Serious question: why aren't so many startups hiring processes filtering out a candidate who is scamming/working multiple jobs?
Office politics comes after you land a job so it doesn’t explain why he was so successful at getting multiple offers.
I’ve seen claims on Twitter that he used multiple tactics:
1. Good ol’ cold emails;
2.Using a recruiter for warm intros
3. Applying like everyone else but with a resume that is full of fabrications.
A common thread in many of his victim companies: he targeted mostly (YC) startups eager to hire (AI) engineers quickly so they can scale.
You think? I'm extending the term to actually getting a job in "traditional" organizations. You already have to optimize for keywords etc, don't you? It's not human interaction but a "process".
> he targeted mostly (YC) startups eager to hire (AI) engineers quickly so they can scale.
But they got an "AI" engineer didn't they? Or no one in management could define what an "AI" engineer is?
Tbh I'd give the guy a high paying job, but in marketing.
Some people do well working with obscure stuff like cobol and Delphi etc, but I wouldn't really recommend that unless it kind of just falls in your lap somehow.
Web development is pretty big, if you can work full stack even better. At least that's what I do, and I don't have any trouble getting jobs.
If you struggle with simple interview questions, work on fundamentals. All my technical interviews have been quite easy but the interviewers have been very impressed. This tells me most devs have poor understanding of programming fundamentals. Being able to do well at interviews is not that hard and it opens a lot of doors. Things like advent of code, codewars etc are good practice. Maybe dust off your old DS&A book and go through it again. A good DSA understanding will help you in your daily work as well, it's not just about interviews. You're not supposed to memorize algorithms, you're supposed to understand them, understand what makes some algorithms faster than others, understand how to use different data structures to improve your algorithms. Understand how to judge the performance of an algorithm just by reading it (big O and such). It's extremely useful and important, I use this knowledge on a daily basis and it helps me do well in interviews.
Also be good with databases. The database is the core of an application, it can and should do most of the heavy lifting. An API is basically just an adapter between a frontend and a db.