unlike the op, I've been having a wonderful time using claude, both at work and for my own personal projects, so I will share what has worked for me, just in case it resonates with anyone else.
my anecdotal advice is to avoid the entire "agent" temptation, and treat the LLM as a code generator. have a single session running at a time. come up with a plan, iterate on it until you are satisfied, then tell it to execute the plan, and watch it. not necessarily to the extent of reading the scroll (though I sometimes do do that too!) but as it finishes each step look over what it has done, suggest improvements and course corrections, and then let it go on to the next step. at the end you will have a pretty good grasp of the state of the code, and the overall time it will take you isn't really any longer than trying to churn out reams of code and then go through it all at once.
the other option if you want something closer to a one shot workflow is to go into far more detail during the planning stage, have it describe not just architectural details but actual code (if you're a senior engineer especially you probably know what the key pieces of code that will drive a lot of other decisions mechanically are likely to be).
also refactoring is cheaper than it has ever been, if something feels hard to grasp to you stop and work with the LLM until you like the looks of it better.
and again, the key bit is to have one LLM doing one thing at a time, and to stay engaged in the process while it does so.
Pinch to zoom on an early iphone navigating those fixed-width sites worked surprisingly well.
I still prefer it to the responsive pages where stuff moves unpredictably and annoyingly. Before you never had that feeling that the webpage was fighting you.
I sometimes wonder if there is an equivalent loss for this new AI world and one that I've noticed is a kind of sameness that is slowly spreading across the internet.
While I appreciate and agree with the key points of the post, Claude's writing style fingerprints are all over it and I guess it's even more exhausting to read someone's AI written article.
Reminds me of "The Animal is Tired" (2021) (https://www.robinhobb.com/blog/archives/2021-05)
> I felt that one in my bones. I was up until nearly 2am recently, prompting, because I was so close to getting a plan right. Or so I thought. [...] And it's addictive in a way that makes the isolation worse.
Right, it's more like pulling the lever on slot machine. Oooh, 677, bad luck, do a ritual and try again, and maybe this time...
Sure, regular programming also has a feedback loop, but normal errors are--as much as possible and by design--things that happen consistently for reasons, reasons that force you to engage you mind to discern them and then eliminate them (hopefully) forever. Experienced developers don't just try something random, hope it works, and if it works you just dismiss it as unknowable.
> But the bottleneck was never the code. It was always the human attention, the engineering judgment, the ability to hold a coherent vision for a system. We just didn't notice because writing code felt like the hard part.
Unless, perhaps, you were already fatigued trying to deal with many stakeholders who can't agree what the system even is. :p
I feel the opposite, AI is making me less tired at the end of a working day even though I get much more done.
What used to tire me: being forced to have a sharp eye for syntax errors when programming, or simply the effort of all the typing and navigating through source files. Trying to visualize details of the codebase I was changing, while at the same time keeping a high level picture in my head of the feature I was changing.
With AI, I can focus on the high level picture. I can focus on the steps to get there and the steps to verify that it works. I don't have to focus on syntax anymore and there is much less need to visualize large parts of my code base. With AI, work is still tiring but much less, and in a different way.
> He described waking up to thirty PRs every morning, each one pulled overnight by someone's AI, and needing to make snap judgment calls on every single one. The temptation to delegate the review itself to an AI was enormous. But, as he put it: "at that point, what am I still doing here?".
It's so funny and somber to see programmers having an existential crisis when they get a glimpse of what work is like for business managers, the demographics many programmers detest.
I am also guilty of holding the business majors in contempt back in college, and now here I am, doing what they are doing in office in a much more indifferent and unenjoyable manner. At least I don't get into trouble with HR from calling my agents a stupid fuck (yet).
Funny I made some very similar points awhile back in a blog post, thinking of it in terms of mode collapse: https://tonyalicea.dev/blog/single-mode-burnout/
You are right to push back on that.
>It's also, frankly, quite lonely. Programming with an LLM is an intensely solitary activity. > You and the machine, going back and forth, refining and prompting and reviewing.
I just want to comment on this. Maybe im part of some spectrum, but building stuff with AI in that "solitary mode" ive found it really enjoyable. It takes me too the times 30 years ago when I was a 14 year old writing my own games on Basic and C++ with Allegro.
I had nobody but tutorials and books. And the hky of building, compiling and seeing the result for myself was very enticing.
Maybe it's because I found peers my age uninteresting. I lived in a small Mexican town where 14 year olds where thinking in bullying someone, and unfortunately that someone was usually me.
