Interview Coder is an invisible AI for technical interviews

I've spent the last decade watching this arms race between interviewers and candidates. Last month I hired a senior dev who couldn't implement a basic database migration when we brought him on but aced our interview problems. Turned out he'd been using tools like this.

The problem isn't the tools - they're inevitable. The problem is that our industry clings to this bizarre ritual where we test for skills that are completely orthogonal to the actual job.

My current team scrapped the algorithmic questions entirely. We now do pair programming on a small feature in our actual codebase, with full access to Google/docs/AI. The only restriction is we watch how they work. This approach has dramatically improved our hit rate on good hires.

What I care about is: Can they reason through a problem? Do they ask good clarifying questions? Can they navigate unfamiliar code? Do they know when to use tools vs when to think?

These "invisible AI" tools aren't destroying technical interviews - they're just exposing how broken they already were.

> The highly talented people will do this for fun

No?

People who have time AND enjoy doing this sort of thing in their free time will do this for fun. That’s the self-selection, then from this pool talent hopefully gets translated into results.

Why reduce your pool to “free time and enjoy doing bounties in free time”? That’s excluding many talented people. I’ll also point out that it’s discriminatory: single childless wealthy men tend to have a whole lot more free time (for example women do most of the unpaid care work in all countries, leaving a whole lot less time for this sort of thing).

I also have a suspicion (not based on any data) that people who enjoy doing bounties in their free time certainly tend to be technically talented, but also tend to have non-technical weaknesses around communication and other soft skills. So you’d self select for this weakness too.

I think if I were hiring remotely right now I’d look to create exercises that could be done “open book” using AI, but that I’d validated against current models as something they don’t do very well on their own. There are still tons of areas where the training data is thinner or very outdated, and there’s plenty of signal in seeing whether someone can work through that on their own and fix the things the LLM does wrong, or if they’ve entirely outsourced their problem solving ability.

And you can say the same for employers that exploit their workers. No one is the villain in their own story.

Does “in-person” mean flying in the candidate, and performing the interview on-site?

Does “100% of their loops” mean everything after the initial contact?

I suspect smaller companies could find this challenging.

I’m old enough to remember when independent recruiters acted almost like “talent agents,” with large payouts.

This encouraged them to curate a “personal brand,” and they would often do a lot of the vetting, themselves.

I believe that executive recruiters still operate that way, but engineering recruiters seem to have sharply declined, since those days.