Definitely has been true for my work. LLMs have absolutely have been useful, I even forked an IDE (Zed) to add my own custom copilot to leverage a deeper integration for my work.
But even if we consider AI beyond just NLP, there's been so much ML you can apply to other more banal day to day tasks. In my org's case, one of the big ones was anomaly detection and fault localization in aggregate network telemetry data. Worked far better than conventional statistical modeling.
I usually assume there is a caricature of "AI Tools" that all of the detractors are working backwards from that are often nothing more than a canard for the folks that are actually using AI tooling successfully in their work.
We never have any proof or source for that, and when we have one (like the Devin thing) it’s always a ridiculous project in JS with a hundred lines of code that I could write in one day.
Give me some refactoring in a C++ code base with 100k lines of code, and we’ll be able to talk.
Anything with using tools which you are not an expert with. If you know how to do things and only use one specific language or framework -- there is nothing to use AI for.
This whole area is so drenched in bullshit, it's no wonder that the generation of BS and fluff is still the most productive use. Just nothing where reliable facts matter. I do believe that machines can vomit crap 10x as fast as humans.
I had to sign a 140 page contract of foreign language legalese. Mostly boiler plate, but I had specific questions about it.
Asking questions to an AI to get the specific page answering it meant I could do the job in 2 hours. Without an AI, it would have taken me 2 days.
For programming, it's very good at creating boilerplate, tests, docs, generic API endpoints, script argument parsing, script one-liners, etc. Basically anything for which, me, as a human, don't have much added value.
It's much faster to generate imperfect things with AI and fix them that to write them myself when there is a lot of volume.
It's also pretty good at fixing typos, translating, giving word definition, and so on. Meaning if you are already in the chat, no need to switch to a dedicated tool.
I don't personally get 10x on average (although on specific well suited task I can) but I can get a good X3 on a regular basis.
But what you're doing isn't a real job. Who hands someone who doesn't speakt the language a contract to sign? Don't you have a legal department that does this job for you and has people that are specialists for that?
Also, what are you going to do if the AI answered inaccurately and you signed a contract that says something different then what you thought?
I am actually pretty sure that the thing described literally isn’t a real job, at least not working for a serious employer. I can’t imagine a company telling someone to sign contracts in a language they can’t speak and somehow try to make a sense of it.
Either it’s their own company and they’re doing something unwise, they are doing it without the knowledge of their superior or their company shouldn’t be trusted with anything.
The point was that „AI helps me translate the contracts I want to sign“ isn’t a good example of „AI increases my productivity“ because that’s not something you should ever do.
But you shouldn't do some stuff you can't do properly at all, not quickly and not slowly. As a layman, you can't sign a contract in a language you don't speak, even if you have a whole year, unless you can become more-than-fluent in that language in a single year. That's just not something you should do, and the AI isn't reliable enough to help you with it. That's what a legal department is for.
I would never in my whole life sign anything in a foreign language that I don’t understand. It’s the perfect example of what AI is: let’s do anything that looks like a job well done and fuck it. That is not convincing. It’s suicidal.
But even if we consider AI beyond just NLP, there's been so much ML you can apply to other more banal day to day tasks. In my org's case, one of the big ones was anomaly detection and fault localization in aggregate network telemetry data. Worked far better than conventional statistical modeling.
I usually assume there is a caricature of "AI Tools" that all of the detractors are working backwards from that are often nothing more than a canard for the folks that are actually using AI tooling successfully in their work.