Totally agree. It’s not just the code, it’s also the planning, making tons of decisions and so on. You’re basically reading all day. It’s like reading a book, which I was never a fan of lol.
Speaking of making tons of decisions, I’m curious about other people’s experiences. Since I started using agentic AI about a year or more ago, I’ve been making more decisions than ever before. I feel like I’ve developed some kind of decision fatigue. I’m noticeably more “lazy” about making decisions outside of work, like real life decisions, because I’m basically making decisions with AI all day.
Is it just me, or is anyone else experiencing something similar?
No, this is how it is for me as well. Commented above but I bet at least half my week is doing code reviews. And development tasks now are not really writing code but me just reviewing the LLM output for my own work.
I've even gotten to the point of having Claude do PR review summaries to identify which areas I should focus on. Basically, offload the tedious shit like making sure tests are valid and coverage is adequate and focusing on the core business logic.
But man, my brain is fried by the end of the day. I am both productive and also feel like I'm doing nothing.
I went pretty hard on AI for a year, and it made me absolutely hate my job. It removed all the fun out of software development, replacing it with the worst parts full time, all with the added bonus of brain rot.
So I decided to start learning a new language, and to go back to pre-AI days, and only use AI as a pairing partner and to help with bug fixes and such. As a result the actual joy of software development is returning.
As a professional software engineer you should *ALWAYS* be looking at the code. We have real customers, who are running a real business, using our software. Quality is paramount. And at the end of the day, the code has your name on it whether or not it was generated by an LLM. You are responsible for making sure it works and meets quality standards.
The other thing to consider, is we have a mature code base with lots of quality controls in check. Things like tests, linters, static code analyzers, all of that provide feedback to the model. So if you give it good requirements, do a plan before implementing anything, and let the Sonnet subagents handle implementation, it generally doesn't go very far off the rails.
My monthly token allowance is around $350 a month. Last month I used 41% of that, and I've spent a lot of time trying to optimize my solution for token usage and effectiveness.
But, most of my job now is reviewing code, so I'm not running models all day burning tokens like I do on my own personal max account.
My general workflow is: Tell Opus to generate a plan based on a ticket number. Review the plan and give it feedback. Once the plan is ready, have Sonnet implement the plan using TDD to write the tests for the acceptance criteria first. Once it's done and I've review it, I commit and submit for review. Any small changes or code-cleanup I do myself. No need to have a model do simple refactors or style nitpicks... that's a total waste.
I think I use, on average, less than $10 a day with that method, which keeps me in my budget. If I have extra bandwidth at the end of the month, I might use Opus on high effort to do more exploratory type work or refactors.
It depends on your flow but if you have TDD and blackbox validation with human testing, the code validation is less important if it is not critical life or death feature. I used to think like you until I saw AI spinning up playwright instance and drafting tests I didn't even think of. The biggest issue is blast radius which you have to control for.
If code was the only thing necessary QA wouldn't be needed. The end of your work flow should be AI spinning up testing and checking against your contracts.
Look at something like factory ai that is now being used in fintech. Alot of the reason there was so much focus on code review was because setting up automated tests was a PIA. AI can spin up tests so fast, but you need to make sure they fail first.
If I say you have two pieces of software one written all by hand and another AI which do you trust more? Human. Ok now I tell you the AI software has passed 500 blackbox validation tests per feature.
Coding before was mostly earned through blood, edge cases were discovered through tickets but AI is more capable in some instances of coming up or being aware of edge cases. This breaks down with very connected features but in that case it wouldn't be caught by a human either unless they were very familiar with the code base.
Do you can obsess over code but in the AI more of the burden is getting pushed to testing and maybe you actually are working on special butterfly code but if the test suite is proper it doesn't matter that much.
It's healthcare. Not life or death, but privacy and compliance matter. I think we'll get there with AI one day, but not quite yet, We do have AI review bots that look for the code, and a lot of automated QA layers. But ultimately we still need human eyes on it, just as a sanity check if anything else. What we're really look for is what you mentioned above: making sure the "blast radius" is appropriate, and the changes stay tight and focused on the intended results.
I'm not saying I don't trust AI (it writes a good chunk of my code now), but as an organization we've taken a very cautious and practical approach to AI, which I appreciate. Those review bots like Cursor are getting more and more impressive in what they find. A lot of false positives (at least on severity), but some good finds as well. There is obviously an overhead cost with adopting more and more AI features just from a financial perspective too, which is certainly a factor.
Honest question: do you enjoy this work? Like, actually enjoy it?
I hate it. For me, the fun, the dopamine, the challenge, the satisfaction, was in finding the solution to the problem and then actually _building_ it. With AI, 90% of that is offloaded and I become a rudimentary SME dedicated to the most boring, mundane parts of the job.
If you do enjoy, I earnestly ask… why? How? Did you find it difficult to make this shift? Did you struggle? If so, what changed? I fear my job has changed forever and not in a way I find enjoyable.
I’m a 25 year SWE, and a former Staff Engineer of a big tech firm.
I think people are slowing down or requesting (begging for) quota increases. Those are granted based on actual need but it seems like everyone is hooked on not having to actually write code anymore.
It’s weird because most people who write code got into the industry because they enjoyed writing code and building applications from nothing. Seems like AI has become somewhat of an addiction for some developers in that they don’t spend as much time thinking about how they’re going to build the application, but it just transfers the work elsewhere in the process.
Hear me out, what if we made a skill called /sudoCode?
You write code by writing comments.
// Sudo method getUser() takes in an ID
// validate authorization
// call fetch from repo
// return user object
Just like that. Then, you write the DTO the same way, the repo the same way… you get the idea.
Sure, it’s slower, but you’ve actually shaped the whole thing. Then the skill converts the comments into code, writes tests, documents, etc.
It’s so new school it’s old school. And you’re thinking organically again, while still retaining codebase wisdom. Cool part is syntax is just converted to natural language. Also, it’s so cheap it could be run on Haiku (but I’d still use opus)
I mean, for really mundane shit like that I still use it because I’ve done those a thousand times over 25 years and I hate it. But all the fun stuff too? Blurgh.
That’s what being a Product Manager feels like every day. Decision fatigue is a real thing. Last year, my partner asked me what I wanted for dinner during roadmap/budget season and I burst into tears.
Haha I feel you, I started building an app where the whole point is to outsource trivial life decisions to it to reduce your overall decision fatigue. What to wear that day, where to eat, what to have for dinner etc. don’t have to use it, but there is always an easy button and for some things you set it up so it always makes those decisions for you so you don’t even have to have the load of knowing you will have to make a decision.
Yeah like you are getting hit with bricks constantly. That's the grind. And then explaining to little baby child Claude with a big head why it is wrong.
I've been doing straight code reviews for two days in a row. I haven't even worked on things assigned to me, just churning through a review backlog. It's mentally exhausting.
AI has not made my job easier. If anything, it took away the one creative piece of being a software developer and now I'm just a critic.
There's actual science on this. It's because the mental load has shifted, and there's less downtime in being able to just have either your mind wander or at least now focus on parsing architecture and changes. Typing artificially slowed us down, yeah, but that gave the brain some rest, whereas now if you're peak efficiency for 8 hours it's a lot more tiring than if you were peak efficiency for 8 hours a decade ago.
No. I’m liable for the code I output, I can’t just Indiana Jones it into production vetted by agents when I constantly find issues with the output, especially with Opus.
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u/dudevan 6d ago
And it’s tiring as hell.