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
For me personally, programming lost most of it's fun many years ago, but with claude code I'm having fun again. It's not the same, but for me personally, at this stage in my life, it's more enjoyable.
I think we much too often forget that the domain of software development has expanded its reach into literally everything and that we share a guild hall with all kinds: those who write deeply safety critical correct code, those who are hacking a blender, those who are just making their clerical task less repetitive, etc.
Engineer teams are nothing but an annoying expense on the balance sheet and the goal is to cram as many features, as quickly as possible to get the sale.
That's exactly why I'm happy to use every tool available to get the work done efficiently. To this end, LLMs have been great for me, especially when dealing with large amounts of boilerplate code.
Long gone the days of crafting artisan code.
Of course, I know the next layoff will come. So I simply want to use the next time of stability to make sure I can be that artisan the next time industry kicks me out. But baby steps for now.
Every time you chill out and come back to work, you will have to invest that extra bit of start-up energy. Which can be draining.
(* probably has to do with reloading your working memory)
(In all seriousness though, it's probably not good for your health.)
I'm wholly unwilling to relinquish my health and my morals to "AI" so I can "ship faster." What a pathetic existence that would be.
I do not smoke myself, but it made me realize how little I know regarding THC and CBD
There are plenty of articles on review fatigue including https://www.exploravention.com/blogs/soft_arch_agentic_ai/ which I published recently. The focus there is less about the impact on the developer and more about the impact on the organization as letting bugs go to production will trigger the returning to high ceremony releases and release anxiety.
The OP article talks about AI fatigue of which review fatigue is a part. I guess that I would sum up the other parts like this. The agentic AI workflow is so focused on optimizing for productivity that it burns the human out.
The remedy is also not new for office work, take frequent breaks. I would also argue that the human developer should still write some code every now and then, not because the AI cannot do it but because it would slow the process down and allow for the human to recover while still feeling invested.
That said I don't dispute the value of agents but I haven't really figured out what the right workflow is. I think the AI either needs to be really fast if it's going to help me with my main task, so that it doesn't mess up my state of flow/concentration, or it needs to be something I set and forget for long periods of time. For the latter maybe the "AIs submitting PRs" approach will ultimately be the right way to go but I have yet to come across an agent whose output doesn't require quite a lot of planning, back and forth, and code review. I'm still thinking in the long run the main enduring value may be that these LLMs are a "conversational UI" to something, not that they're going to be like little mini-employees.
Never used headphones - if the environment is too loud, make it quieter. I once moved into a new office area that had a dot-matrix printer that "logged", in the worst sense of the word (how could you find any access on such a giant printout), every door open/close in the block. It was beyond annoying (ever heard a DM printer? only thing worse is a daisy wheel) so I simply unplugged it, took out the ink ribbon and twisted off the print head. It was never replaced, because as is very often the case nobody ever used the "reports" it produced.
But LLM prompting requires you to constantly engage with language processing to summarize and review the problem.
My inner dialogue is always chatty; that doesn't stop when I enter a flow state. It just becomes far more laser focused and far less distracted. LLMs help to maintain the flow because I'm able to use it to automate anything I don't care about (e.g. config files) and troubleshoot with me quickly to keep the flow going.
To me, flow is a mental analogue to the physical experience of peak athletic output. E.g. when you are are at or near your maximum cardiovascular throughput and everything is going to training and plan. It's not a perfect dichotomy. After all, athletics also involve a lot of mental effort, and they have more metabolic side-effects. I've never heard of anybody hitting their lactate threshold from intense thinking...
My point is that the peak mental output could be applied to many different modes of thought, just as your cardiovascular capacity can be applied to many different sports activities. A lot of analogies I hear seem too narrow, like they only accept one thinking task as flow state.
I also don't think it is easy to describe flow in terms of attention or focus. I think one can be in a flow state with a task that involves breadth or depth of attention. But, I do suspect there is some kind of fixed sum aspect to it. Being at peak flow is a kind of prioritization and tradeoff, where irrelevant cognitive tasks get excluded to devote more resources to the main task.
A person flowing on a deep task may seem to have a blindness to things outside their narrow focus. But I think others can flow in a way that lets them juggle many things, but instead having a blindness to the depth of some issues. Sometimes, I think many contemporary tech debates, including experience of AI tech, are due to different dispositions on this spectrum...
