[dpc_01234]

I don't think I have a "burnout", but LLMs are really exhausting due to amount of pressure they generate. No one is really pushing me to increase my workload, but at every moment there is always something ready, done by my clankers or clankers of other people that I could be unblocking. In the past (before LLMs) it was already hard to keep up, but now it feels like there's 10x more things waiting at any given time, and there could be 10x more if everyone just "optimized" and streamlined processes fed the AI even more tasks in parallel faster. It just being a bottleneck of everything, all the time is tiring...

I am happy about all the little side-projects, and ideas it help my realize, and I enjoy exploring this new world, but I've noticed LLMs feed my unhealthy "don't want to take a break and waste time being idle" mindset, and I need to correct it.

W.r.t. article's main complain - I think the similar thing happened due to factory manufacturing automation. What used to be a varied skillful craft in a shop became standing in a single place of an assembly line doing the exact same thing whole day. LLM took away the more creative and variable part of the work, and left the repetitive QA rubber-stamping. Probably some of the mitigations used back then could be rediscovered today.

[UncleOxidant]

> done by my clankers or clankers of other people

I'm getting so many requests to review LLM-generated documents - planning docs, docs intended for end-users, project docs, business plan docs. A team member sent me a zip file with about 30 LLM generated documents in it the other day and asked if I could review them right away. And a lot of it was just repetition and/or stuff that was just out of left field, made-up, hallucinated stuff. They're able to generate this stuff way faster than we can review. It used to be that it would take a significant part of a day for a project manager to come up with a planning doc - now they can generate one in a few minutes and send it out for review. It's just really tiring.

[mathw]

The only way to even start to counter that is to make it a firm company policy that if you use an LLM to hallucinate any documents you absolutely must thoroughly review them yourself before you send them to anybody else, and that you are still responsible for the quality of LLM-generated content.

Getting an LLM to vomit out a bunch of documents and sending them straight to another colleague is absolutely unacceptable behaviour.

[theideaofcoffee]

This is going to just run up against the insanity that is tokenmaxxing every moment of the day. When people are incentivized (upon pain of firing) to get the LLM to vomit out as much as possible, they're hardly going to stop and ponder if schlepping the slop over the wall is acceptable if the alternative is a pink slip.

Which is going to win?

[thinkingemote]

We employees need to remember that most software projects fail. So the work we produce should have lower value than we give it.

We also need to be motivated to stay in our jobs.

Most developers like their projects and value their work. But the chances are that it's for nothing.

Many developers know they work on bad products (gambling industry, military, surveillance, whatever) and so it's here that they focus on their technologies, tools and frameworks rather than the work they produce.

"Agentic engineering" for example.

Id be curious to see what and how Googlers are doing with their 20% time.

[soulofmischief]

The 20% policy at Google is effectively dead.

[AnimalMuppet]

If tokenmaxxing wins in your company, your company is going to lose. There's an external reality out there, outside your company, and your company has to produce things that actually work out there. Hallucinated AI slop does not help you do that. It leads you to unworkable plans, and if the plans produce, they produce unsellable products.

If you're an employee in that situation, push back if you can. If you can't, put your resume on the street. (But that may not work, these days. If it doesn't, all I can say is ride it out as best you can, and try to maintain both your job and your sanity. How? I don't know.)

[jaggederest]

Feed it into an AI and ask it to adversarially criticize it, doc for doc, send back 30 responses in a zip folder, wipe hands on pants, return to HN.

[nswango]

Don't know if you are serious, but why become part of the problem?

Why not just review a single document quickly, find an error which invalidates the document, and send it back saying "Policy paper 1 mentions X as being on the business plan for Y, it's not on the plan, please can you fix."

[lesostep]

Because they will fix it and send again.

Unless you can write a good-sounding reason why it's on them to review a LLM output before sending it to you, they will outsources this reviewing to you, and it's a lot of reviewing.

[nswango]

It's not a lot of reviewing if you simply find the first thing that makes the document unusable and call them out on it.

If it's genuinely hard to find that single bug .. perhaps the document has reached the quality required for corporate communication?

[lesostep]

Original comment stated that it was 10 documents, all LLM-generated.

In my experience, it does take a lot time and effort to find contradictions between 10 documents. Even with good documentation, it's hard to build a mental map for that amount of information.

[zufallsheld]

Because they'll just paste your remarks in their llm, let it correct the text and send it back to you.

