Ask HN: Who has seen productivity increases from AI
I would love examples of positions and industries where AI has been revolutionary. I have a friend at one of the largest consulting firms who has said it'd been a game-changer in terms of processing huge amounts of documentation over a short period of time. Whether or not that gives better results is another question, but I would love to hear more stories of AI actually making things better.
These "questions" just seem like a trap/disingenuous. The people "asking" commonly have decided the answer and are just looking to reinforce that by playing "No true Scotsman" with other people's productivity increases.
We have software written in what is essentially an obsolete platform (a RAD solution from the 1990s). We've been slowly hand rewriting it into React. A single developer converts one a week by hand, and the results are good (we still have over a hundred).
We've developed an internal tool to turn the software's definition files into a single XML, and then are feeding it through a multi-process Codex pipeline (multiple instruction files, that product intermediaries), which ultimately outputs a "90%" working React page.
Our developers then PR the output, fix/adjust/test, and release. We've gone from one per week for a single developer, to roughly three per week without a marked quality loss.
It is taking care of most of the repetitive parts of the work, and allowing our developers to spend more time in technology they're familiar with (React) instead of legacy stuff. Is it perfect, no, but the cost/benefit is clear.
I imagine content farms, social media bots, at-scale scam operations, blackhat seo, busywork homework, social media propaganda botnetworks have all seen a significant boost of oroductivity.
Me! I'm in a leadership position at a marketing agency. I'm a self-taught programmer (just found it interesting and started on my TI-83 in high school doing BASIC and then some Z80 assembly) and studied creative writing in college.
I used to hand-write a lot of the scripts we used to automate processes (mostly Google Apps Scripts and Python). It was very helpful to us but slow going and sometimes frustrating.
In the past, I was limited by my programming knowledge and ability. Now I am limited by my knowledge of our business and ability to explain what I want to happen.
With LLMs, I can generally 1-shot most things I want to automate, including things that would've taken me days to figure out in the past. I generally just say that I'll spend 30 minutes on something and more often than not, it's either done or very close at the end of that time.
We have software written in what is essentially an obsolete platform (a RAD solution from the 1990s). We've been slowly hand rewriting it into React. A single developer converts one a week by hand, and the results are good (we still have over a hundred).
We've developed an internal tool to turn the software's definition files into a single XML, and then are feeding it through a multi-process Codex pipeline (multiple instruction files, that product intermediaries), which ultimately outputs a "90%" working React page.
Our developers then PR the output, fix/adjust/test, and release. We've gone from one per week for a single developer, to roughly three per week without a marked quality loss.
It is taking care of most of the repetitive parts of the work, and allowing our developers to spend more time in technology they're familiar with (React) instead of legacy stuff. Is it perfect, no, but the cost/benefit is clear.
I used to hand-write a lot of the scripts we used to automate processes (mostly Google Apps Scripts and Python). It was very helpful to us but slow going and sometimes frustrating.
In the past, I was limited by my programming knowledge and ability. Now I am limited by my knowledge of our business and ability to explain what I want to happen.
With LLMs, I can generally 1-shot most things I want to automate, including things that would've taken me days to figure out in the past. I generally just say that I'll spend 30 minutes on something and more often than not, it's either done or very close at the end of that time.