alt Hacker NewsI don't know what to think about comments like this. So many of them come from accounts that are days or at most weeks old. I don't know if this is astroturfing, or you really are just a new account and this is your experience.
As somebody who has been coding for just shy of 40 years and has gone through the actual pain on learning to run a high level and productive dev team, your experience does not match mine. Even great devs will forget some of the basics and make mistakes and I wish every junior (hell even seniors) were as effective as the LLMs are turning out to be. Put the LLM in the hands of a seasoned engineer who also has the skills to manage projects and mentor junior devs and you have a powerful accelerator. I'm seeing the outcome of that every day on my team. The velocity is up AND the quality is up.
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Who would I possibly be astroturfing for? The entire industry is all-in on LLMs.
Agreed.
It's clear to me as a more seasoned engineer that I can prompt the LLM to do what I want (more or less) and it will catch generally small errors in my approach before I spend time trying them. I don't often feel like I ended up in a different place than I would have on my own. I just ended up there faster, making fewer concessions along the way.
I do worry I'll become lazy and spoiled. And then lose access to the LLM and feel crippled. That's concerning. I also worry that others aren't reading the patches the AI generates like I am before opening PRs, which is also concerning.
This is a very reasonable comment. IMO it's a falacy to take into consideration the age of an account especially when it is subjective experience.
> The velocity is up AND the quality is up.
This is not my experience on a team of experienced SWEs working on a product worth 100m/year.
Agents are a great search engine for a codebase and really nice for debugging but anytime we have it write feature code it makes too many mistakes. We end up spending more time tuning the process than it takes to just write the code AND you are trading human context with agent context that gets wiped.