Back arrow, reload sign, house for the home button (all them on most web browsers), +/- signs, trash can to delete, music notes, thumbs up and down, movie clap, compas for navigation, "?" for help, clock for time, lockpad for secured, git wrap for free, speaker for volume, bell for notification, battery, pen to edit, calendar for date, clipboard to copy/past, gear for settings, yellow triangle for warning, red circle carrying an icon for forbidden, check mark for approved...
We are literally living in the era of emoji and there is one for every single one up there. Teens can have all conversations without using words.
It happens because the more we use symbols, the more we attach and spread meaning.
Send "lesser than three" to someone 30 years ago, you'll get a blank reaction.
"Compass for navigation" would actually confuse me as I expect a "Google maps pin" for that, for example.
Also <"?" for help>, that's literally text made an icon, hardly counts for this conversation.
As someone who uses emojis to a degree that is embarrasing, I agree tgat often are amazing to convey things tgat words have harder time, but I still have to accept that there is ambiguity in their meanings, yes, a bunch of conventions have rooted enough that most people would undertand the same, but get out of those or simply present them in a different environment and things change. Labels are way less ambiguous.
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.
I just reviewed uv for my team and there is one more reason against it, which isn't negligible for production-grade projects: Github Dependabot doesn't handle (yet) uv lock file. Supply chain management and vulnerability detection is such an important thing that it prevents the use of uv until this is resolved (the open github issue mentions the first quarter of 2025!)
While working in Django projects, one would prefer to have an environment activarted to perform all kinds of django-admin commands, I certainly wouldn't want to do via `uv run`.
Also, `nvim` is started with an environment activated if you want all the LSP goodies.
`uv run` is good for some things, but I prefer to have my venv activated as well.
But still, it's not good enough for Django as there are too many management commands and I don't want to configure them in pyproject.toml file, especially since some of them take additional arguments... There is no point in using anything but django-admin command (I do have a wrapper around it, but the point remains) and that requires activated venv.
How exactly does `uv` determine which is "the" venv? Is it simply based on the working directory like the `direnv`/`autoenv`/etc. workflows others are describing here?
It does seem like people have use cases for running code in a different environment vs. the one being actively used to develop the package.
It uses the content of the UV_PROJECT_ENVIRONMENT var env, which defaults to .venv. If you pass --active, it can also look whatever is in VIRTUAL_ENV and CONDA_PREFIX.
You can also force an env passing a complete path to --python
conda compiance is nearly impossible to get because the typical anaconda project doesn't exist: it's a separate ecosystem with huge variability that is by design incompatible with everything else and that no two teams use in the same way.
We are literally living in the era of emoji and there is one for every single one up there. Teens can have all conversations without using words.
It happens because the more we use symbols, the more we attach and spread meaning.
Send "lesser than three" to someone 30 years ago, you'll get a blank reaction.
Send "<3" today, and it's a different game.