[reed1234]

Why do your colleagues work when they could at least attempt it first?

[da_grift_shift]

This may actually be a solid way to tackle the bullshit asymmetry problem caused by drive-by LLM sloppers.

[jaggederest]

I always laugh because I've been practicing prompting every single day for the last few years, if they want to start a prompt fight, brother let me at 'em.

[sdesol]

> now they can generate one in a few minutes and send it out for review.

I think we will very soon move to a prove to me you've read it protocol and/or introduce speed bumps to slow things down.

[PsylentKnight]

Thats gonna be a no from me dog. I don’t expect anyone to read something I didn’t read myself

[intended]

Rate of generation/Rate of verification is a proxy for signal to noise ratios, just for work.

That ratio has changed, and verification is the hard part.

Verification is the point of all markets (and a decent part of human civ as well).

And review isn’t cost less - https://en.wikipedia.org/wiki/Ironies_of_Automation

[layer8]

> Rate of generation/Rate of verification is a proxy for signal to noise ratios

Hopefully you mean Rate of verification/Rate of generation.

[intended]

Yes! it should be:

Verification/generation

[soonnow]

Yeah I heard a similar thing recently at a presentation. At that point wouldn't it be easier to just send the prompt around?

[senectus1]

I find myself telling co-workers that if they couldn't be bothered writeing the email/document, why should i have to be bothered reading the document/email.

this is just spam, people sending unsolcited data at you and expecting you to swoollow and process that data.

its just rude and unreasonable, not to mention an unconscious (hopefully) act of sabotage.

[AgentMatt]

Seems like for such requests it's necessary to get some proof of work: require a meeting where for every artifact they sent you to review, they briefly explain the gist and point out the motivation for creating the artifact.

[AnimalMuppet]

Side benefit: They get public humiliation for the problems in what they sent around. It could create some social pressure to not send out garbage.

[jjav]

> I'm getting so many requests to review LLM-generated documents

That's the other nightmare of AI slop. So easy to generate endless content. Who will review?

Just today the boss request I review slides for a presentation. But it's all AI slop, generated from querying tickets and docs and who knows what. It's mostly sort of correct but also plenty misleading and incorrect. So now I have to fact check all this slop which will take hours (even with my AI assistance) and rewrite most of it.

If AI didn't exist, he would've had to do the research to generate the content and it would be 99% correct and I could just give a few notes of feedback in 5 minutes. But with the asymmetric AI workload, he can generate it in 5 minutes and I get to spend 3 hours correcting.

[AnimalMuppet]

> If AI didn't exist, he would've had to do the research to generate the content and it would be 99% correct and I could just give a few notes of feedback in 5 minutes. But with the asymmetric AI workload, he can generate it in 5 minutes and I get to spend 3 hours correcting.

Maybe, depending on the boss. Some would have spent five minutes describing what they wanted, and someone else would have spent three hours creating the deck.

[jjav]

I'm fine with that. The company doesn't have infinite people so as long as someone spends 3 hours generating and I spend 5-15 minutes reviewing, that's fine.

Problem with AI is that generation is so many orders of magnitude faster than reviewing so it's basically infinite monkeys on infinite typewriters.

[palmotea]

> A team member sent me a zip file with about 30 LLM generated documents in it the other day and asked if I could review them right away. And a lot of it was just repetition and/or stuff that was just out of left field, made-up, hallucinated stuff

You just discovered the unlock to massive AI-driven productivity increases: outsource the hard stuff to others, or just don't do it at all. Keep the easy tasks that generate a big volume of output for yourself.

[chadgpt3]

It's spam, it's a DoS attack. The right way to handle a DoS attack is to blacklist the sender. But this doesn't work if the sender is paying you.

[groby_b]

Write an LLM script to review them. Tell it to find at least three severe issues. Set to auto-reply.

He who brings the slop cannon shall be drowned by slop rain.

[tanseydavid]

> He who brings the slop cannon shall be drowned by slop rain.

If this approach gets widely adopted, then I think you should probably start building an ARK.

Make it big enough to hold two of every animal species. /s

[deterministic]

Reject documents that contain LLM hallucinations.

Or use LLM's to generate 12+ pages of detailed reviews of those documents and return to sender.

[freefaler]

I got this problem with my own employees, LLM are fine, but lazy slop is not permitted. Current idea is to have a clear "best practice" template for most of the research/specs/problem definition they submit and it reduced the slop to a manageable level. But this might work in a smaller company where the management is reading and is strict about these things.

