There's this joke about clients not knowing what they want, so they couldn't possibly explain it to an AI and therefore developers will keep their jobs.
Honestly AI works for writing a small function, and it's definitely superior to Google / SO when searching for code examples.
But in the context of a large app with more exceptions than business rules and where you have to take in to account legacy code & constraints ... I don't see an AI figuring that all out for the simple reason that it's too hard to explain to it the big picture.
Sounds like the ultimate business idea. Sell customers a magic shovel that eliminates their need to hire shovelers. If it doesn't work, just tell them to be more specific with their requests to the Shovel.
Agree as well. We are at the very beginning, AI is the worst it will be right now.
Those who keep saying 'I can't see how my job is at risk' living under a rock.
I remember watching streaming video on the real player on a 56k modem. It was a complete joke but you could envision things getting much better.
Is it fair to say TV broadcasters/production professionals were in danger of losing their jobs in that moment? Kind of, but TV broadcasters/production professionals were also the people in the best position to take advantage of the new advances.
Of course, that was predicated on being open to change and not clinging to the past.
Surely, anyone on HN talking about AI right now is in good shape.
We are inside the bubble. There is a huge % of even young people who have no interest in any of this. It is like 50% of 18-29yo haven't even used chatGPT themselves in the US.
Most candidates nowadays are obliged to deal through low grade, poor quality recruiters. Demonstrating creativity to these morons is an absolute waste of time.
Those "poor quality recruiters" only work with the data you give them. If you give them the same stuff everyone else is giving, what leads you to believe that they'll side with you? They naturally tend to go with those who help them justify their decision, and that's where that creativity enters the picture.
One way to contrast these in broad terms is that tools like Airflow are generally much more focussed on continually running well defined production workflows, while tools like Snakemake are mostly focused on creating a reproducible pipeline for one particular analysis, or making it easy to perform exploratory analysis, exploring the effect of different input data and parameters.
One way this focus is reflected is how e.g. Snakemake are much more focused on naming files in a way that you can figure out what input data and parameters were used to produce them, making it easier to compare results from variations on the main analysis.
If you are interested in knowing more about the differences of a pull-style workflow engine like Snakemake which is geared towards Bioinfo problems vs a push-style workflow engine which is geared towards data engineering, you might find our write up helpful: https://insitro.github.io/redun/design.html#influences
There are other important dimensions on which workflow engines differ, such as reactivity, file staging, and dynamism.
By design, Airflow needs a centralized server/daemon, whereas snakemake is just a command line tool, like make/cmake. This would become an issue in the HPC environment.
In Airflow the workflow is assumed to be repetitively executed whereas in snakemake it is usually run once (like you will only compile the program when source files change).
Airflow has a queuing system, whereas Snakemake is to be used in conjuncture with other task management systems.
In Snakemake, shell script always feels like a second-order citizen, whereas with Snakemake, it has good support for shell scripting, which enables easy integration with tools made in other programming languages.
I don't know if I would call it "atrociously" bad rates but a quick scan of Cobol listings on Indeed somewhere between $90K and $110K. I'm sure there are outliers on both sides.
Honestly I feel the rates for all software devs have gone down from a year ago which I am sure has something to do with the massive layoffs from the big companies.
‘Understanding the business logic and getting it out of the customer’ is precisely what a lot of programmers are bad at doing. Many would rather talk to a compiler than a human being. For them, ChatGPT is a real existential threat.
