AI fatigue is real and nobody talks about it

The waits are unpredictable length, so you never know if you should wait or switch to a new task. So you just do something to kill a little time while the machine thinks.

You never get into a flow state and you feel worn down from this constant vigilance of waiting for background jobs to finish.

I dont feel more productive, I feel like a lazy babysitter that’s just doing enough to keep the kids from hurting themselves

> The Hacker News front page alone is enough to give you whiplash. One day it's "Show HN: Autonomous Research Swarm" and the next it's "Ask HN: How will AI swarms coordinate?" Nobody knows. Everyone's building anyway.

These posts got less than 5 upvotes, they didn't make it to home page. And while overall quality of Show HN might have dropped, HN homepage is still quite sane.

The topic is also not something "nobody talks about," it's being discussed even before agentic tools became available: https://hn.algolia.com/?q=AI+fatigue

This problem has been going on a long time, Helen Keller wrote about this almost 100 years ago:

> The only point I want to make here is this: that it is about time for us to begin using our labor-saving machinery actually to save labor instead of using it to flood the nation haphazardly with surplus goods which clog the channels of trade.

https://www.theatlantic.com/magazine/archive/1932/08/put-you...

I've had conversations with people recently who are losing sleep because they're finding building yet another feature with "just one more prompt" irresistible.

Decades of intuition about sustainable working practices just got disrupted. It's going to take a while and some discipline to find a good new balance.

Moving from horses to cars did not give you more free time. Moving from telephone to smartphone did not give more fishing time. You just became more mobile, more productive and more reachable.

People say AI will make us less intelligent, make certain brain regions shrink, but if it stays like this (and I suspect it won’t, but anyway…) then it’ll just make executive functioning super strong because that’s all you’re doing.

Consider that each aspect has different psychological impacts. The first aspect is the hardest, more intense one.

The second one, translating the ideas in your head into code -- where "flow state" typically comes into play -- is mostly a mechanical, somewhat repetitive task, and hence actually meditative. It is relaxing, almost "cozy", in a counter-intuitive way.

The third part, seeing the code work at the end, is a nice little dopamine reward.

Originally we used to shift between these aspects at a much more balanced cadence: we typically spent a lot of time on the stressful problem-solving part, and even longer on the meditative coding stage. The dopamine hits were spread out across longer stretches of time. (Note that this pattern is fractal, because not only is "high-level algorithm design / architecture -> coding" one cycle, the coding stage itself has similar smaller-scale sub-cycles, e.g. "encountering syntax errors / implementation bugs -> fixing them.")

With LLMs this balance has been disrupted. Now that agents are doing most of the coding, we are spending almost all our time in the stressful problem-solving mode, and then directly jumping to the dopamine hits when the agent delivers code that mostly just works. If you're not YOLOing it and do code reviews, those are also intense, as TFA points out. We get almost none of the meditative coding activity in between.

So it's not surprising that oscillating constantly between two intense modes is going to be much more draining. Vibe-coding may actually be the coding equivalent of doom-scrolling.

I think a lot of recent talk about missing the old way of coding is rooted in the loss of that meditative aspect.

Personally I've noticed I prefer a pair-programming approach with AI, which still lets me spend a lot of my time hands-on coding. It may be because this maintains some of that balance and is more sustainable in the long run. However the allure of productivity from wrangling multiple agents is also very, very seductive...

Since then I've pulled back to 2-3 at a time - thats sustainable for me. But I had to build systems to make it work: larger chunked tasks so I'm not constantly context switching on small stuff, adversarial LLMs where Claude writes and Codex judges so reviews are more solid, tooling to track whether I'm shipping real complexity or just noise. (Thats actually why I built https://gitvelocity.dev - wanted to measure my own output honestly, not just feel productive.)

Two things I've landed on:

First - the "don't context switch" adage needs updating. It was true when switching meant reloading everything in your head. With AI handling more of the implementation, the switching cost is lower. My wife juggles 10 things managing our kids schedules/appointments and shes way better at it than me - not wired differently, just practiced. I think we can build that muscle.

