical framework for explaining your code naturally and effectively.
You wrote the optimal solution, but you still got rejected. Why? Because technical interviews test more than just your code. Here are the top red flags interviewers look for, and how to make sure you don't wave them.
Your first technical interview feels like walking into a final exam for a class you never took. The format is unfamiliar, the expectations are unclear, and everyone else seems to know things you don't. Here's the honest guide nobody gave you.
Most interview advice assumes you have a study buddy, a coach, or a friend at Google willing to run mock interviews. Most candidates have none of those things. Here's how to build an effective practice routine on your own.
System design interviews aren't about memorizing architectures. They're about showing you can reason through ambiguity, make tradeoffs under constraints, and communicate decisions clearly — all in 45 minutes. Here's how to actually prepare.
For years, the gold standard of interview prep was finding a friend—or a stranger on the internet—to do a mock interview with. Today, AI interviewers are nearly indistinguishable from human ones. Which should you use?
You can solve difficult problems perfectly in your living room, but the moment a hiring manager says 'Let's begin,' your mind goes blank. This isn't a coding problem; it's a physiological one.
The technical screen proves you can code. The behavioral interview proves you are someone the team actually wants to work with. Here are the top questions asked by tech companies and how to structure your answers.
Interviewers at AI-first companies aren't asking you to design Twitter anymore. They want to know if you can reason about LLM inference costs, RAG retrieval quality, evaluation pipelines, and the unique failure modes that come with non-deterministic systems.
Most candidates spend 90% of their prep time grinding LeetCode and 0% practicing the thing that interviewers care about most: how you think out loud under pressure. Here's what a complete preparation strategy actually looks like.
You can solve the problem correctly and still fail the interview. The candidate who narrates their thinking clearly — who takes the interviewer along for the ride — almost always wins, even against someone with a more optimal solution.
Reading is step one. Rubduck's spoken interview simulator lets you practice the real thing — with an AI interviewer that listens to how you explain, not just what you code.
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