AI is the reason interviews are harder now

Are Interviews Actually Harder Now?

• Some argue interviews were already “broken” and AI doesn’t meaningfully worsen things; hiring remains largely about luck or connections.
• Others say AI-enabled cheating forces companies to tighten processes (harder questions, in‑person rounds, more heuristics like school pedigree), indirectly making interviews harder.
• A few experienced interviewers claim interviewing is not harder than past cycles; it’s always been difficult to do well.

AI as Cheating vs Legitimate Tool

• One camp: candidates should exploit AI (LLMs, bots, mass applications) to maximize outcomes; the system is a tragedy of the commons, so rational actors game it.
• Opposing camp: this behavior is abusive, unethical, and degrades the hiring ecosystem; some mention potential blacklisting risks.
• Others take a middle view: using search/AI openly is fine; the core issue is dishonesty and misrepresentation of one’s actual ability.

What to Test When AI Exists

• Some say if AI can solve an interview problem, the interview is flawed; we should design tasks AI can’t trivially solve or that require human judgment.
• Suggested adaptations:
  • Code-review exercises (real or synthetic PRs).
  • Debugging/bug-hunting tasks on existing code.
  • Mixed sets of AI-generated correct and incorrect code, asking candidates to discriminate.
  • Assessing how people use their own tools (IDE, Copilot, Stack Overflow).
• Counterpoint: allowing AI in interviews adds noise and obscures individual problem‑solving ability.

Remote vs In‑Person Interviews

• Remote interviewing is seen as easier to game (hidden helpers, LLMs, phones).
• Some advocate returning to in‑person interviews with offline machines and controlled tool access.
• Others note cheating predated AI and even in‑person formats aren’t foolproof.

Broader Hiring Dynamics

• Networking remains disproportionately powerful; this disadvantages immigrants and those without connections.
• Many criticize FAANG‑style LeetCode/hard algorithm interviews as disconnected from real work and serving mainly as high‑pressure filters.
• There’s concern that AI raises the minimum bar: if LLMs can outperform very weak devs, some existing roles may be harder to justify.