Second - were still measuring productivity the old way. Commits, PRs, lines. AI makes volume trivial so expectations ratchet up. If we measured complexity and value instead, the pressure to churn would ease.

Burnout is real. But some of this is growing pains, not permanent condition.

2. Don't mix N activities. Work in a very focused way in a single project, doing meaningful progresses.

3. Don't be too open-ended in the changes you do just because you can do it in little time now. Do what really matters.

4. When you are away, put an agent in the right rails to reiterate and provide potentially some very good result in terms of code quality, security, speed, testing, ... This increases the productivity without stressing you. When you return back, inspect the results, discard everything is trash, take the gems, if any.

5. Be minimalistic even if you no longer write the code. Prompt the agent (and your AGENT.md file) to be focused, to don't add useless dependencies, nor complexity, to take the line count low, to accept an improvement only the complexity-cost/gain is adequate.

6. Turn your flow into specification writing. Stop and write your specifications even for a long time, without interruptions. This will improve a lot the output of the coding agents. And it is a moment of calm focused work for you.

LLMs because of their nature require constant hand-holding by humans, unless business are willing to make them entirely accountable for the systems/products they produce.

That's the way society is set up.

AI generates a solution that's functional, but that's at a 70% quality level. But then it's really hard to make changes because it feels horrible to spend 1 hour+ to make minor improvements to something that was generated in a minute.

It also feels a lot worse because it would require context switching and really trying to understand the problem and solution at a deeper level rather than a surface level LGTM.

And if it functionally works, then why bother?

Except that it does matter in the long term as technical debt piles up. At a very fast rate too since we're using AI to generate it.

Its a million little quality of life stuff.

Looking at this Windows event log, the server rebooted unexpected this morning at 4:21am EST, please analyze the log and let me know what could have been the cause of the reboot.

It took Gemini 5 minutes to come back with an analyst and not only that, it asked me for the memory dump that the machine took. I uploaded that as well and it told me that it looks like SentinelOne might have caused the problem and to update the client if possible.

Checking the logs myself, that's exactly what it looks like.

That used to take me HOURS to do and now it took me 30 seconds, took Gemini 10 minutes, but me 30 seconds. That is a game changer if you ask me.

I love my job, but I love doing other things rather than combing over a log trying to figure out why a server rebooted. I just want to know what to do to fix it if it can be fixed.

I get that AI might be giving other people a sour taste, but to me it really has made my job, and the medial tasks that come with it. easier.

Yet, The Machine has good points.

>For someone whose entire career is built on "if it broke, I can find out why," this is deeply unsettling. Not in a dramatic way. In a slow, grinding, background-anxiety way. You can never fully trust the output. You can never fully relax. Every interaction requires vigilance.

> you are collaborating with a probabilistic system, and your brain is wired for deterministic ones. That mismatch is a constant, low-grade source of stress.

Back when I bought my first computer, it was a crappy machine that crashed all the time. (Peak of the fake capacitors plague in 2006). That made me doubt and second guess everything that is usually taken for granted in hardware and software (Like simply booting up). That mindset proved useful latter in my career.

I’m not saying anything new. Andy Hunt and Dave Thomas have written about it in a way better way. I find it to still hold very relevant guidelines.

https://www.khoury.northeastern.edu/home/lieber/courses/csg1...

>Think! About Your Work

>Critically Analyze What You Read and Hear

I may be an odd one but I'm refusing to use agents, and just happily coding almost everything myself. I only ask a LLM occasional questions about libraries etc or to write the occasional function. Are there others like me put there?

I review all code it ever pushes, primarily because on occasion it nukes thousands of lines for no reason.

When I read the 'what actually helped' it's clearly decision fatigue they are managing.

Here's the real trick, you need to change how you're using AI. Have the AI do the decisions. Treat the AI like it's a new hire dev that doesnt get to push to nothing. That you then have AI review the changes, have AI build tests around, have AI do a security review.

