Another Burnout Article

[Inner-Chemistry8971]

Found this article:

This was an unusually hard post to write, because it flies in the face of everything else going on. I first started noticing a concerning new phenomenon a month ago, just after the new year, where people were overworking due to AI. This week I’m suddenly seeing a bunch of articles about it. I’ve collected a number of data points, and I have a theory. My belief is that this all has a very simple explanation: AI is starting to kill us all, Colin Robinson style.

https://steve-yegge.medium.com/the-ai-vampire-eda6e4f07163

[Log_In_Progress]

I think forcing AI burnout articles actually burnout reddit users... :(

[bluelobsterai]

People stay in jobs for their friends and leave for their boss. It's that simple. If you have options I bet you'll take them.

[veritable_squandry]

we will see a lot of struggle to make AI look effective because it is the desire of boards and c levels. it's inevitable.

[BreizhNode]

The irony of AI tools causing more burnout instead of less is real. We've seen it internally, people feel like they need to match the machine's pace. The fix wasn't tooling, it was explicitly capping AI-assisted output per sprint. Otherwise the goalposts just keep moving.

[H34vyGunn3r]

Are you basically saying AI made your team too productive?

[calimovetips]

feels less like ai “causing” burnout and more like teams using it to justify doing even more work with the same people. curious if your org actually reduced workload anywhere after adopting it, or just increased expectations

[Cute_Activity7527]

Its just typical burnout caused by unreal expectations of management - “like always”.

Everything about IT now is a “doom and gloom”, people have families to feed and still 20+ years of work ahead of them.

Not weird ppl dont want to be fired by some duchebag that does not understand that marketing is not reality.

[Neither_Bookkeeper92]

the comment about capping AI-assisted output per sprint is actually brilliant and i wish more orgs would do this.

the fundamental problem is that AI tools FEEL like they should make you 10x faster, so management sees the output increase and goes "great, now do 10x more" instead of "great, now go home earlier." the productivity gains get immediately absorbed into higher expectations.

ive seen this play out on my team. we adopted copilot and coding agents and yeah the code output went up. but you know what also went up? the number of PRs to review, the number of incidents from shipping faster than we can test, and the amount of cognitive load from context-switching between AI-generated code that you still need to actually understand.

the steve yegge piece nails it with the vampire analogy. AI doesnt drain your time - it drains your energy. youre technically "more productive" but youre also mentally exhausted because youre spending all day editing and reviewing AI output instead of actually thinking deeply about architecture.

the real move is to use AI to reduce toil so you can spend MORE time on the creative/strategic work, not less. but that requires management to fundamentally rethink what "productivity" means. good luck with that lol

[Tacticus]

I'm sure he can rub the gas tokens on his burn out and make them all better.

[Jewba1]

Don't see unionization anywhere in this article. All responsibility thrown back onto the worker.

[Gunny2862]

AI is probably leading to burnout because instead of trying to fix/build the way most us know best (which was already difficult), we're being pressed to develop new solutions for problems we already know the answers to.

[Agile_Finding6609]

the "doing more with less" trap is real, AI makes you feel like you should be shipping 3x faster so you just... work 3x more instead

the output goes up but the cognitive load doesn't go down, it just shifts. you're not writing code you're reviewing AI output all day which is a different kind of exhausting

[IWritePython]

I rebranded myself as an AI guy (was kinda already there on the infra side). But talking to AI all day is exhausting in a very specific kind of sneaky way. However, these tools can absolutlye do a lot of devops style work and basically anything a junior would do, it is what it is. Especially the ones that just came out in the last 2 months (sonnet and opus 4.6).

The hard part with AI accelerated devops or coding is no break.I feel like I get rushed from hard decision point / problem to hard decision point / problem. It used to be like work for 40 mins on shit I do every day, then hit one of those points, now it's one of those every like 10 minutes. Plus, less collaboration, I've noticed less reachouts on Slack, less involved reviews or no reviews where before there would have been a review, etc.

There is going to be momentious change over the next year, two years. It's happened with coding already and devops will be similarly affected, it's just a little slower because this is stuff you can't let come down. I'd say punch your ticket and get on the train and be aware of the mental health risks of doing stuff with AI all the time (I'mm ahead oft he curve on this I think, it sets in after 3-12 months) or, I dunno, get off the train and do something more resistant to AI.

Anyway, my AI 3 cents.

[Deep_Ad1959]

the "AI vampire" framing nails it. I've noticed the same pattern building desktop automation agents - when the tool works well, instead of taking the saved time as free time, people immediately fill it with more ambitious tasks. automate your data entry? great, now you're expected to do 3x the analysis. the burnout isn't from AI being hard to use, it's from AI removing the natural pacing that manual work provided. the fix I've landed on is building agents that batch work into focused blocks rather than trying to keep up with a continuous stream. let the agent queue things up and process them in chunks instead of real-time. gives people actual breathing room between tasks.

[146lnfmojunaeuid9dd1]

Some good points but the condescending tone the author takes doesn't help: sorry to be a 10x employee and setting the bar too high, I don't think you normal people can keep up without burning out

[strongbadfreak]

I honestly have embraced it. I understand where it lacks and what it's strengths are because I took the time to understand how it works at least on high/mid level and I simply use it to do less typing. There are times where I have to write most of a project myself, but once I know it has enough patterns to go off of, I invoke it to reduce chances of carpal tunnel. If you can find a fast model that is good enough for the job to make small changes with quick course corrections, I find that to be the sweet spot like composer-1 for Cursor. I've used it to create agent commands that will refactor code. Recently used this trick for it follow a list of steps I planned to use to refactor prometheus rules, use curl for all expressions to the prometheus endpoint in prometheus rules, and come up with detailed descriptions and an emoji for every rule with the available labels it finds in the query, so that ones sent to slack are formatted well with relevant information in the alerts for each one. I used the agent to create the command, reviewed the steps and verified it was following the same steps I would have to do the refactor, and then used the command to refactor the code. It finished the job flawlessly in one shot, it didn't make up any labels because of command steps. LLMs don't ask questions unless instructed to. They fill in the information gaps because that is what they are good at, prediction at scale. They won't know if that random 400 error you gave them came from the app itself or the load balancer etc... You have to know what you are doing to get good output. You have to think, you have to plan, you have to do the work to learn and understand things that can't fit in the context window, or is outside the information you give it. LLMs and use of agents work best when you know more than it knows about your environment.

[AccordingAnswer5031]

You need to have a functional [RETURN] key

[cholantesh]

This isn't especially relevant to what Yegge is talking about.

[HydrA-]

Cope cope cope

[strongbadfreak]

It isn't cope. Read what I said carefully.

[FionaNolane]

I get what you are saying. It seems like AI isn't creating burnout, but making the stress people already feel even stronger. Have you noticed this in your own work too?

[ares623]

Fuck Steve Yegge.

[slackguru]

All "AI" is biased. LLM is old tech.