the 70/30 principle: AI handles 70% of execution, the human provides the 30% that matters.

Never mentioned authentication

readable AND writable by anyone on Earth for 11 days

Shouldn’t you have had a human check that before going live, given the 70/30 principle?

Full writeup with forensic details, the remediation comedy, and the 70/30 framework: mpdc.dev/the-locksmiths-apprentice I document everything — wins and losses — because someone building their first self-hosted stack shouldn’t have to learn this the hard way.

I don’t think they should learn from you, either, to be fair.

And then what?

I believe you set env vars on Windows through System Properties -> Advanced -> Environment Variables.

I believe you just need to set the env var OLLAMA_HOST to 0.0.0.0:11434 and then restart Ollama.

What OS is your server running? Do you have an Android phone or an iPhone?

In either case all you likely need to do is expose the port and then access your server by IP on that port with an appropriate client.

In Ollama you can expose the port to your local network by changing the bind address from 127.0.0.1 to 0.0.0.0

Regarding clients: on iOS you can use Enchanted or Apollo to connect to Ollama.

On Android there are likely comparable apps.

For reference, Anthropic is currently valued at $183 Billion and their annual recurring revenue is currently $5 Billion (up from $1 Billion in 2024). So this will cost them roughly 30% of their current annual revenue.

I’m a professional software engineer and I’ve been in the industry since before Kubernetes was first released, and I still found it overwhelming when I had to use it professionally.

I also can’t think of an instance when someone self-hosting would need it. Why did you end up looking into it?

I use Docker Compose for dozens of applications that range in complexity from “just run this service, expose it via my reverse proxy, and add my authentication middleware” to “in this stack, run this service with my custom configuration, a custom service I wrote myself or forked, and another service that I wrote a Dockerfile for; make this service accessible to this other service, but not to the reverse proxy; expose these endpoints to the auth middleware and for these endpoints, allow bypassing of the auth middleware if an API key is supplied.” And I could do much more complicated things with Docker if I needed to, so even for self-hosters with more complex use cases than mine, I question whether Kubernetes is the right fit.

While police may resent offensive words, they cannot use their authority to punish individuals for lawful, protected conduct.

Factually incorrect.

First, consider that regardless of whether they are prohibited from arresting people for insulting them, they do. Those charges are often dropped or thrown out, sure - albeit with no consequences for the police officer - but I would consider having to deal with that hassle “punishment” that they can inflict purely because of their authority.

But there’s also institutional support for an officer to punish you for lawful, protected conduct. If you upset an officer and in response, he cites or arrests you for a minor but legitimate offense that he’d have otherwise not cared about, you’re very unlikely to get that technically legitimate charge thrown out of court. It may be that police are technically prohibited from doing this, but in practice, “He only arrested me for — insert random crime here, let’s say jaywalking — because I called him a pig, said I’d engaged in coitus with his mother the previous night, and asked if he’d like to watch next time or if he had a night in with his partner’s nightstick planned” isn’t going to suffice to get the charge thrown out, even if the judge believes you, if you were actually breaking the law in question. And since pretty much everyone is breaking laws all the time, this means that as long as the police officer can find one that you’re currently breaking, you’re fucked.

We need more unions like this one.

Summary of my comment: the study showed that the AI tool in question was an effective tool for the task, nothing more.

I didn’t read this particular article, but I recently read a different one about the same study. I also clicked into the study itself and read the abstract and everything else that was freely available. The study was paywalled, but as far as I could tell:

• Performance immediately displayed a sustained increase of 24% relative to baseline while using the AI tool in question
• Immediately after the tool was taken away (after using it for three months), performance was 20% lower than the baseline
• The study did not check to see what level performance returned to after three months without it, nor when it returned to baseline levels
• The study also did not compare performance drops after returning from a three month vacation
• The study did not compare performance drops when losing access to other tools

This outcome is expected if given a tool that simplifies a process and then losing access to it. If I were writing code in Notepad and using _v2, _v3, etc for versioning, was then given an IDE and git for three months, then had to go back to my old ways with Notepad, I’d expect to be less effective than I had been. I’ve been relying on syntax highlighting, so I’m going to be paying less attention to the specific monochrome text than I used to. I’ll have fallen out of practice from using the version naming techniques that I used to use. All of the stuff that I did to make up for having worse tooling, I’m out of practice with.

But that doesn’t mean that I should use worse tools.

