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.

That's the way society is set up.

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.

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

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.

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)

I'm fatigued by this myth.

> 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

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.

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.

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.

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.

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...

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.

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.

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.

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.

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

> 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.

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.

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 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.

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.

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

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".

Use your own words!

I'd rather read the prompt!

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.

Managing people has always been emotionally and psychologically exhausting.

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

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.

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.