> AI reduces the cost of production but increases the cost of coordination, review, and decision-making. And those costs fall entirely on the human.

The combination of these two facts is why I'm so glad I quit my job a couple of years ago and started my own business. I'm a one-man show and having so much fun using AI as I run things.

Long term, it definitely feels like AI is going to drive company sizes down and lead to a greater prevalence of SMBs, since they get all the benefits with few of the downsides.

> It's knowing when to stop.

99% of gamblers stop right before they hit it big.

Some people thrive in more stressful situations, because they don't get as aroused in calmness, but everybody has a threshold velocity at which discomfort starts, higher or lower. AI puts us closer to that threshold, for sure.

Managing people has always been emotionally and psychologically exhausting.

Managing AI entities can be even more taxing. They're not human beings.

On the other side, I feel like using AI tools can reduce the cognitive overload of doing a single task, which can be nice. If you're able to work with a tool that's fast enough and just focus on a single task at a time, it feels like it makes things easier. When you try to parallelize that's when things get messier.

There's a negative for that too - cognitive effort is directly correlated with learning, so it means that your own skills start to feel less sharp too as you do that (as the article mentions)

Coding, not so much.

Does it matter anymore? Most good engineering principles are to ensure code is easy to read and maintain by humans. When we no longer are the target audience for that, many such decisions are no longer relevant.

I agree with the article and recognize the fatigue, but I have never experienced that the industry is "aggressively pretending it does not exist". It feels like a straw man, but maybe you have examples of this happening.

It kind of takes its toll somehow; because the solution is "done" one it's fed to the AI, there's no time to recover by churning out boilerplate code or other patterns that sits in the spine.

It's more "full steam ahead, always".

AI is not good for human health - we have it here.

I may be an odd one but I'm refusing to use agents, and just happily coding everything myself. I only ask a LLM occasional questions about libraries etc. Are there others like me put there?

I keep pushing the ai to do absolutely everything to a fault and instead of spending 10mins to manually correct a mistake the ai made i spend hours adjusting and rerunning the prompt to correct the mistake.

I’m learning how to prompt well at least.

Employers expect more from each employee, because, well, AI is helping them, right?

I’ve noticed this strongly on the database side of things. Your average dev’s understanding of SQL is unfortunately shaky at best (which I find baffling; you can learn 95% of what you need in an afternoon, and probably get by from referencing documentation for the rest), and AI usage has made this 10x worse.

It honestly feels unreasonable and unfair to me. By requesting my validation of your planned schema or query that an AI generated, you’re tacitly admitting that a. You know it’s likely that it has problems b. You don’t understand what it’s written, but you’re requesting a review anyway. This is outsourcing the cognitive load that you should be bearing as a normal part of designing software.

What makes it even worse is MySQL, because LLMs seem to consistently think that it can do things that it can’t (or is at least highly unlikely to choose to), like using multiple indices for a single table access. Also, when pushed on issues like this, I’ve seen them make even more serious errors, like suggesting a large composite index which it claimed could be used for both the left-most prefix and right-most prefix. That’s not how a B{-,+}tree works, my dude, and of all things, I would think AI would have rock-solid understanding of DS&A.

With Ai, the situations where you know what you are building and you get into flow are fewer and further apart.

So much more time is thinking about the domain, and the problem to solve.

And that is exhausting.

I like conductor.build, they are doing amazing job, but I don't want to give up my freedom and get heavily reliant on closed source

Usually there was a cadence to things that allowed for a decent amount of downtime while the machine was running, but I once got to a job where the machine milled the parts so quickly, that I spent more time loading and unloading parts than anything else. Once I started the first part, I didn't actually rest until all of them were done. I ended up straining my back from the repetitive motion. I was shocked because I was in good shape and I wasn't really moving a significant amount.