If someone remembers The Hackers Manifesto (The Conscience of a Hacker) I feel that again after so many years, with AI. Edit: particularly this part:
---
I made a discovery today. I found a computer. Wait a second, this is cool. It does what I want it to. If it makes a mistake, it's because I screwed it up. Not because it doesn't like me...
Or feels threatened by me...
Or thinks I'm a smart ass...
Or doesn't like teaching and shouldn't be here...
Shame. There is something thoughtful in the post, I am sure, but I am so tired of reading Claude that I couldn't get myself to engage.
One could hope that the author is making a meta-point.
the irony of an article about human fatigue being detected as AI-written by half the comments is doing more for the argument than the article itself
I don't understand how people are using AI.
A lot of the time, what I want to build, doesn't have a succinct English sentence to describe it. If I describe the user requirement I just get a Fisher-Price toy thing that kind of ignores most of the adjectives and adverbs in my requirement. So I'd have to prompt with a big list of specs and algorithms for the specific thing I want. Then what's the point?
> The honest truth
> That loss is real and it's worth naming
I think I will not heed the first sentence and bear with this. What motivates people to do this? What do they get out of prompting Claude for some vapid "thought piece" and spamming it on the internet?
>When you've earned your opinions about architecture and code quality the hard way, they feel less like textbook rules and more like scar tissue.
I don't think it's common for any compsci programs to (competently at least) teach architecture and code quality.
>The honest truth is that in the last few months, there have been days when I have spent close to two full days writing a plan for an LLM to execute: obsessively clarifying, specifying, re-specifying, only to have it still do something inexplicably stupid.
It's because LLMs are actually taking us back in time to the pre-agile days where there was a career path (architect) that involved almost nothing but painstaking spec authoring and endless meetings to review and course correct the work of the engineers whose job was to implement what you designed as closely as possible. I have to emphasize that this was a different career path than what we think of as a senior engineer today. Not everyone likes this.
It stresses me out for some reason and I'm just working on a hobby project.
Should we not get to work less if Ai is increasing productivity so much while also making us exhausted more quickly?
Perhaps on the way to UBI and the end of labor, we could get a 32 and 24h work wweek with lots more vacation, my hope at least
Relatable.
> with my colleague Douwe
Wait, meltano Douwe? Small world. Glad to see you're doing well. I always liked meltano.
> In an era when anyone can produce reasonable-looking UI
Identical looking slop? Every Claude-based vibe coded app looks identical.
> The fear of skill rot is legitimate. And the fear that if you don't go fast enough you'll be left behind is — while often overstated — not entirely unfounded.
You know what, that's OK. I just hit "OK" on LLM Scala code I _actually_ think is awful. It works. It's probably faster than the "pure" code I'd write by hand. The code I would write - as a FP and Scala/Elm/Haskell/... enjoyer - would actually be maintainable for humans, but LLMs struggle with it. But LLMs writing code for LLMs? Sure, have at it. Objectively lower barrier of entry.
> So if you're feeling overwhelmed, destabilized, simultaneously more productive and less happy, know that you're not alone.
But yes, I am indeed simultaneously more productive and less happy.
https://skaldmaps.com, my little side project, was only possible _because_ I was able to feed my real world knowledge about real estate, combined with GIS and SWE knowledge into various torment nexus... pardon me, LLM prompts.
Since I don't have the _time_ to write boilerplate react code (it's pepper and tomato season in Georgia, which _actually_ brings me joy), telling Claude/Codex/... how to write dbt models saves me time and I objectively get a lot more done, but it's not fun.
I guess that's also why I still enjoy blogging. You can't use LLMs for blogs without people noticing immediately. Shameless plug: https://chollinger.com/blog/
Enjoy my entirely human typos, since that's clearly rare these days.
It's sad to have to unearth the very human line of thought in this article from the very foamy LLM slop.
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> Here's a term for what I think is happening: the human reward function problem. In machine learning, a reward function tells an agent what good looks like. Writing code by hand was never easy, but it was full of small rewards. Solving a problem in your head. Understanding a gnarly bit of logic. Watching the code compile. The feeling of control. LLM-assisted programming has automated much of the work that generated those dopamine hits and replaced it with the cognitive load of review and supervision. The satisfying part shrank. The exhausting part grew. And there are no new rewards to fill the gap.
Say what you will about the Claudisms in this piece, this bit certainly rings true for me. With old school coding, there was always a reward at the end, the harder it was, the more satisfying it felt.
With agentic coding, I really doesn’t feel like that, at least not in the same way. It feels more like continually riding a wave of productivity, where small features or huge features have similar levels of interaction required. And that’s exciting in the beginning but quickly becomes very tiring.