[aakresearch]

Wait, what? I thought everyone agrees that modern models post September 2025 (or whenever Opus or whatever 5.6789 was released) do not hallucinate, make things up, contradict themselves and can review their own output into perfection regardless of task, goal or context???? /s

[UncleOxidant]

In general I think from the coding side they're more robust now. However, people generating docs are maybe not as experienced with how to prompt in ways that avoid having the LLM tell you what you want to hear. I think this is still a pitfall that can easily be fallen into. Those of us who are doing LLM-assisted coding for the last couple of years are more aware of this now. Those who are planning/management folks are still kind of susceptible depending on how much experience they've had dealing with LLMs.

[KronisLV]

What a take with no nuance.

> do not hallucinate

They do, just less. To the degree of being usable, as long as there are guardrails and they're used responsibly. For example, if there's code being output, there should be type checking and compilation, as well as code tests that prove that it works or that it doesn't - seeing how abysmal code coverage is in most of the projects I've seem, for whatever reason people thought that they didn't really need it much. They were wrong.

This also implies you need SOTA models on max reasoning.

> make things up

Same as above. Ideally you'd give them some way to verify their claims, like web search or browsing and referencing docs, Jira tickets etc., basically improve the signal to noise ratio.

> contradict themselves

They do so way less than before, as long as the above is true.

> can review their own output into perfection

They are pretty good at reviewing things, especially if you make them do adversarial review! It will never be perfect, but can be close in quality to human output (e.g. the code they produce, when used properly and with intent, is better than the code I've seen many developers write and ship before LLMs were a thing).

This also more or less scales with how much compute you give them - three parallel review agents will turn one output artifact into something good with higher confidence than two, and definitely better than with no review. There's a cost vs quality balance and it seems that all those xhigh and max reasoning modes are still geared way too much towards cost, instead of quality. So you have to make up for that shortcoming yourself.

> regardless of task, goal or context????

Garbage in, garbage out. I won't be an asshole and say that you're holding it wrong, nor will I say that anyone should listen to the claims marketing AI (absolutely delusional takes, meant to attract investors), but we're slowly getting to a better position in regards to LLMs, year by year.

It's just a shame that the peak of inflated expectations hit while the technology still hasn't fully plateaued and reached whatever its ceiling is.

I probably also shouldn't ignore the fact that some people will not care about any of it and send AI generated slop verbatim and to an outside observer there's no way to easily tell apart the difference between the two, unless you make a technical report contain exact references to where the data is sourced from, for example (and then either verify the references yourself, or make another agent do it).

[MaKey]

I think you missed the /s (for sarcasm) at the end.

[KronisLV]

Yeah, my bad, though I’ve also heard those arguments more or less said genuinely - on one hand people hold LLMs to some unreasonably high standard, expecting to one shot apps before being deemed good, and on the other just outputting slop with no regard for the quality.

[xg15]

> I think the similar thing happened due to factory manufacturing automation. What used to be a varied skillful craft in a shop became standing in a single place of an assembly line doing the exact same thing whole day.

I had to think of the factory scenes in Charlie Chaplin's Modern Times. The author's feeling is basically the main idea of the sketches, i.e. humans having to follow the pace of the machines instead of the other way around.

Reverse centaurs are nothing new. Ask any worker movement from the last centuries.

[sefrost]

One of the reasons they exhaust me, is that it's always "one more prompt" to get a UI correct. It's often just slightly off, but it can take 5-10 mins sometimes to rework something. It has led to me working much longer hours.

I think this is in part because I am one of the software engineers that always liked building products more than writing complex software. So, I am driven by the feeling of creating something. And I want to get the feature perfect and complete. But getting from 95%->100% done can take a long time with UI work for me.

So I work much longer hours now, unfortunately.

[jaynetics]

It's a bit paradoxical to use AI to increase productivity, and then feel the need to work longer hours to fully actualize said productivity.

But it's probably a common feeling. I wonder if we'll see an increased number of people burn out in the serious, medical sense.

[cuu508]

Perhaps do the last 5% yourself?

[sefrost]

You're right, I should!

Main blocker is I am using apps like Conductor and have lots of plates spinning at once. But that's on, me and I should try and start completing the last part myself.

[r0b05]

This is what I do as I have learnt after much frustration.

[ssl-3]

Maybe when they get better at making SVGs of pelicans riding bicycles, they'll also get better at making UIs that can be reworked into sensible form without too much effort.

