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Any examples?

Here's an example of what they're responding to with inaccurate personal attacks:

https://grapheneos.social/@GrapheneOS/116353973732143171

GrapheneOS posts factual information debunking inaccurate claims from groups attacking it. Some of those groups react to their misleading claims being addressed with personal attacks. Threads about GrapheneOS on Hacker News usually have multiple posts with personal attacks towards our team from people influenced by those groups.


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> GrapheneOS is security before anything else.

GrapheneOS is a privacy project highly focused on usability and compatibility. Privacy depends on security so it has to put a lot of work into security too and it has always been a major focus, but it's a misconception that it's all about security.

> This means they strongly advice against using other software many in their core audience are predisposed to like: Firefox, Signal, plugins for browsers, F-Droid, ect.

GrapheneOS doesn't recommend against Signal but rather it's the main recommendation for end-to-end encrypted chat from the project including via the Molly fork of Signal.

> The explanations are usually quite... blunt, and they're not exactly open for discussion (which makes sense, from a pure security perspective, those apps are indefensible).

This isn't true. GrapheneOS provides nuanced information with detailed explanations for these topics.


In my experience it's not as simple and depends on a whole lot of circumstances: generally I am interested to learn and to build. Give me pressure through dysfunctional processes, understaffed teams, unrealistic standards, too strong peer opinions- etc - and I'll happily reach for the shortest path.

Maybe the trick is to own it - are AI vtubers already a thing?

Neuro-sama has been a thing for quite a while, and is much more interesting than ChatGPT in a waifu suit. https://youtube.com/channel/UCLHmLrj4pHHg3-iBJn_CqxA

I can’t imagine having such a functional view of “consuming content” in my life that I’d ever want to watch that.

Truly something we still have to figure out. Attention budget is real and things can get buried. The really big problem of our time.

I wonder how gitops is done with docker compose

I see a lot of people using Komodo for it, though if I had to pick I'd go with Doco CD[0]. You can also use standard Ansible for just cron+bash script to git pull.

On the Podman side, I wrote a tool named Materia[1] for it, but there's also the wonderful Ansible quadlet role as well as Quadit and Orchess.

[0] https://github.com/kimdre/doco-cd

[1] https://primamateria.systems or https://github.com/stryan/materia


I recently setup Arcane and started migrating stuff from Truenas apps, they were all deployed as custom docker compose services so it worked out. Arcane supports Git syncs to auto deploy compose stacks, https://getarcane.app/docs/features/projects#sync-from-git I'll write up some posts on my full setup soon.

What _IS_ Arcane? I fail to understand from their website https://getarcane.app/

Is it a deployment automation platform where it can run a project’s docker services, with rollback and all?


so, the project is pretty much vibe coded, including the docs. It makes a lot more sense if you play around with it. It's just a docker host management UI, I like using it. It has gitops built in and a nice container log view. It doesn't do rollbacks, it only seems to sync from git and run compose up.

Is it analogous to portainer with a git-pull-compose-apply loop?

A long long time ago I wrote something for the company I was with to allow for pre-merge staging environments (preview environments but I didn't have a name for them then)

Used docker-compose + git for application servers, and docker-compose + sync for static sites.

Actually worked pretty well! There's bound to be better options nowadays.


Honorable mention: webxdc, as implemented in DeltaChat for example.

https://webxdc.org/


npm install will continue after a short break from our sponsor

Funny to read about that superpowers repo, since only yesterday I wrote skills to do some markdown-plan centered aproach. I feel like smallish local models are getting capable of lots of things now, but they need lots of structure for resiliency.

Yeah I’ve been using gpt-5.3-codex-spark in Codex lately and it can be surprisingly good and it’s super fast. However it needs more explicit instructions.

Reminds me of a time when it was possible to "deploy" single HTML files via shorturl services by using base64 URI scheme

The bio angle is crazy to think about - imagine a health crisis triggered by LLM. What a time we live in.

What's the risk here? If someone is skilled enough to produce said risk, do they need input from these models?

This is all so amazing and good. These are exciting times we’re living in. Can’t wait to see what the future holds.

Which part got you the most amped - "health crisis?"

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