Readit News logoReadit News
msvana commented on LLMs work best when the user defines their acceptance criteria first   blog.katanaquant.com/p/yo... · Posted by u/dnw
msvana · 7 days ago
I think there is one problem with defining acceptance criteria first: sometimes you don't know ahead of time what those criteria are. You need to poke around first to figure out what's possible and what matters. And sometimes the criteria are subjective, abstract, and cannot be formally specified.

Of course, this problem is more general than just improving the output of LLM coding tools

msvana commented on Labor market impacts of AI: A new measure and early evidence   anthropic.com/research/la... · Posted by u/jjwiseman
throwaw12 · 9 days ago
People who are saying they're not seeing productivity boost, can you please share where is it failing?

Because, I am terrified by the output I am getting while working on huge legacy codebases, it works. I described one of my workflow changes here: https://news.ycombinator.com/item?id=47271168 but in general compared to old way of working I am saving half of the steps consistently, whether its researching the codebase, or integrating new things, or even making fixes. I have stopped writing code, occasionally I jump into the changes proposed by LLM and make manual edits if it is feasible, otherwise I revert changes and ask it to generate again but based on my learnings from the past rejected output

I am terrified about what's coming

msvana · 9 days ago
I work as an ML engineer/researcher. When I implement a change in an experiment it usually takes at least an hour to get the results. I can use this time to implement a different experiment. Doesn't matter if I do it by hand or if I let an agent do it for me, I have enough time. Code isn't the bottleneck.

I also heard an opinion that since writing code is cheap, people implement things that have no economic value without really thinking it through.

u/msvana

KarmaCake day49August 21, 2023
About
AI and software engineer. Interested in far too many things, including but not limited to AI, software development, economics, philosophy, or psychology.

https://svana.name

View Original