It helps that I don't outsource huge tasks to the LLM, because then I lose track of what's happening and what needs to be done. I just code the fun part, then ask the LLM to do the parts that I find boring (like updating all 2000 usages of a certain function I just changed).
Standing desk, while it's working I do a couple squats or pushups or just wander around the house to stretch my legs. Much more enjoyable than sitting at my desk, hands on keyboard, all day long. And taking my eyes off the screen also makes it easier to think about the next thing.
Moving around does help, but even so, the mental fatigue is real!
LLMs force me to context switch all the time.
I suffered from the problems you describe, grabbing a browser window or my phone which would usually take my attention much longer than the task and it left me burned out at the end of the day.
There are some helper tools, like blocking "interesting" pages (like HN, reddit) on the browser, putting the phone in the bag at the end of the room or using a pomodoro timer so sequence proper breaks. But at the end the only thing that really helped is getting into meditation: I try to use these little interruptions of flow as a opportunity to bore myself. Try to reframe boredom from being an annoyance that needs to be fought to a chance to relax your brain for a couple of seconds and refocus.
The want to grab the phone is hard at the start, but it gets better very soon when you manage to push through the discomfort in the first days.
EDIT: I wanted to add that I think it's a great time to get back to it because this mental fatigue has been leading me to migrate to more analog tools, like pen and paper for journaling and ditching my smartwatch for analog ones.
Today Anthropic started offering 3x(?) Opus speed at 5x cost as well.
Probably more stress if I’m on battery and don’t want the laptop to sleep or WiFi to get interrupted.
I try to fix it by having multiple opencode instances running on multiple issues from different projects at the same time, but it feels like I'm just herding robots.
Maybe I'm ready for gastown..
Edit: Looks like plenty of people have observed this: https://www.reddit.com/r/xkcd/comments/12dpnlk/compiling_upd...
(Also, this only applies if what you're working on happens to be easily parallelizable _and_ you're part of the extremely privileged subset of SV software engineers. Try getting two Android Studios/XCodes/Clang builds in parallel without 128GB of RAM, see what happens).
But yeah improving build speed & parallel running I think are one of the biggest advances devs can do to speed up development time in the AI age. With native apps that can be a challenge. I restructured a react native project to make it faster to iterate, but I have a feeling you might not be fond of rn.
Going back from writing an email to working, versus going back from email to reviewing someone else's work feels harder.
e.g. managing systems, initiating backups, thinking about how I'll automate my backups, etc.
The list of things I haven't automated is getting shorter, and having LLMs generate something I'm happy to hand the work to has been a big part of it.
I don’t just give somebody a bit’s ticket a let the go. I give them a ticket but have to hover over their shoulder and nitpick their design choices.
Tell them “you should use a different name for that new class”, “that function should actually be a method on this other thing”, etc
The output is still small and I can review it. I can switch tasks, however if it's my primary effort for the day I don't like stepping away for an hour to do something else.
But the cycle is longer. When you help a person they don’t come back to you 4-20 minutes later.
I also only review PRs at specific times a day, because that’s more cognitively intensive and switching in and out pretty much ensures you’ll do it badly.
Either way, I’m really starting to think agentic as designed is a deeply flawed workflow. The future could be small, fast models that finish pseudo code and look stuff up to aide focus. Anthropic’s own research seems to support this.
> 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
Those Show HN posts aren't the insane part. Insane part is like:
> Thank you, OpenClaw. Thank you, AGI—for me, it’s already here.
> If you haven't spent at least $1,000 on tokens today per human engineer, your software factory has room for improvement
> Code must not be reviewed by humans
> Following this hypothesis, what C did to assembler, what Java did to C, what Javascript/Python/Perl did to Java, now LLM agents are doing to all programming languages.
(All quoted from actual homepage posts today. Fun game: guess which quote is from which article)
The real AI fatigue is the constant background irritation I have when interacting with LLMs.
"You're not imagining it" "You're not crazy" "You're absolutely right!" "Your right to push back on this" "Here's the no fluff, correct, non-reddit answer"
Perhaps the author just likes to write? I've only just recently started blogging more, but I unexpectedly started to really enjoy writing and am hoping to have my posts be more of a "story". Different people have different writing styles. It's not a problem, it's just that you prefer reading posts that are straight to the point.
