I used FastTrack in the early days and loved the product.
Problem was their question bank was too small so it was easy for anyone motivated to cheat. I spent under an hour reading reviews of what questions were asked, prepared solutions for those questions, and then in the interview there were no surprises. I merely regurgitated my prepared solutions. One of them was making a tic tac toe game.
If employers knew how easy it was to pass the Triplebyte exam then I wonder how many would have allowed candidates to skip to onsite.
This was an issue, but less of one than you'd probably think. I estimate that roughly 10% of people we vouched for were cheating. 10% is certainly not zero, and it was occasionally trouble with clients, but 10% also kind of disappears into the general noise of different hiring processes and steps to the point that that estimate could be off by a factor of 2 or 3 in either direction.
There's also the sort of sad statement that even prepping that much puts you far ahead of the average candidate. We TOLD candidates what to expect (and we do at Otherbranch, too) and the overwhelming majority do not even read that, which requires no active searching, no moral compromise, and no pre-knowledge of our process.
Triplebyte did, late in the history of FastTrack, start rotating problems a bit to address that problem.
The real problem for me is the next point on the page:
> When placed in nature, Photon's motion sensor tends to trigger often due to grass or leaves blowing in the wind, which can cause Photon's battery to deplete quickly if configured to capture a photo when motion occurs.
A future software update may provide a motion-sensitivity setting to help address this scenario.
So, not behind a glass and not outside a glass. Maybe I could place it close to my front door and check who rings to me and which cats pass by? I hope that software update will happen soon. On the other side, the demo images on the Mac app page seem to be all outdoor pictures, so I wonder if excessive motion sensitivity is really an issue.
Yeah, I was trying to set appropriate expectations for the motion capabilities. The sensor is pretty sensitive, so if there's movement within the spec'd range (~5m) it can trigger. It works quite well indoors / in garages / outdoors where there isn't constant movement in the ~5m region.
> On the other side, the demo images on the Mac app page seem to be all outdoor pictures, so I wonder if excessive motion sensitivity is really an issue.
FWIW I captured those using the time-based triggering (every 30 seconds), so the motion sensor was disabled for those photos.
>We provide our models with a working Python interpreter in a sandboxed, firewalled execution environment, along with some ephemeral disk space. Code run by our interpreter plugin is evaluated in a persistent session that is alive for the duration of a chat conversation (with an upper-bound timeout) and subsequent calls can build on top of each other. We support uploading files to the current conversation workspace and downloading the results of your work.
It really feels like I'm just googling for you, you had the feature name.
