Ask HN: By what percentage has AI changed your output as a software engineer?

- It sometimes generate decent examples of linux kernel api usage for modules, which saves a lot of time digging in the limited documentation. But most of the time it will mix deprecated a new version of the api and it will very likely have very suboptimal and/buggy choices.

- for embedded C, it won't be able to work within the constraints of a very specific project (e.g. using obscure or custom hal), but for generic C or rtos applications it can generate between decent and half decent suggestions.

- almost never seen it generate decent verilog

I was very very keen on using this tech when it just emerged and was almost addicted to it.

The feeling I was gaining was akin to scrolling one of them feed-generating apps with cat videos, or eating fast food - quick and empty joy and excitement without lasting fulfilling effect.

After months, or maybe a year of using LLMs - I realized that neither I am faster in delivering the final desired quality of the product, nor am I satisfied with where I am professionally. I lose my human skills and I forget how to get joy out of my work (and I enjoy making them computers work). I noticed how I grew negligent to the results of my work, felt disconnected from and disconcerted by it, and it was alarming sign.

Anybody who worked anywhere for long enough knows that unhappy, robbed of joy people - produce worse results.

Said that, I realized loud and clear that writing code, developing systems, is something that I want to experience joy of personally, I want my brain struggle, sweat and click through most of the parts of it, and that parts of the work that I don't enjoy doing and can be shamelessly offloaded to LLM, are, in fact, quite minimal.

On top of it, while using the LLMs (and boy was I using all of it! Sub-agents, skills, tasks! Hour-long planning-prompting exercises!), I was still noticing that when it comes to "write code" tasks - LLMs were only better and faster than me in delivering quality work when the task at hand was not my primary skill, something that I'd be below average (in my case, web-development or app development, any front-end work). And, given, that I was employed to exercise my main skill rather than secondary skills, it's almost never the case that LLMs were boosting my productivity, they required long time of baby-sitting before I'd almost certainly give up and do all of the work myself.

Admittedly, LLMs are outstanding study partners that can give pointers to where to start and what structure to stick to when learning about new project, technology, problem domain, or generating flash cards based on materials one wants to study, and that's a use of LLM that I'd probably not give up. My speed of learning new things with some LLM assist is boosted greatly, so from this perspective, one can say that LLM makes me better developer after all.

I work on a code base that is easily over 1 million lines. It has had dozens of developers work on it over the last 15 to 20 years. Trying to follow the convention for the portion of the code base that I work on alone is a pain. I’ve been working on it for about seven years and I still had to ask questions.

So I would say that I work on a could base with a high level of drudgery. Having an all knowing AI companion has taken an awful lot of the stress out of every aspect.

Even the very best developer I’ve ever worked with can’t match me when I’m using AI to augment my work. For most development tasks, being the best of the best no longer matters. But in a strange way, you still need the exact same analytical mindset because now it’s all about prompts. And it definitely does not negate the need for a developer.

Writing your own code is essentially just an exercise in nostalgia at this point. Or someone who prefers to pick seeds out of cotton themselves, instead of using a cotton gin.

Or perhaps instead of using voice dictation to write this post, I would write a letter and mail it to Hacker News so that they can publish my comment to the site. That’s how backwards writing code is quickly becoming.

At work, also 2x to 4x.

The numbers would be even higher (4x to 8x) if I didn't spend half the time correcting slop and carefully steering the AI toward the desired solution when it gets sidetracked. But then again, I was also guilty of those things so maybe it's an even score?

Perhaps it's partly psychological in that using it forces me to think through the problems I'm trying to solve differently than before. Perhaps I'm just a mediocre dev and the AI is bringing me up to "slightly above average," but a win is a win and I'll take it.