Agree. The article could have been summarized into a few paragraphs. Instead, we get unnecessary verbiage that goes on and on in an AI generated frenzy. Like the "organic" label on food items, I can foresee labels on content denoting the kind of human generating the content: "suburbs-raised" "free-lancer" etc.
Funny, I don't associate that with AI. I associate it with having to write papers of a specific length in high school. (Though at least those were usually numbers of pages, so you could get a little juice from tweaking margins, line spacing and font size.)
Too bad we didn't have more laconic, interesting books to feed in?
> Time-boxing AI sessions.
Unless you are a full-time vibe coder, you already wouldn't be using AI all the time. But time boxing it feels artificial, if it's able to make good and real progress (not unmaintainable slop).
> Separating AI time from thinking time.
My usage of AI involves doing a lot of thinking, either collaboratively within a chat, or by myself while it's doing some agentic loop.
> Accepting 70% from AI.
This is a confusing statement. 70% what? What does 70% usable even mean? If it means around 70% of features work and other 30% is broken, perhaps AI shouldn't be used for those 30% in the first place.
> Being strategic about the hype cycle.
Hype cycles have always been a thing. It's good for mind in general to avoid them.
> Logging where AI helps and where it doesn't.
I do most of this logging in my agent md files instead of a separate log. Also after a bit my memory picks it up really quickly what AI can do and what it can't. I assume this is a natural process for many fellow engineers.
> Not reviewing everything AI produces.
If you are shipping in an insane speed, this is just an expected outcome, not an advice you can follow.
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.
My problem is - before, I'd get ideas, start something, and it would either become immediately obvious it wouldn't be worth the time, or immediately obvious that it wouldn't turn out well / how I thought.
Now, the problem is, everything starts off so incredibly well and goes smoothly... Until it doesn't.
Now I have an idea and jot it down in the Claude Code tab on my iPhone... and a couple of minutes later the idea is software, and now I have another half-baked project to feel guilty about for the rest of time.
(just joking, your posts are great, Simon!)
The larger often half-baked projects will flail like they always have. People will get tired of bothering to attempt these. Oh look you created a big bloated pile of garbage that nobody will ever use. And of course there will be rare exceptions, some group of N people will work together to vibe code a clone of a billion dollar business and it'll actually start taking off and that'll garner a lot of attention. It'll remain forever extremely difficult to get users to a service. And if app & website creation scales up in volume due to simplicity of creation, the attention economy problem will only get more intense (neutralizing most of the benefits of the LLMs as an advantage).
The smaller, quasi micro projects used to more immediately solve narrow problems will thrive in a huge way, resulting in tangible productivity gains, and there will be a zillion of these, both at home and within businesses of all sizes.
Totally my experience too. One last little thing to make it perfect or something that I decide would be "nice to have" ends up taking so much time in total. Luckily now I can access the same agent session on my phone mobile browser too so I can keep an eye on things even in bed. (Joke but not joke :D)
I don’t think I agree. How can something be both “usually not a bottleneck” that usually “takes a significant amount of time” ?
> Now we get to spend more time on the real bottlenecks. Gathering requirements from end users, deciding what should be built, etc.
Sounds like you might really enjoy a PM role. Either way, LLM or not, whatever gets written up and presented will have a lot of focus on a bike shed or will make the end user realize allllll the other things they want added/changed, so the requirements change, the priorities change…
So now we just don’t get to do the interesting part… engineer things.
If I wanted to be a PM I’d do that.
Some day it'll handle that, but for now it's very bound to make silly decisions that you need to be on top of, especially as those compound in a large scale system.
I dont understand what you dont understand. Is everything that takes a significant amount of time necessarily a bottleneck? That seems implied by you but makes no logical sense.
The funnel into the programming work is often more difficult/time consuming/resource intensive than the programming.
Also, sometimes its not as costly but should be. And insufficient time and resources were spent up front which caused the coding portion to take a lot longer than it should. In which case the programming time may appear to be the bottleneck but it was still really the funnel leading into it.
> Sounds like you might really enjoy a PM role
Enjoyment isn't really a factor in terms of what work needs to be done. And designing technical features isnt really a PM responsibility.
It reminds me of why people wanted financial markets to be 24/7.
We as a society should probably take a look at that otherwise it may lead to burnout in a not so small percentage of people
It is not prompting, it is the constant feeling that you always have to be "on."
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.
Oh how I'd love to just use an old android with graphene os and work half the time. Unfortunately the math doesn't work
I might keep a tablet or old phone with no service so that I can still do email.
