I have a little bit more time so lets start with a layoff done "right".

Back in September 2024 Microsoft laid off "650 roles across Microsoft Gaming" they had severance, extended healthcare, and outplacement services. The reasoning was "streamlining" and "sustainable future growth". Why people had to be fired for growth I'll never understand, but they had just purchased Activision and I guess they wanted to change the structure.

https://www.theverge.com/2024/9/12/24242695/microsoft-xbox-layoffs-650-employees

This is where my clear tech workers bias shows. This shit has been prevalent in transportation, retail, chain restaurants, factory work, anywhere they have high turnover or hire and fire large groups of people regularly. I had Neighbor’s kids answer weird personality questions with the camera on to judge their fit for a role. That was for an analyst role at a large financial institution before this recent AI takeover!

So, no training and a clear message that people who were doing their job well without AI were no longer considered to be performing.

Will AI models be used to analyze a profile of each worker to see if they “fit”? If the people doing the reporting are doing their newly defined job, then absolutely.

Shopify and other places… have publicly been reported to say that AI usage metrics are going to be used in performance reviews. (With memos obviously not vetted by HR.) This is a new job requirement and in Shopify’s case employees were directed to engage in self learning on their own time.

From what I can tell surveillance AI is a mix of traditional machine learning, normal database usage and prompts to describe what someone thinks they’re looking for. We don’t need AI for surveillance (workplace or otherwise) but I think it makes it less reliable and more accessible.

90% accurate and 100% more capable.

“Show me people who are complaining about leadership in slack, or on zoom”. It won’t have any nuance but oh my it’s been trained with examples of complaints.

I will probably write the section slowly as I do research to try to disprove what I think I know. Because science rules everything around me.

Also old papers on software engineering, they rule things around me too. Here's the PDF of No Silver Bullets

https://worrydream.com/refs/Brooks_1986_-_No_Silver_Bullet.pdf

So this gets into workers rights. Let’s start with surveillance, and then illegal layoffs and let’s end with the German concept of a “works council” and unions.

I’m gonna shout this loud and far, I am incredibly ignorant on this topic. I know very little about the history, the current state of the world, and what’s getting enforced today.

However, I seem to be less ignorant than a lot of my peers. I welcome the ones who know more than I do to chime in.

We have CEOs telling junior developers to not bother learning how to code, try to vibe code. That’s scary! You don’t learn much with vibe coding. Learning is the best part of the job!

I tell my junior engineers to not outsource their learning. AI can’t do the modeling, the architecture, the understanding. Can it do boilerplate? Sorta! But the job isn’t writing boiler plate.

We knew this way back with the no silver bullets essay on incidental vs necessary complexity.

When this bubble bursts, and the fraction of software that was created during it that remains useful will need stabilization. At some point the infrastructure that hasn’t been maintained will need rebuilding. Many engineers will be hired back again. But the people with the skills will be fewer and older.

When you’re young or new, every technology is new, it’s hard to see the difference. You play along with wonder instead of fear, you feel valued, you haven’t seen the cycle before.

My friends who have spent a lifetime learning how to make stable change on critical systems will be forced to adapt to help stabilize the tools that lost them their jobs.

Some of them will find a way through, some of them will join the Cobal programmers I have met in other industries throughout the world.

They have told me they were let go because they were getting old, or didn’t want to change. I wonder if it was a similar hype cycle that I was too new or young to see.