I've been on both sides of the data engineering hiring table for years. I've written interview loops, failed interview loops, and watched candidates ace screens that told me absolutely nothing about whether they could debug a silent data loss bug at 2am. The signal was always thin. Now it's basically noise. Here's the situation in 2026: 64% of companies ban AI in interviews. Candidates use it anyway. One company measured 80% of candidates using LLMs on take-home tests despite explicit prohibition. AI cheating on take-homes doubled from 15% to 35% between June and December 2025, and that number is accelerating. The traditional code screen; the thing that was supposed to separate "can do the job" from "can't do the job"; is dead. It just hasn't stopped twitching yet. So if an AI can spit out a clean solution to a medium LC problem, what does asking that problem actually tell me about you? That you memorized something a machine produces on demand? I've been interviewing FAANG data engineers for years.…