If I talk about excessive concern for productivity (or profit) being a problem, certain people will roll their eyes. It's hard to separate a message from the various agendas we perceive around us. Regardless of personal feelings, there will always be a negative fallout for people when there's a sudden inversion in workflow like the one described in this article or the one I experienced during my internship.

I dont have exhaustion as such but an increasing sense of dread, the more incredibly work I achieve, the less valuable I realise it potentially will be due to its low cost effort.

If “I get exhausted that I have to check in on my coding agent while it does my job” isn’t weak, what is? This has to be satire.

I'm fatigued by this myth.

And even today when it’s useful, it’s really most useful for very specific domains like coding.

It’s not been impressive at all with other applications. Just chat with your local AI chat bot when you call customer service.

For example, I watch a YouTube channel where this guy calls up car dealerships to negotiate car deals and some of them have purchased AI receptionist solutions. They’re essentially worse than a simple “press 1 for sales” menu and have essentially zero business value.

Another example, I switched to a cheap phone plan MVNO that uses AI chat as its first line of defense. All it did was act as a natural language search engine for a small selection of FAQ pages, and to actually do anything you needed to find the right button to get a human.

These two examples of technology were not worth the hype. We can blame those businesses all day long but at the end of the day I can’t imagine those businesses are going to be impressed with the results of the tech long term. Those car dealerships won’t sell more cars because of it, my phone plan won’t avoid customer service interactions because of it.

In theory, these AI systems should easily be able to be plugged in to do some basic operations that actually save these businesses from hiring people.

The cellular provider should be able to have the AI chatbot make real adjustments to your account, even if they’re minor.

The car dealership bot should be able to set the customer up in the CMS by collecting basic contact info, and maybe should be able to send a basic quote on a vehicle stock number before negotiations begin.

But in practice, these AI systems aren’t providing significant value to these businesses. Companies like Taco Bell can’t even replace humans taking food orders despite the language capabilities of AI.

I know more than most there is some baseline productivity we are always trying to be at, that can sometimes be a target more than a current state. But the way people talk about their AI workflows is different. It's like everyone has become tyranical factory floor managers, pushing ever further for productive gains.

Leave this kind of productivity to the bosses I say! Life is a broader surface than this. We can/should focus on be productive together, but leave your actual life for finer, more sustainable ventures.

> When each task takes less time, you don't do fewer tasks. You do more tasks.

And you're also paid more. Find a job that ask less from you if you are fatigued, not everyone want to sacrifice his personal life for his career. That's choices you got to make but ai doesn't inherently force you to become overworked.

Unfortunately, with these types of software simpleton's making decisions we are going to see way more push for AI usage and thus higher productivity expectations. They cannot wrap their heads around the fact (for starters) that AI is not deterministic so that increases the overhead on testing, security, requirements, integrations etc. making all those productivity gains evaporate. Worse (like the author mentioned), it makes your engineer less creative and more burnt-out.

Let's be honest here. Engineers picked this career broadly for 2 reasons, creativity and money. With AI, the creativity aspect is taken away and you are now more of a tester. As for money, those same dumbass decision makers are now going to view this skillset as a commodity and find people who can easily be trained in to "AI Engineers" for way less money to feed inputs.

I am all for technological evolution and welcome it but this isn't anything like that. It is purely based on profits, shareholders and any but building good, proper software systems. Quality be damned. Profession of Software Development be damned. We will regret it in the future.

It is getting very hard to continue viewing HN as a place where I want to come and read content others have written when blog posts written largely with ChatGPT are constantly upvoted to the top.

It's not the co-writing process I have a problem with, it's that ChatGPT can turn a shower thought into a 10 minute essay. This whole post could have been four paragraphs. The introduction was clearly written by an intelligent and skilled human, and then by the second half there's "it's not X, it's Y" reframe slop every second sentence.

The writing is too good to be entirely LLM generated, but the prose is awful enough that I'm confident this was a "paste outline into chatgpt and it generates an essay" workflow.

Frustrating world. I'm lambasting OP, but I want him to write, but actually, and not via a lens that turns every cool thought into marketing sludge.

