Meanwhile there's a handful of companies (the one I work at included) using AI to automate code reviews. Sure, these tools are not as good as a real human. Yet

Meanwhile there's a handful of companies (the one I work at included) using AI to automate code reviews. Sure, these tools are not as good as a real human. Yet. Just like 3 years ago companies were starting to ban candidates to use GitHub Copilot, pretty soon candidates WILL find a way to either have ChatGPT open on the side, or listening to the operating system audio and providing real time suggestions during the interview (yeah I know this can be done today). We either go back doing things on site, or we go crazy and let candidates use whatever they want during an interview. Want to use Cursor and Perplexity + R1? Sure, why not. This is what people are using at work anyway. This probably means interview conclusions are going to be even more nuanced, it can't simply be they solved the problem or not (and the interviewer liked the person), but during the actual conversation things moved organically to whatever direction the topic led to - which is what actually happens at work when pairing. As you can see I have no idea how to "solve" this problem moving on, but one thing is for sure, the bigger the gap between tooling involved in actual work vs the interview, the bigger this problem is. It's one thing to ask people to write code on a whiteboard for 30 minutes (because they "write" code in a text editor), and another thing to ask people to write code in a whiteboard and the actual work is people chatting with AI Agents to produce so much software in 30 minutes that the entire thing would look like side projects 5 years ago.