Subscribed for work, but using it mostly for one-shot utilities and fixes, very infrequently.
I'm also running local models on my gaming laptop, but just out of curiosity, for testing how far local models are coming along. Despite my negative experiences (below) I still think the technology is cool, and it's even cooler I can run it on my not very cutting edge laptop. I give local models a set of tasks and see how far along each new one comes.
Rant:
For work, I've mostly given up on using LLMs for large features, in all cases I've tried in the last 2 years, the time it takes to clean up their output is about the same I would have spent writing and debugging the feature myself. There's only a single major feature I've shipped that was mostly written by an LLM, and that was back in May. All other major tasks I've tried, even somewhat trivial ones, led to unusable code, filled with comment slop and workarounds, and hidden bugs.
This is probably due to the sheer amount of legacy code our app has, but even trying to develop more or less self-contained components was very difficult.
I do use LLMs daily, but mostly through a chat interface, as a somewhat faster alternative to web search and as an alternative to copying and pasting from StackOverflow for minor problems.
Most of my current job is now going over PRs submitted by my team members, that are mostly all AI-generated, and cleaning them up. The amount of junk inserted into the code by current SOTA models is astonishing, especially during rounds of bug fixes, probably due to context rot.
Hundreds of useless variables and small wrapper functions on top of wrapper functions. Hundreds of comments that are essentially word salad, or worse, the LLM talking to the user through the comment instead of through the chat, essentially saying in a comment "I was a good subservient model, and did what you wanted! This function now returns an error, see?". Repeated hundreds of times. Not to mention actual bugs that the inane and lazy unit tests it adds never catch.
I'm far less lenient on AI output than on if the same dev wrote the code herself.
Thankfully, people in my team cooperate with me and fix my comments, and so far we have no pressure from management to move faster.
/Rant
Nitpick: Title seems to be missing a word: "Are you USING a subscribed LLM or a locally open-source model". Or else it's targeting LLM which are reading this forum. If so, there aren't any responding, all responses seem to be from humans...
I'm not, but I find it interesting you thought I am.
What made you think so, if I may ask? The rant? The amount of text I wrote?
Feel free to look at my own posting history. You'll see that I was posting some very verbose comments here even before the first LLMs appeared on the scene... A sign of autism maybe, but no, not a bot.
EDIT: Removed what could be interpreted as a personal attack.
I personally review most of the code written by my team without using an LLM.
Just today I reviewed a patch made by a teammate using Claude for a not very significant bug, where in addition to fixing it (in a very roundabout way), it introduced 2 new very subtle bugs, and refactored a large portion of another function that was unrelated to the code, and made several observations and comments which were subtly wrong and out of touch with the rest of the code.
I ended up rejecting the PR and writing my own very small local patch for the bug.
Other people in the team use Claude to help them review my own PRs, and it sometimes finds minor issues, although there was only a single time it found a major issue.
My own use of LLMs is mostly to develop large features, which I then thoroughly review myself.
Funny, I'm just reading War and Peace myself (the Anthony Briggs translation) and having the same reaction, gushing occasionally to people I know how approachable it is, and how darkly funny and modern it feels. Well, at least after passing through the first ~200 pages which are a slog. I didn't find even Tolstoy's historical musings boring, although he tends to repeat himself. And I usually suck at names, but the main characters are done so well I find them easy to remember. There aren't that many important ones despite how it seems at the start. It also serves as a fascinating peek into the daily lives of Russians of all stripes in the early 1800s.
I also had the same reaction to Crime and Punishment as the OP did.
Read those first 200 pages 10x could never get past it. 300 characters with names that I’ll never remember, some woman and her son, a general or something. A guy that keeps saying “Capital!”, standing around at parties.
I’m sure it’s good but I don’t think I have it in me to try again.
I swear it took me six retries to make it past the start. But if you have six hours the BBC adaptation is pretty good IMHO and captures many of the essentials of the book if not all the details. The show made me cry and the book did not have the same effect but maybe that was because it focused on certain aspects. I particularly remember the combat scenes in the book would have been difficult to match - the prose capturing the chaos and randomness of brutality in the neighborhood of D Day landing in Saving Private Ryan but with horse cavalry charges and cannon fire.
I listened to the audio book version of War and Peace. I think it was something like 25-30 hours. The audio format helped keep the pace going and also it helped with the names. Although for some things, the audio format made it harder to look up in the dictionary, like I kept hearing agitant instead of adjutant, so that part didn't make sense in a lot of the military scenes. I agree with the parent that the book was very engaging, parts even felt like I was watching a movie, e.g. the drunken party tying a bear to a police officer, the foxhunt scene, the duel, the battles like when Petya gets shot, and the burning of Moscow. I even liked the abstract ending when Tolstoy relates human history to calculus so that each individual person has an infinitesimal but real contribution to history.
Ha, I'm a gardener then, on my 15th year of maintenance. So halfway there according to you. Slowly, very slowly, fixing the thousands of bugs the rockstar left behind 15 years ago.
