Six things that changed in tech interviews in 2026

2026 is the first year where AI is on both sides of the table. You're prepping with it. They're screening with it. Hiring is slower than it was in 2024, companies have changed how they run interviews, and your CV has to pass an automated screen before any human sees it. Most “2026 tech hiring trends” articles stop here.

I'm more interested in what changed inside the room. The six shifts below come from primary sources — Canva and Meta's published policies, the 2026 CoderPad and Karat surveys, Levels.fyi compensation data, and SmartRecruiters benchmarks.

1. The AI question is now in your coding round, not your behavioural round

A year ago, the standard advice was to prepare a behavioural answer about how you use AI. That was wrong. The companies that updated their AI policy didn't add a behavioural question. They changed the coding round.

Since June 2025, Canva officially expects candidates for Backend, Frontend and ML roles to use Copilot, Cursor, or Claude during their technical interviews (source). Their head of platforms, Simon Newton, said it directly: “we want to see the interactions with the AI as much as the output of the tool.” To make that something they could grade, Canva rewrote their question pool. Out went “implement Conway's Game of Life.” In came “build a control system for managing aircraft takeoffs and landings at a busy airport.” The new question is ambiguous enough that you can't just prompt your way to an answer.

Meta launched a similar pilot in October 2025. They now replace one of the two onsite coding rounds for SWE and EM candidates with a CoderPad three-panel layout: file explorer, code editor, AI chat. Candidates pick from GPT-5, Claude Sonnet 4.5, Gemini 2.5 Pro, or Llama 4 Maverick (source). Meta's recruiting team said it's “more representative of the developer environment that our future employees will work in, and also makes LLM-based cheating less effective.”

What to prep: a behavioural answer about how you use AI still helps — it'll come up in hiring-manager rounds. But in 2026 the higher-leverage prep is live coding with the assistant turned on: prompting, reviewing, rejecting bad output, and explaining your reasoning out loud. That's what these companies are now grading. Most other major-tech companies haven't adopted this yet, so check with your recruiter before you assume it's allowed.

2. “Catches and fixes AI mistakes” is now the #1 thing interviewers grade

CoderPad's State of Tech Hiring 2026 survey asked interviewers what they're actually grading in coding rounds. The top two answers will surprise candidates who spent the last year focused on speed (source):

1. Catches and fixes AI mistakes — 66% of hiring teams rank this as a top signal.
2. Explains trade-offs and correctness — 56%.

In plain English: they want to see you reject bad LLM output more than they want to see you ship its good output. Pause mid-stream. Say “this is wrong because it's assuming the input is sorted — let me fix it.” Correct it with a clear reason. That candidate beats the one who accepts the assistant's first draft and pastes it in.

This is the prep work most people underrate. Rehearsing your STAR stories is still useful, but the most useful drill in 2026 is this: sit with a real AI assistant, give it a medium-hard problem, and practise the pattern. Review. Catch the bug. Say the bug out loud. Decide whether to fix the prompt or fix the code. Karat's 2026 trends report says the same thing — interviewers are grading judgment under AI, not raw output (source).

3. If AI is banned, assume they're watching

Most major tech companies still don't allow AI in their technical rounds. They've also gotten better at catching candidates who use it anyway. Karat's 2026 survey of 400 engineering leaders across the US, India and China found that tech leaders estimate over half of candidates use AI even when explicitly told not to (source). A separate Karat datapoint puts LLM use during code tests at roughly 80% even when it's banned.

Companies responded the obvious way: they invested in detection tools, and they moved more interviews to formats where you can't hide a side tab — in-person rounds, live screen-share, paired observation with a second interviewer. Detection isn't perfect, but it's better than candidates assume.

What to do: ask the recruiter directly. “Are AI assistants allowed during the technical rounds?” is a fair question and they'll tell you straight. Then commit to one side. If AI is allowed, prep with it on (section 1). If it isn't, prep with it off — and don't reach for it on the day. The risk isn't worth it.

4. Companies are getting rid of take-home tests — in three different ways

Karat's 2026 report says it plainly: “hiring signal from take-home projects and automated code tests degrades fastest under AI.” That has been true for eighteen months. What's new is how companies are responding — and it's not the clean “FAANG bans them, startups keep them” split that gets reported. There are three patterns:

1. Rewritten to use AI openly. Canva replaced their take-home questions with the ambiguous, scenario-based ones described in section 1. The take-home still exists, but it's now done in a live round with the assistant turned on (Canva, June 2025).
2. Replaced with live observed coding. Meta's CoderPad pilot replaces one of the two onsite coding rounds. What used to be a take-home is now live work they can watch (Meta via CoderPad, October 2025).
3. Dropped entirely. Smaller companies and many mid-size SaaS shops have quietly removed the take-home and replaced it with a 30-minute live coding session on a simpler problem.

There is no FAANG-wide ban on take-homes. That's not actually true. Google, Amazon, Apple, and Netflix have made no public changes to their take-home policy as of mid-2026. The right move is the same as in section 3: ask the recruiter what the format is. The answer varies more now than it ever did.