Edit: also i have a very strong suspicion that someone will figure out a way to make most matrix multiplications in an LLM be sparse, doing mostly same shit in a different basis. An answer to a specific query does not intrinsically use every piece of information that LLM has memorized.

Like MoE (Mixture of Experts) models? This technique is already in use by many models - Deepseek, Llama 4, Kimi 2, Mixtral, Qwen3 30B and 235B, and many more. I read that GPT 4 was leaked and confirmed to use MoE, and Grok is confirmed to use MoE; I suspect most large, hosted, proprietary models are using MoE in some manner.

This is what I would try first. It looks like 1337 is the exposed port, per https://github.com/nightscout/cgm-remote-monitor/blob/master/Dockerfile

x-logging:
  &default-logging
  options:
    max-size: '10m'
    max-file: '5'
  driver: json-file

services:
  mongo:
    image: mongo:4.4
    volumes:
      - ${NS_MONGO_DATA_DIR:-./mongo-data}:/data/db:cached
    logging: *default-logging

  nightscout:
    image: nightscout/cgm-remote-monitor:latest
    container_name: nightscout
    restart: always
    depends_on:
      - mongo
    logging: *default-logging
    ports:
      - 1337:1337
    environment:
      ### Variables for the container
      NODE_ENV: production
      TZ: [removed]

      ### Overridden variables for Docker Compose setup
      # The `nightscout` service can use HTTP, because we use `nginx` to serve the HTTPS
      # and manage TLS certificates
      INSECURE_USE_HTTP: 'true'

      # For all other settings, please refer to the Environment section of the README
      ### Required variables
      # MONGO_CONNECTION - The connection string for your Mongo database.
      # Something like mongodb://sally:sallypass@ds099999.mongolab.com:99999/nightscout
      # The default connects to the `mongo` included in this docker-compose file.
      # If you change it, you probably also want to comment out the entire `mongo` service block
      # and `depends_on` block above.
      MONGO_CONNECTION: mongodb://mongo:27017/nightscout

      # API_SECRET - A secret passphrase that must be at least 12 characters long.
      API_SECRET: [removed]

      ### Features
      # ENABLE - Used to enable optional features, expects a space delimited list, such as: careportal rawbg iob
      # See https://github.com/nightscout/cgm-remote-monitor#plugins for details
      ENABLE: careportal rawbg iob

      # AUTH_DEFAULT_ROLES (readable) - possible values readable, denied, or any valid role name.
      # When readable, anyone can view Nightscout without a token. Setting it to denied will require
      # a token from every visit, using status-only will enable api-secret based login.
      AUTH_DEFAULT_ROLES: denied

      # For all other settings, please refer to the Environment section of the README
      # https://github.com/nightscout/cgm-remote-monitor#environment

To run it with Nginx instead of Traefik, you need to figure out what port Nightscout’s web server runs on, then expose that port, e.g.,

services:
  nightscout:
    ports:
      - 3000:3000

You can remove the labels as those are used by Traefik, as well as the Traefik service itself.

Then just point Nginx to that port (e.g., 3000) on your local machine.

—-

Traefik has to know the port, too, but it will auto detect the port that a local Docker service is running on. It looks like your config is relying on that feature as I don’t see the label that explicitly specifies the port.

JustWatch is still useful if you want to act like you watched it legitimately, e.g., if a coworker asks where they can watch it. Even if your coworker also pirates, they might not have an account on your private tracker, Usenet, etc…

I may be wrong, as I haven’t actually torrented anything substantial since Demonoid was still a thing, but it all feels less accessible than it used to be.

From the blog post referenced:

We do not provide evidence that:

AI systems do not currently speed up many or most software developers

Seems the article should be titled “16 AI coders think they’re 20% faster — but they’re actually 19% slower” - though I guess making us think it was intended to be a statistically relevant finding was the point.

That all said, this was genuinely interesting and is in-line with my understanding of the human psychology that’s at play. It would be nice to see this at a wider scale, broken down across different methodologies / toolsets and models.

PSTN is wiretapped.

It’s a good thing that the website itself supports sending and receiving alerts, then.

Current generation iPad Pros and Airs have the same processing power as Apple Silicon Macs. That’s more than enough for Blender. Even the base iPad and the iPad Mini likely have enough processing power - though I don’t think the base iPad has enough RAM.

Does mirroring a screen (or adding a screen) from a computer or connecting to a computer via remote desktop count?

if everyone thought like you no one would create digital media

This is obviously incorrect.

I thought Hue bulbs used Zigbee?