It's easy to look at a newly made garden, its flowers all freshly planted and its paths all neatly laid out, and think it finished, but once you see one that's been carefully maintained for decades and how its plants have matured and grown together and how the steps have been worn by human feet, it's clear the project is merely off to a good start.
This comment made me imagine what would the guy maintaining my first deployed project at my first company thinks about me. Never had this thought ever cross my mind.
I work on an ancient codebase, C# and C++ code spanning over 3 major repos and 5 other minor ones. I'm senior engineer and tech lead of my team, but I also do a lot of actual coding and code reviews. It's a somewhat critical internal infra.
I'm intimately familiar with most of the code.
I've become somewhat addicted to using coding agents, in the sense I've felt I can finally realize a lot of fantasies about code cleanup and modernization I've had during the decade, and also fulfill user requests, without spending a lot of time writing code and debugging. During the last few months I've been spending my weekends prompting and learning the ropes. I've been using GPT 5.x and GPT 4 before that.
I've tried both giving it big cleanup tasks, and big design tasks. It was ok but mentally very exhausting, especially as it tends to stick to my original prompt which included a lot of known unknowns, even after I told it I've settled on a design decision, and then I have to go over its generated code line-by-line and verify that earlier decisions I had already rejected aren't slipping into the code again. In some instances I've had to tell it again and again that the code it's working on is greenfield and no backwards compatibility should be kept. In other instances I had to tell it that it shouldn't touch public API.
Also, a lot of things which I take for granted aren't done, such as writing detailed comments above each piece of code that is due to a design constraint or an obscure legacy reason. Even though I explicitly prompt it to do so.
Hand-holding it is a chore. It's like coaching a junior dev. This is on top of me having 4 actual real-life junior devs sending me PRs to review each week. It's mentally exhausting. At least I know it won't take offense when I'm belittling its overly complicated code and bad design decision (which I NEVER do when reviewing PRs for the actual junior devs, so in this sense I get something to throw my aggression against).
I have tried using it to make 3 big tasks in the last 5 months. I have shelved the first one (modernizing an ancient codebase written more than 20 years ago), as it still doesn't work even after spending ~week on it, and I can't spare any more time. The second one (getting another huge C# codebase to stop rebuilding the world on every compilation) seemed promising and in fact did work, but I ended up shelving it after discovering its solution broke auto-complete in Visual Studio. A MS bug, but still.
The 3rd big task is actually a user-facing one, involving a new file format, a managed reader and a backend writer. I gave it a more-or-less detailed design document. It went pretty ok, especially after I've made the jump to GPT 5.2 and now 5.4. Both of them still tended to hallunicate too much when the code size passed a certain threshold.
I don't use it for bug fixing or small features, since it requires a lot of explaining, and not worth it. Our system has a ton of legacy requirement and backwards compatibility guarantees that would take many days to specify properly.
I've become disillusioned last week. It's all for the best. Now that my addiction has lessened maybe I can have my weekends back.
I'm also running local models on my gaming laptop, but just out of curiosity, for testing how far local models are coming along. Despite my negative experiences (below) I still think the technology is cool, and it's even cooler I can run it on my not very cutting edge laptop. I give local models a set of tasks and see how far along each new one comes.
Rant:
For work, I've mostly given up on using LLMs for large features, in all cases I've tried in the last 2 years, the time it takes to clean up their output is about the same I would have spent writing and debugging the feature myself. There's only a single major feature I've shipped that was mostly written by an LLM, and that was back in May. All other major tasks I've tried, even somewhat trivial ones, led to unusable code, filled with comment slop and workarounds, and hidden bugs.
This is probably due to the sheer amount of legacy code our app has, but even trying to develop more or less self-contained components was very difficult.
I do use LLMs daily, but mostly through a chat interface, as a somewhat faster alternative to web search and as an alternative to copying and pasting from StackOverflow for minor problems.
Most of my current job is now going over PRs submitted by my team members, that are mostly all AI-generated, and cleaning them up. The amount of junk inserted into the code by current SOTA models is astonishing, especially during rounds of bug fixes, probably due to context rot. Hundreds of useless variables and small wrapper functions on top of wrapper functions. Hundreds of comments that are essentially word salad, or worse, the LLM talking to the user through the comment instead of through the chat, essentially saying in a comment "I was a good subservient model, and did what you wanted! This function now returns an error, see?". Repeated hundreds of times. Not to mention actual bugs that the inane and lazy unit tests it adds never catch.
I'm far less lenient on AI output than on if the same dev wrote the code herself. Thankfully, people in my team cooperate with me and fix my comments, and so far we have no pressure from management to move faster.
/Rant
Nitpick: Title seems to be missing a word: "Are you USING a subscribed LLM or a locally open-source model". Or else it's targeting LLM which are reading this forum. If so, there aren't any responding, all responses seem to be from humans...