Same. Plus I have kids and a mortgage. My company just had a 5% layoff and I survived. Seems like it will be the first of many rounds. It's a really stressful time.
To be clear, I'm confident the impact of AI is going to be massive, and that massive impact is already underway rather than years away. But, separate from that, having seen it up close Block was bloated as hell
Yeah. We are coping. Just today, I had a simple bug where the data received was throwing undefined because it was in 2 alternate formats.
I showed ChatGPT(free-tier) the API response and the part of the code reading it, and it fixed it in 5 seconds. Would've been pretty short either way less than 30-40 mins but it's very good for simple tasks like these. The solution is just correct.
Even if they are right about quality, people on here vastly overstate the value of quality. From socks to dishwashers to airfares, slop is a valid product as long as it is cheap. Security from a business perspective has been proven not quite optional, but it is hardly catastrophic if it fails.
I recognize that my experience may not be typical, but I spend the vast majority of my development time improving the quality of the systems I work on, in response to specific customer demands for it. The last time I had multiple consecutive weeks of greenfield development was in 2021.
This thread is a great discussion and I have kept coming back to it over the last couple days to read more of it when I have a chance. I’m kind of disappointed that it artificially ended. I think at some useful comment threshold level you just have to let it go.
>But it shouldn't matter if he gave 5 bullets to Chat gpt that expanded it to a full page with a detailed plan.
The coworker should just give me the five bullet points they put into ChatGPT. I can trivially dump it into ChatGPT or any other LLM myself to turn it into a "plan."
I feel the same way, if all one is doing is feeding stuff into AI without doing any actual work themselves, just include your prompt and workflow into how you got AI to spit this content out, it might be useful for others to learn how to use these LLMs and shows train of thought.
I had a coworker schedule a meeting to discuss a technical design of an upcoming feature, I didn't have much time so I only checked the research doc moments before the meeting, it was 26 pages long with over 70 references, of which about 30+ were reddit links. This wasn't a huge architectural decision so I was dumbfounded, seemed he barely edited the document to his own preferences, the actual meeting was maybe my most awkward meeting I've ever attended as we were expected to weigh in on the options presented but no one had opinions, not even the author, on the whole thing. It was just too much of an AI document to even process.
If ChatGPT can make a good plan for you from 5 bullet points, why was there a ticket for making a plan in the first place? If it makes a bad plan then the coworker submitted a bad plan and there's already avenues for when coworkers do bad work.
How do you know the coworker didn't bully the LLM for 20 minutes to get the desired output? It isn't often trivial to one-shot a task unless it's very basic and you don't care about details.
Asking for the prompt is also far more hostile than your coworker providing LLM-assisted word docs.
Honestly if you have a working relationship/communication norms where that's expected, I agree just send the 5 bullets.
In most of my work contexts, people want more formal documents with clean headings titles, detailed risks even if it's the same risks we've put on every project.
On this topic I think it’s pretty off base to call HN a “well insulated bubble” - AI skepticism and outright hate is pretty common here and AI negative comments often get a lot of support. This thread itself offers plenty of examples.
> there are about 230 billion* links that need visiting
> * Thanks to arkiver on the Archive Team IRC for correcting this number.
Also when running the Warrior project you could see it iterating through the range. I don't have any logs handy since the project is finished but they looked a bit like
https://goo.gl/gEdpoS: 404 Not Found
https://goo.gl/gEdpoT: 404 Not Found
https://goo.gl/gEdpoU: 302 Found -> https://...
https://goo.gl/gEdpoV: 404 Not Found
They are useful for putting URLs in print materials like books. Useful for sharing very long links in IRC and some other text based chat apps (many google maps links would span multiple IRC lines if not shortened, for example). They are good for making more easily scannable QR codes.
The major difference is that in the type of reading Joel Splosky is talking about, you are coming in not knowing the code's intent. It was written by one or more other people at some point in the past, likely with many iterative changes over a period of time. Figuring out the intent in this case is 90%+ of the work. With LLM generated code, you know the intent. You just told the assistant exactly what your intent was. It's much, much easier to read code that you already know the intent of.
reply