[sph]

> LLM took away the more creative and variable part of the work, and left the repetitive QA rubber-stamping

“I wanted a machine to do the dishes so I could concentrate on my creative work, and all I got was a machine to do my work so I’m left to wash the dishes.”

[ryandrake]

> I don't think I have a "burnout", but LLMs are really exhausting due to amount of pressure they generate. No one is really pushing me to increase my workload, but at every moment there is always something ready, done by my clankers or clankers of other people that I could be unblocking.

I see a different type of pressure: I'm at a company that still is requiring everyone use LLMs with token leaderboards, time-spent measurements, and impacts to performance reviews, and all that. So I find myself having to carve out some percent of my time to stop doing productive work, and "go do AI to show token use." So my workload hasn't changed (or it's gone up), but I have N% less time to work on it because I have to spend time appeasing the AI gods...

[efnx]

Just have an agent chug on a side-project for you, or set up a CI script to review every pull request or some similarly “helpful” task. That should eat a lot of tokens!

[eloisius]

Man. If I had this kind of mandate I could really burn some tokens. Review each new PR and extract 100 topics to debate related to it. Spin up 1000 sub agents, each with a different personality profile system prompt, to debate each point until consensus has been reached. Synthesize the learnings into a limerick. Build a Spotify playlist that pairs with the tone of the debates. Post the limerick and link to playlist on the PR and tag me to notify me that I have a PR to review.

[jaggederest]

Oh man, when MCP was still new and shiny I made an MCP that let the AI choose appropriate theme music for what it was doing and it was an absolute blast, I need to make a more modern one.

Peer Gynt Suite's "In the Hall of the Mountain King" made a prominent appearance, but so did Aqua's "Barbie Girl"

[fhd2]

Depends on how much you're asked to burn I guess. Until one point, it's actually helpful. Then there's a point where you can do stuff that's semi helpful but doesn't get in the way. But then I would imagine you reach a point where you have to come up with a token burn strategy and some kind of narrative for your manager that's in line with it. I bet at that last point, it gets taxing.

Probably like eating. Having to eat less to loose weight isn't great. Eating anything you want without worries is great. Having to eat more than you want to gain weight, not great.

[marking-time]

Also, post the limerick to HN.

[chrisandchris]

> side-projects

Just be careful about any legal implication of doing side-projects during work with work-resources.

[vkou]

Ideally, you should ask the LLM to write that CI script.

[derdi]

I wonder how long this will still be a thing. More and more companies seem to come to the conclusion that tokenmaxxing is just too expensive for the value it delivers. Will there be others that continue doing it? Will there be companies that advertise "unlimited tokens" as part of job listings? How will they react when employees test the limits of "unlimited" (whether by accident or not)?

[jorisw]

Probably easy for an outsider to say but companies tracking their workers quantatively like this would have me looking for another job

[bdlowery]

What work are you doing where an LLM can’t meaningfully contribute to your everyday work

[adverbly]

> No one is really pushing me to increase my workload

Spoken like someone who is not at an org/team that has undergone layoffs and reduced hiring in the last 3 years.

You might be in the minority there - especially when it comes to those who are facing burnout.

[missedthecue]

I don't have an employer. But most of the excuses I used to tell myself are simply not believable anymore and that causes pressure leading to overworking myself.

[bsoles]

My employer literally put "effective use of AI" as a yearly performance review criteria this year. So there is that...

[onion2k]

I am happy about all the little side-projects, and ideas it help my realize..

Same, but I really have to fight the urge to just add fun new features to things I work on any time inspiration strikes. I am an appalling 'feature factory' if I don't actively keep myself in check. The cost of just building everything is so low, but the value of those things is also incredibly low, so I'm often just bloating what I build.

There's been a lot of articles and posts about the increasing importance of 'taste' in software built with AI, and I'm finding I know need to look for strategies to find some.

[agumonkey]

I wonder if anybody has an implicit fear that with LLM you're expected to be a 20x engineering all the time, otherwise you're out. Can also lead to people producing shiny apps that impress others (sometimes for legit reasons) even though they have no idea how anything work. A "ship value" culture will not bother with the inner workings or actual skills.