Some people tried that a bit and they had to retreat back to the usual connected life. What happens is, that old non-digital disconnected world is no longer there waiting for you. It may pretend to be the old world you desired, but it is looking at you and judging you. You become an animal in a zoo, instead of an anonymous part of the old-time world.
https://scienceintegritydigest.com/2024/02/15/the-rat-with-t...
I've started doing it now, still needs to work on it. Thanks for the tip though, i hope it is working well for you!!
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
But now, I can't trust any of the models to be that reliable. I can't delegate that responsibility. And since context and prompting is such a fickle thing, I can't really trust any of them to learn from their mistakes, either.
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.
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.
Do you hold the dice accountable when you lose at the craps table?
I would imagine instead companies will end up sleeping walking into this scenario until catastrophy hits.
The difference is that we as humans are held accountable for our non-determinism.
The consequences of our actions have real world implications on our lives.
My other comments probably aren't any better, but those escape my notice!
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.
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?
> It's knowing when to stop.
99% of gamblers stop right before they hit it big.
That's the way society is set up.
That's the sentiment you don't get.
Edit: haha, I'll repeat an earlier comment! Nothing can fly on the moon.
But with “AI” the gain is more code getting generated faster. That is the dumbest possible way to measure productivity in software development. Remember, code is a liability. Pumping out 10x the amount of code is not 10x productivity.
Managing people has always been emotionally and psychologically exhausting.
Managing AI entities can be even more taxing. They're not human beings.
> 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.
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.
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
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 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?
Employers expect more from each employee, because, well, AI is helping them, right?
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 also don't understand why you assume what the AI generates is more readable by AI than human generated code.
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 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.
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.
You're an engineer, not a manager, or a chef, or anything else. Nothing you do needs to be done Monday-Friday between the hours of 8 and 5 (except for meetings). Sometimes it's better if you don't do that, actually. If your work doesn't understand that, they suck and you should leave.
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.
Prompting isn't a real skill and you're not learning anything.
"Claude 4.5 Sonnet operator" is not a job description.
You’ve been left behind and at this very late point in the game i feel no obligation to even try to convince you.
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.
AI is not good for human health - we have it here.
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.
> 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.
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.
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.
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.
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.
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.
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.
> Distill - deterministic context deduplication for LLMs. No LLM calls, no embeddings, no probabilistic heuristics. Pure algorithms that clean your context in ~12ms.
I simply do not believe that this is human-generated framing. Maybe you think it said something similar before. But I don't believe that is the case. I am left trying to work out what you meant through the words of something that is trying to interpret your meaning for you.
Use your own words!
I'd rather read the prompt!
Do you find it works well?
With these agents I've found that making the workflows more complicated has severe diminishing returns. And is outright worse in a lot of cases.
The real productivity boost I've found is giving it useful tools.
I'm fatigued by this myth.
We are trained on the other thing: unpredictable user interaction, parallelism, circuit-breaking, etc. That's the bread and butter of engineering (of all kinds, really, not just IT).
The non-deterministic intuition is baked into engineering much more than determinism is.
That's perfectly fine. We are honed for this too.
We don't need to produce exact solutions or answers. We need to make things work despite the presence of chaos. That is our job and we're good at it.
Product managers freak out when someone says "I don't know how much time it will take, there are too many variables!". CFOs freak out when someone says "we don't know how much it will cost". Those folk want exact, predictable outcomes.
Engineers don't, we always dealt with unpredictable chaotic things. We're just fine.
Just a few days ago: https://news.ycombinator.com/item?id=46885530
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.
Find the last log entries for the system before the reboot; if they point to a specific application, look at its logs, otherwise just check all of them around that time, filtering by log level. Check metrics as well - did the application[s] stop handling requests prior to the restart (keeping in mind that metrics are aggregations), or was it fine up until it wasn’t?
If there are no smoking guns, a hardware issue is possible, in which case any decent server should have logged that.
> I just want to know what to do to fix it if it can be fixed.
Serious question: how do you plan on training juniors if troubleshooting consists of asking an AI what to do?
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".
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.
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.
My comment is relevant because I’m pointing out, like the article does, that AI isn’t turning out to be anywhere near as useful and low-friction as it has been promised. Hence, the fatigue.
Your comment is the one that contributes nothing.
> 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.