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Comment by yieldcrv | Hacker News Reader

A lot of it involves masking and blending in by the candidate

You can easily find an older person ranting against the idea of using full stack javascript, unaware of the V8 changes while still having some valid criticisms

But then wonder if their rejection is ageism, instead of the rant

just one example

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I think the general resistance from older devs comes from the velocity of software in the past decade. I just connected with a former manager I worked with at IT services from my university and we talked about how crazy tech has moved since my time working there. I had the privilege of working on the data center before the university moved to AWS. The entire backend was written in pure C, running on BSD. We had monitoring scripts written in Perl before getting a contract with Splunk. My manager worked on the design of the distributed file system for the university, and is still an active contributor to the distro. It wasn't the greatest system, but it sure was cool. I'd be a little salty too if some MBA came in and said, "we're moving to AWS, Okta, Workday, and Splunk. And oh by the way, we have to rewrite the system in node.js, and these interns are going to do it. Have fun!"

> he velocity of software in the past decade

Enterprise software is going nowhere but sideways for 2 decades already.

But yes, the velocity of new bullshit with dubious value that is consistently getting add on top of each other is just amazing.

By the way, I still haven't seen any single project get value out of SaaS auth (both auths) systems. Why the hell people use them?

Also, I had to check: "The key to driving your business forward? One powerful AI platform that keeps your most important assets on track, every decision on point, and your fleet of AI agents at peak performance. That’s Workday."

Well, people here still didn't manage to make LLMs do anything useful. That's despite a strong push from the top to use them, and many very smart people. They did manage to design a very promising tool that uses LLM in a way that uses its strengths and add a lot of value (that seems to be completely unparalleled - and we just invited the entire economic sector for a talk), but didn't manage to make it work well yet. So, our fleet of AI agents at peak performance...

I can provide more than just one example to back up any prejudice you can think of.

Treating a person as part of a group is the problem.

And when you are trying to isolate one person out of many, like for a job hire, it's not easy to avoid mass-filtering to speed it up.

> Treating a person as part of a group is the problem.

Yes, but it's efficient and effective in a large number of cases.

Those with no programming experience is a group. Those who just graduated a CS program is a group. Fresh bootcamp grads are a group. People with 5+ years of experience with your tech stack are a group.

Is there someone with no programming experience who would turn out to be great? Of course; none of us were born with programming experience, but most people are practical enough to not bat an eye when we use past experience as a proxy to quickly pre-filter the possible candidate pool.

Exactly true. But being hairless apes, we tend to overrely on our ability to group. "Smells like ___, must be bad at finding bananas in modern C++ product development process."

Where ___ is: "no formal education", the accuracy is possibly over 50%.

Where ___ is: "Dutch", the accuracy is below 50%

There is tons of overfitting done by hiring managers

I think staying curious and keep learning regardless of your age is key. You don't really want to be stuck in whatever tech was popular during your 20's or 30's and ignore or reject whatever is new.

That's true for the hiree - but it's not an answer for the hiring group. How do they effectively discriminate for candidates who are apt in current tech, AND will stay current in upcoming years?

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