[nacozarina]

LLMs drive the unit cost of cognition to zero. Therefore, you will exhaust yourself near-instantly trying to drive differentiated value out of cognitive work. Non-arbitrable labor is one safe haven: bending steel, drilling wells, running cables, flying drones, etc. Physical agency gets you a premium the clankers can’t (yet?) trespass upon. That’s why guys building data centers are making bank & job-hopping while the SAs administering the computational guts of them are struggling. A second vector is reputational: either by authority (you’re a regulator) or by taste (you’re a rare/reknown specialist) you make quality attestations about cheaply-produced cognitive artifacts. The first vector is a big community; the second is not. Get out of being in a knife fight with the clankers on their own turf, they’ll gut you.

[ehnto]

Flying drones is an interesting one, I guess you do have to drive the car out to site and set up the drone. But a lot of drone ops are waypointed, automatic flight. I can see a future in which the only thing the operator does is drive the drone van to site, hit the deploy button as the drone pops out the roof, and wait for it to return. Mission set up already by an LLM prompt back at the office.

[imhoguy]

I bet drone van is the next thing to be automated.

[reverius42]

For legal reasons, a human will still need to be in the self-driving van, so the job description will change to "drone van chaperone".

[Freak_NL]

Or 'drone accident scapegoat'.

[intended]

I’d scope it down further than cognition.

Cost of generation has been reduced, and is highly subsidized currently.

Cost of verification has effectively not changed. I’d say as a rule of thumb: verification is the tough part.

Our brains don’t fare well under constant review pressure. https://en.wikipedia.org/wiki/Ironies_of_Automation

[Planktonne]

> LLMs drive the unit cost of cognition to zero.

This isn't the problem; the problem is that people incorrectly believe it to be true.

[zahlman]

> LLMs drive the unit cost of cognition to zero.

Then why are so many others in the thread reporting being swamped with requests to review coworkers' slop? If it's genuinely "cognition" at trivial cost, surely this review would be completely unnecessary?

[wisty]

Individual gains from llm seem much larger than net productivity increases. I think a major source of this discrepency is people creating more work for their coworkers at the speed of slop. Especially the people with no idea.

"I did a Chat output, please fix and review it " is the kind of thing that empowers the people who used to have a minimal productivity, and now lets them to wreck things on an industrial scale.

[yuye]

>"I did a Chat output, please fix and review it " is the kind of thing that empowers the people who used to have a minimal productivity, and now lets them to wreck things on an industrial scale.

AI is not a productivity multiplier. There are diminishing results.

The ones that notice the highest increases of productivity are usually the ones that were unproductive at best and dangerously incompetent at worst.

[zahlman]

> AI is not a productivity multiplier. There are diminishing results.

Sure it is. Just that some of the values being multiplied are negative.

[nomel]

Could you describe your usual workflows and usage patterns with AI?

[nomel]

I think this is a perfectly reasonable question. They're having a very different experience than many other people (including myself). It would be interesting to get an idea of why it's so different.

[yuye]

>Could you describe your usual workflows and usage patterns with AI?

I don't. I'm not a gambling man, and I respect my fellow engineers to not inundate them with slop.

[apsurd]

This is valid in the other direction as well. Principle engineers, CTOs, with legitimately earned authority end up using that authority to 100x their output onto the team as if it was a Godsend unlock.

It's not. There is no one person that has universally good taste. Also, we're not in your head, no matter how much better of a coder or whatever. We're not in your head and it's all terribly painful to navigate.

[wisty]

I'm just waiting for Bezos to order all work with human agents to use the same API and guardrails as an LLM.

[imhoguy]

Isn't it how these fulfilment centers already work that way with all these work manuals. Read AMAZON.md /s

[topgrain2]

> Individual gains from llm seem much larger than net productivity increases. I think a major source of this discrepency is people creating more work for their coworkers at the speed of slop. Especially the people with no idea.

Lots of companies (nearly all, I’d wager) of any size were leaving bare-minimum a 2x software development speed increase on the table before LLMs, having nothing whatsoever to do with how fast anyone was typing or thinking up code, and everything to do with how they organized and supported development work, and with your basic ordinary corporate dysfunction.

My company, I’d say it was more like 4x or 5x they could have achieved before LLMs, by fixing processes and reducing how often management steps on their own dicks.