5. The pay gap between junior and staff got bigger

Compensation in 2026 has split. Levels.fyi's Q3 2025 analysis of AI engineer offers shows the AI pay premium at staff level grew from 15.8% to 18.7% year-over-year, while the AI premium at entry-level shrunk from 10.7% to 6.2% (source). The Pragmatic Engineer reported a Google AI-infrastructure staff engineer getting a competing Meta offer above $1M total comp, with similar packages for HPC, ML systems and responsible-AI specialists (source). PwC's 2025 AI Jobs Barometer puts the broader wage premium for AI-skill roles at 56%, up from 25% the prior year (source).

If you're senior — staff, principal, director — leverage matters more than it has in years. Having another offer in your back pocket is no longer a luxury. At this level, it's the only way to reach the top end of the pay range. Don't accept the first offer. Keep two other processes going until you have a number you can sign.

If you're junior or mid-level — the AI premium has shrunk because “I use AI tools” is no longer a differentiator. Everyone uses AI. At IC2 / IC3, what you need to show is what companies have always wanted: you can own a feature on your own, you can measure the outcome, and you can make judgment calls when the answer isn't obvious. Branding yourself as “an AI engineer” stopped working in late 2025.

6. Hiring got slower — mostly after your final round

SmartRecruiters' 2025 Recruiting Benchmarks Report (based on roughly 90 million applications and 1.5 million jobs across 95 countries) puts the tech industry median time-to-hire at 48 days — 26% slower than the global cross-industry median (source). The interesting part isn't the headline number — it's where the slowdown actually happens. Tech is about 10 days slower than other industries between your final interview and your offer.

That changes how you should plan. Expect 6–8 weeks from recruiter screen to offer, and expect the silence after your final round to last longer than it used to. Companies are taking longer to debate, compare you against other candidates they're still talking to, and finalise the comp number. If you panic during that silence and lower your asking price, you've just paid for the company's caution.

What to prep: keep two other interview processes going through your final round. Send a substantive thank-you within 24 hours of your final interview — not within 4 hours (that reads desperate). Then go quiet and let them finish deciding. The only leverage you have during a 10-day decision silence is another active offer, and you only have one if you started the other processes early.

What to do about it

These are six general shifts. Your interview isn't general. To turn this article into real prep, you need to apply these to the specific role you're walking into:

1. Ask if AI is allowed before the round. Canva and Meta are exceptions. Most companies still ban it, and the wrong assumption sinks you.
2. Practise your AI-judgment story out loud. Pick two real moments where you caught or rejected bad LLM output. Rehearse them until they sound natural — not scripted.
3. Ask the recruiter what the take-home format is. Three different patterns are out there. Assuming the 2023 format is the fastest way to under-prepare.
4. Run a comp benchmark on the role. If you're at staff or above, the pay range is wider than it was eighteen months ago. Leverage matters more.
5. Plan for a longer wait after your final round. Tech loses 10 days at the decision stage compared to other industries. Keep two other processes going.

The honest AI prep tools — Calibrd, Hello Interview, Exponent — keep the AI in the prep phase, not the interview phase. That's the side of the line the industry is trying to widen.

If you want a coach to do this on the specific job you're prepping for: Calibrd reads the job description, predicts the questions that company actually asks at that level, runs a comp benchmark for the role and location, and drills you out loud with an AI coach that won't cheat for you. It puts the AI in your prep, not your interview — and that matters more in 2026 than it did a year ago.

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Sources

• Canva engineering blog — “Yes, you can use AI in our interviews” (June 2025) — primary source for sections 1 and 4 (policy reversal, question redesign, five-competency rubric, Simon Newton quote).
• CoderPad — “AI in the interview is not cheating, it is the job” (Meta pilot, October 2025) — primary source for the Meta CoderPad pilot, three-panel layout, model menu, and internal recruiting framing.
• CoderPad — State of Tech Hiring 2026 — survey source for the #1 (catches AI mistakes, 66%) and #2 (explains trade-offs, 56%) graded skills.
• Karat — Engineering Interview Trends 2026 — survey of 400 engineering leaders (US, India, China); source for the “over half of candidates use AI when told not to” estimate and the take-home signal decay framing.
• Levels.fyi — AI Engineer Compensation Trends Q3 2025 — staff AI premium 15.8% → 18.7%; entry-level premium compressed 10.7% → 6.2%.
• The Pragmatic Engineer — “The Reality of Tech Interviews” — $1M+ TC packages for AI-infrastructure staff engineers; HPC, ML systems, responsible-AI specialist comp.
• SmartRecruiters — Recruiting Benchmarks 2025 Report (PDF) — 48-day tech median time-to-hire, 26% slower than global; decision-stage 10 days slower than other industries.
• PwC — 2025 AI Jobs Barometer — 56% wage premium for AI-skill roles, up from 25% prior year.

A few caveats. Most of the strongest evidence comes from two named companies — Canva and Meta — so the article names them rather than generalising to “FAANG.” Vendor surveys (CoderPad, Karat) are checked against non-vendor sources (Levels.fyi, Pragmatic Engineer, SmartRecruiters, PwC) where possible. All the data is US-centric. Karat covers India and China in its survey of engineering leaders but doesn't cover Europe. Last audited: 31 May 2026.