___luigi

> flagged it as “no” because they had too many position changes

This is wrong and misleading in many ways, you should ask people why they left, you should give a chance to those who have good skillset, not based on number of jobs they had. I know a lot of people who worked on contracts, so they had to change employers frequently, and I know a lot of people who were looking for a place, as juniors, to learn from good mentors. It is really hard to find mentors in Startups, and not everybody can make it to big companies. If companies don't invest on their employees, they leave.

"Indistractable" by Eyal Nir is a good book if you want to dive into this topic.

I would like to see a comparison between this operator and Stolon.

One book that helped me understand these challenges was "Hard things about hard things". I recommend/gift the book to any (engineer) friend who is burning to start his own business. It's a different game. Even Sr. Engineer is a different game than coding, we spend some time on System design, mentoring, presenting technical outcomes of our work/PoCs, writing new product requirements, .. etc. I think these tasks require other skillsets as well.

Disinformation is a problem for all social media platforms, for all languages, FB is one of those platforms. I have the feeling that media focuses more on FB & English, but we should rather focus on the problem as whole and its harm for all communities around the globe.

This is GREAT summary!

I work in a large organization, in an industry that is naturally slow. The work (in the industry) is slow because it's critical to deliver stable and reliable solution because large part of population and economy rely on this industry SW/HW. I have heard a lot of complains on how the process is slow, but in many cases, building on top of existing work takes a long time. It takes long time to understand legacy work, to go through older studies and projects, and to find spots to add contributions. Not all of us work on green field projects, but many of us maintain code/work that doesn't look "cool".

> YouTube recommendations quite good

I feel it suffers from "rich is getting richer" phenomena. Once the video start trending, the recommender starts showing it for any search.

Is there any reference to delve in the details of GIL, multithreading, multiprocessing, high performance computing on top of Python eco-system?. There are some interesting projects such nimba, Dask, etc, but the resources are a bit scattered.

> Based on a small user study, we find puzzle difficulty to correlate between human programmers and the baseline AI solvers.

Now that we have AI to solve "LC type of questions", can we stop asking candidates to invert a linked list in an interview.

I think it depends on how you use it. I find Twitter more useful than Linkedin.

I think the author was focusing more on general applications (given his research & industrial background). In computer vision & NLP, the field is a bit advanced and it's harder to come up with rules. The promise of Auto-ML is bigger in these two fields.