If you write Python, you've probably heard of Pydantic (400m downloads per month) and if you do AI engineering you've probably heard of Pydantic AI (one of the fastest growing agent frameworks). We are also building Logfire - our commercial observability platform, and we are hiring our first Solutions Engineer to take ownership of our post-sales success.
Yes. When I was very inexperienced I still remember being interviewed by an extremely big dog in the open-source world (he was VP of engineering at a very successful startup). I was probably about a 3/10 in terms of quality of interview answers, and unsurprisingly didn't get the job.
Despite that, he still managed to make me feel good about the whole experience. At some points in the interview where I was close/slightly off he'd first coax "that's quite similar to X or Y, don't you think?" then if that didn't work he'd coach "here's how X works, elegant explanation, ok, let's talk about Y".
I remember this vividly years later with a smile. Just like I remember all the negative experiences where people were dismissive or ghosted.
I agree that ending an interview early is a no-go. However if it's an onsite/process with multiple interviews, I think the fairest approach (and I've done this in the past) is to manage expectations ahead of time that the full interview sequence only happens if you pass each one.
This way you don't waste the candidate or your time if it's clearly a no after interview 1. They feel a bit bad because they obviously didn't pass, but if you've communicated ahead of time it's not a rug-pull.
Timing matters. The latest generation of VR headsets are incredible. I feel like this point matters, the same way that Netflix needing broadband to be fast enough to stream video mattered.
Very true. This is one of the amazing things about Stripe support. They are the only large company where the first person you talk to actually has a clue
Great post. A key point you don't bring up is the aftermath, even if you do deliver. Especially in non-tech companies there still remains the tendency to view these projects as "done" after the end of the project/MVP etc., with no understanding that sites need ongoing maintenance and improvements. And that this work is still considerable.
I can see this being really useful on documentation sites, kudos.
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If you write Python, you've probably heard of Pydantic (400m downloads per month) and if you do AI engineering you've probably heard of Pydantic AI (one of the fastest growing agent frameworks). We are also building Logfire - our commercial observability platform, and we are hiring our first Solutions Engineer to take ownership of our post-sales success.
See the full description here: https://pydantic.dev/jobs/solutions-engineer