All the people I’m seeing with crazy-high LLM productivity at my company? They’ve been given enormous autonomy to basically go do WTF ever they want, and people are jumping to get them anything they need (and most of what they’re doing is prototyping, for that matter). So right off the bat, if they’re competent, they should see a notable multiplier on productivity even if they weren’t using LLMs. Not that those aren’t helping, too, but if you don’t change processes they’re not all that effective, because the problem wasn’t speed of code-writing (and if you can change processes, you already could have sped up development a lot before LLMs…)

[imhoguy]

In my place I see currently a governance panel effort mandating around LLM agent skills usage, it is so much shit show that I expect productivity is going to fall to 0.5x pre-agents. But not pre-LLM as autocompletion was really helpful in the trenches. The tool in wrong governing hands and you get sand into cogs thrown.

[AnimalMuppet]

Hmm. When you put it that way, it sounds like LLMs and social media trigger the same "I have to see what's going on now" pattern (and therefore can wind up at the same kind of addiction, with the same problems).

[thefourthchime]

I echo this entirely, brother. I think a lot of us developers have a lot of ideas that were unrealized, and now we have this opportunity to do it. And any time an LLM is sitting idle, it feels like we're wasting our time. Why aren't we having it built something for us? Currently, I work on about three projects at work at the same time and about four personal projects at the same time. My day just zips by. I'll burn four hours without even thinking about it. It's exhausting but exhilarating. I do wonder if burnouts in the future though.

[alfiedotwtf]

> I've noticed LLMs feed my unhealthy "don't want to take a break and waste time being idle" mindset, and I need to correct it.

Embrace it if you’re like me and feel uncomfortable having an idle mind, embrace it! You’ll get more done and being 120% go go go is impossible over the long run so eventually your body will just say I need a break then once you recover full steam head again on the treadmill

[jug]

This article is also related to exhausting AI through generating pressure and posted here recently:

AI coding is addictive. Engineers are paying the price https://leaddev.com/ai/ai-coding-is-addictive-engineers-are-...

[walrus01]

> No one is really pushing me to increase my workload, but at every moment there is always something ready, done by wankers

I confess that the above variant on the quotation is how I originally read it. And that's just about how I feel now with trying to sort through vibe-coded slop projects that are put forth by (well-meaning, probably good intentioned, not evil) people who represent them as if they're the handcrafted result of one dedicated developer.

[Hilliard_Ohiooo]

That ALL sounds horrible, is that really life in tech these days?

[jjav]

Yes. Run away if you can, run far away.

[KronisLV]

> In the past (before LLMs) it was already hard to keep up, but now it feels like there's 10x more things waiting at any given time, and there could be 10x more if everyone just "optimized" and streamlined processes fed the AI even more tasks in parallel faster.

I find LLMs to help me manage the unrealistic workload I have, because at least now it's feasible instead of just getting more work piled on top of me with a never ending backlog (that people actually expect me to thin, not let grow). Add on top of that colleagues that would have death by commitee'd many ideas and now just have to argue against actual MVPs that work instead of ideas (or can be proven to not work and discarded without wasting time on them in some cases), and I don't even hate my job as much!

It's just that to ensure that the technology is not a net negative, I need millions upon millions of tokens every single day (tool runs, adversarial reviews, testing), but once you get that inflection point, alongside needing a good enough model, the floor for which currently I'd say GLM 5.2 on Max reasoning reaches, or use something like SOTA Anthropic/OpenAI models, it becomes a pretty good way of working. That said if you have missing pieces there (e.g. using cheap models that aren't very good), the curve of getting stuff done can go downwards and you'll just end up with a lot of slop - useless docs, bad code and an ever increasing amount of technical debt.

On average, each task that I do, needs about 15 minutes to 2 hours of planning and making the agents explore the codebase and refine the plans first.

Curiously, in my case this leads to less burnout cause I can actually pause and grab a drink, meal or go for a walk, while parallel agents do the work, once I've planned things well enough and have dispatched something that will work for 1-4 hours. I don't have to review their output immediately once they finish but can just batch things.

[jjav]

> but at every moment there is always something ready

Yes, this is to me the primary driver of the extreme AI burnout. In ~30 years in Silicon Valley and many, many startups, the pressure has never been as intense.

Before AI I'd mostly work on one thing at a time (at least within a given hour) and in the evening I wouldn't start a new 6 hour task because it's too long, so tomorrow is another day.

Now, that 6 hour task is more like 30 minutes, so there is intense pressure to just knock it off tonight. And then the next one. And one more. And while the bot is thinking, to have 4 other work streams in parallel so there is never, ever, a break in the day. The human mind is not built for 100% utilization 15 hours a day.

[rib3ye]

Yeah, but it's that KIND OF AWESOME?