AI-assisted engineers are burning out, is this fine?

totalslop_ai

Writing code was slow but you understood what you built. Reviewing AI code is fast but you're accumulating blind spots. Both the human cost (this article) and the codebase cost are growing together.

mark336

This was bound to happen. Probably won't get better, but will mean we will need more emphasis on mental health.

harlanji

Exchange / "chat" requests like with a human contractor feels like the optimal bandwidth. Imagine having a report whose work nobody in the org understands or owns? Can't scale into maintenance or support mode. I might be open to some agent-like behavior, access to a git repo and ticket system. Probably not my whole OS, any more than I'd give to a drunk schitzo I met on the Internet. I see the appeal to what people have going on. But I've been using LLMs for going on a year, I was slow to adopt and wait-and-see because I didn't need it at the time (deep dive, learning python Ecosystem). I'm glad I stayed the course. I can get great results prompting these things and edit the results with care. No more burnout than a subordinate working for hire in this mode. Things remain manageable, and I can do all the higher level Dev/Eng/Product work that drives the Coding. Which is a good new challenge to me, never got to go so high up the food chain with so much focus.

tracker1

My only thought is take your time to actually review what the LLM/Agent generates... ensure that you understand and can follow it. Give feedback and iterate as necessary. I've used this analogy a lot, but it's really a lot like managing remote development teams in a lot of ways... and even though you can also use agents for planning, it becomes a critical step as part of the communication loop when you aren't sharing a physical space. I emphatically do not use multiple agents at a time... I monitor what the agent I'm working with is doing, stop it if it's going down the wrong path and give feedback along the way... don't be afraid to git reset a set of changes, then tell the agent you did so and why. Spend more time on structure and design up front, it will save you a lot of headaches later. Beyond this, I've found the "5 hour window" that anthropic gives to be pretty helpful... when I've expended my allotment for the window, odds are, I've done enough for the day even. Read, work on something else, etc... know when it's a good time to stop for a day... it's easy to over-work yourself... it takes discipline to actually break for lunch, or the day. For that matter, step away from your desk for lunch and plan to take at least an hour if you can. You can still deliver a crap ton of value beyond what you individually could do with an agent... but there needs to be a human in the loop for anything that people depend on for their money or livelihood.

m0llusk

Working on some experimental coding it reminded me how coding in little steps then testing, documenting and coding some more is basic to making development work. Now LLMs encourage big chunks of development all at once. The interfaces, back end, tests, configuration all appear at once, fully formed. Coming to terms with the code still requires taking in minutia, but keeping up with LLMs ends up exhausting this capacity. The new method is fully the opposite of what has been known to work.

ryanolsonx

I’ve felt burnt out- it’s pretty exhausting reviewing and testing code all day