aimed at AI-scale data growth.

This is an important part that the responses glossed over. The responders suddenly forgot that they were just recently sold down the river for this aim, and seem to think that it won’t continue.

They can suck my dick and balls. None of this benefits the average consumer.

I have all my services spun up in docker containers, which makes it easier to pick and choose which services use Tailscale and which use a VPN. I guess I haven’t yet been put in a position where I wanted one to use both.

Tailscale’s free offering goes a long way.

Never attribute to stupidity that which is adequately explained by a good marketing opportunity.

I’m just thinking if you got nicked and didn’t have a chance to reboot into an encrypted state, or otherwise the device was compromised outside the house.

Y’all aren’t worried about having a tunnel into your (likely questionable) servers, on your mobile devices?

Hold up, you’re telling me Zuckerberg isn’t a good person?

I read OpenClaw and for some reason hoped it was a new port of Claw.

Lemmy is full of militantly anti-AI folks who would rather die on a hill penniless, than use a flawed technology against oppressing influences, in their own favor. Despite the impending bubble pop, the tech isn’t going anywhere, may as well learn how to leverage and exploit it in the workplace.

I’ve fooled them into thinking I’m so studious and productive, that I’m only required to spend 4 hours in office, 4 days a week. A good chunk of that time is spent chatting with people I enjoy chatting with over coffee. I’m also naturally reclusive, so the requirement of getting out of the house has a positive impact on my life, regardless of the setting.

EDIT: I’m playing 4D chess over here while all you downvoters are 2D nut-tapping each other.

They’re using AI inefficiently, then. I use it to get a lot done in very short bursts through the day, and spend longer bursts fucking off in between.

EDIT: imagine being so brainrotted that you think it’s bad to use AI to reclaim more of your day from your wage slavers.

If they enable that and iron out the iOS app, it’d be a surefire migration for my whole crew.

If we’re referring to the article in the link, being self-hosted didn’t seem to be a hard requirement, merely that the app is a potential alternative.

If Stoat (formerly Revolt) can integrate screen sharing capabilities soon enough, they will be the closest, user-friendly experience to Discord. Even the UI is familiar, if you come from Discord.

I thought Discourse was bought by Roblox, merged into Roblox, and then discontinued outside of Roblox?

I’m thinking of something else, I think.

Meredith Whittaker is bae.

Excel

Nah dawg.

But at a certain point, it seems like you spend more time babysitting and spoon-feeding the LLM than you do writing productive code.

I’ve found it pretty effective to not babysit, but instead have the model iterate on it’s instructions file. If it did something wrong or unexpected, I explain what I wanted it to do, and ask it to update it’s project instructions to avoid the pitfall in future. It’s more akin to calm and positive reinforcement.

Obviously YMMV. I am in charge of a large codebase of python cron automations, that interact with a handful of services and APIs. I’ve rolled a ~600 line instructions file, that has allowed me to pretty successfully use Claude to stand up from scratch full object-oriented clients, complete with dep injection, schema and contract data models, unit tests, etc.

I do end up having to make stylistic tweaks, and sometimes reinforce things like DRY, but I actually enjoy that part.

EDIT: Whenever I begin to feel like I’m babysitting, it’s usually due to context pollution and the best course is to start a fresh agent session.

This is extremely valid.

The biggest reason I’m able to use LLMs efficiently and safely, is because of all my prior experience. I’m able to write up all the project guard rails, the expected architecture, call out gotchas, etc. These are the things that actually keep the output in spec (usually).

If a junior hasn’t already manually established this knowledge and experience, much of the code that they’re going to produce with AI is gonna be crap with varying levels of deviation.