Hacker News Reader

Comment by pastel8739 | Hacker News Reader

What do you suggest these people do instead? I’ve been frustrated by this recently: I pivoted to a new subfield and am working on stuff that I would love to dive deep into and really learn what is going on so I can speak intelligently about the tradeoffs etc. But that would take a long time, and I have tasks that I should get done. So I have found myself working with a pretty vague understanding that, when pressed by coworkers, quickly finds its limits. Then I go back and try to deepen my understanding enough to cover those limits. But because I’m not working with each detail of the problem, implementing line by line with time to think about what’s happening, there just isn’t time for me to learn this unfamiliar topic. But I would love to, and I would enjoy the work much more if I could. So what am I supposed to do?

View on HN

I'm not GP, but I've been experiencing this too. All my coworkers are in the same boat though, so we don't really have anyone with the deep understanding. Our approach (which has been working pretty well, we've solved a lot of problems and learned some along the way) has been to use AI as an informer who also points us to sources (like documentation, github issues, etc) where we can then read up on something the AI has pointed us at. We try to time box things a bit to prevent going down the rabbit hole, so we don't always get to exhaust our curiosity, but we're continually gaining that knowledge and pressing forward. Most recent example is tuning the kernel settings and our app on our prod machines to behave better for WebRTC packet handling/forwarding. AI for things like ffmpeg has been a god send when nobody on the team is an ffmpeg expert.

I've also had success just asking claude to write documentation on a system or subsystem or module, etc, and reading that. I then sometimes have it turn that into an svg diagram or something visual that often helps understand things. That domain-specific knowledge is hard to gain though, so not a silver bullet by any stretch.

> All my coworkers are in the same boat though

That changes the picture a lot though because OP's whole point was the impedance mismatch between colleagues.

If you're all self aware that you're all winging it, and learning together, that seems a lot more of a healthier culture.

I have a very similar experience, and am very frustrated too.

I could (and do) lay blame on this new culture that "in the age of AI" things are there to be done, not learned, and doing is cheap (even if badly).

But I'm also particularly frustrated with myself for going along with it, and becoming that person.

I've never been that person. So on the one hand I feel I pressure to adapt or die. On the other hand adapting is dying, in a sense.

I don't think you can do much about it if you're hoping to hide that you have been in the domain for less than a year. You're going to have to admit your inexperience and ask questions of your more experienced coworkers and try to stretch your common sense (e.g. devise internal consistency checks).

Don't just blindly pass around LLM generated content that you don't understand. I think it's important to consider that you are supposed to be more than just a meat proxy for the model. You don't want people to start associating you with AI slop.

Read some books on the subject and within a year in this new domain you'll be much better. Did you forget your whole life before the last 3 years?

Yes, certainly, in a year I’ll be better. But in the meantime…? 3 years ago it would be understandable for me to take my time with the tasks I’m doing because they are complex. Now it would be unreasonable for me to spend enough time to understand the nuances.

Reply on news.ycombinator.com