Code and feature still need to experience time and stability in order to achieve maturity. We need to give our end users time to try stuff, to shape their opinions and habits. We need to let everyone on the dev team take the time to update their mental model of the project as patches are merged. Heck, I've seen too many Product Owners incapable of telling you clearly what went in and out of the code over the previous 2 releases, and those are usually a few weeks apart.

Making individual tasks faster should give us more time to think in terms of quality and stability. Instead, people want to add more features more often.

I write software professionally and remotely for large boring insurance company, but I'm building a side project of an area of interest using AI tools to assist, and I've created in a couple months a few hours per week what would have taken me a year or more to create. I've read other's comments about having to babysit the AI tools, but that's not so bad.

The little benefit I've noticed using AI tools to "vibecode" is sometimes they come back with solutions that I never would have come up with. ...and then there's the solutions where I click the Undo button and shake my head.

Dude! You don't have to use it!! Just write code yourself. Do a web search if you are stuck, the information is still out there on stack overflow and reddit. Maybe us kagi instead of Google, but the old ways still work really well.

Use your own words!

I'd rather read the prompt!

They you have to deal with slop, slopfluencer articles written under the influence of AI psychosis, AI addicts, lying managers, lying CEOs etc.

And you usually, the author of this article being an exception, get dumber and are only able to verbalize AI boosterism.

AI only works if you become a slopfluencer, sell a course on YouTube and have people "like and subscribe".

What about article? <Well known fact> + "nobody talks about" is fire title, really. People will vote for it even without reading the article.

Also: short sentences. For emphasis. Always three.

Feel the same pain as me? Find me on X or LinkedIn, or join the discussion on Hacker News.

Just a few days ago: https://news.ycombinator.com/item?id=46885530

> I shipped more code last quarter than any quarter in my career. I also felt more drained than any quarter in my career. These two facts are not unrelated.

I’m gonna be generous (and try not to be pedantic) and assume that more-code means more bugfixes and features (and whatnot) and not more LOC.

Your manager has mandated X tokens a day or you feel you have to use it to keep up. Huh?

> I build AI agent infrastructure for a living. I'm one of the core maintainers of OpenFGA (CNCF Incubating), I built agentic-authz for agent authorization, I built Distill for context deduplication, I shipped MCP servers. I'm not someone who dabbles with AI on the side. I'm deep in it. I build the tools that other engineers use to make AI agents work in production.

Oh.

> If you're an engineer who uses AI daily - for design reviews, code generation, debugging, documentation, architecture decisions - and you've noticed that you're somehow more tired than before AI existed, this post is for you. You're not imagining it. You're not weak. You're experiencing something real that the industry is aggressively pretending doesn't exist. And if someone who builds agent infrastructure full-time can burn out on AI, it can happen to anyone.

This is what ChatGPT writes to me when I ask “but why is that the case”.

1. No, you are not wrong

2. You don’t have <bad character trait>

3. You are experiencing something real

> I want to talk about it honestly. Not the "AI is amazing and here's my workflow" version. The real version.

And it will be unfiltered. Raw. And we will conclude with how to go on with our Flintstone Engineering[2] but with some platitudes about self-care.

> The real skill ... It's knowing when to stop.

Stop prompting? Like, for

> Knowing when the AI output is good enough.

Ah. We do short prompting sessions instead.

> Knowing that your brain is a finite resource and that protecting it is not laziness - it's engineering.

Indeed it’s not this thing. It’s that—thing.

> AI is the most powerful tool I've ever used. It's also the most draining. Both things are true. The engineers who thrive in this era won't be the ones who use AI the most. They'll be the ones who use it the most wisely.

Of course we will keep using “the most powerful tool I’ve ever used”. But we will do it wisely.

What’s to worry about? You can use ChatGPT as your therapist now.

[1] https://news.ycombinator.com/item?id=46935607

[2] https://news.ycombinator.com/item?id=44163821