27 Matching Annotations
  1. Sep 2022
    1. Why History is Crucial: - History is how you win the argument. - History determines legality - History determines morality - History is how you develop compelling media. - History is the true value of cryptocurrency. - History tells you who’s in charge. - History determines your hiring policy. - History is how you debug our broken society.

    1. Different states will focus on different metrics; imagine a network state premised on improving its citizens’ overall life expectancy, or one aimed at provably right-shifting the income distribution for all. You get what you measure.

      extraterritorial contract jurisdiction as seen in libertarian thought?

  2. Feb 2022
    1. Rejecting based on query complexity (cost analysis)Amount limitingDepth limiting

      limit the load on the network

    2. We can reduce the load on the database significantly by batching and caching with Data Loader
    3. The issue is that potential attackers can easily call complex queries, which may be extremely expensive for your server and network.
    4. If you are in a development environment, it is definitely useful to allow introspection for various purposes. In production, however, it can leak important information for potential attackers, or it can also just reveal information about a new feature which has not yet been implemented on the frontend.
    1. When testing and trying out your mutations, I suggest you only use variables, and use inline arguments as little as possible. This will force you to make GraphQL documents that can be copy-pasted right from the GraphiQL into your integration test suits and to your frontend. If you only use inline arguments, you will need to rewrite the GraphQL document in the client.
    2. In most cases, it is much better to use the object type and input object type. If you want to add some field as the return, you should not use simple scalars as return values, as this will cause your GraphQL document to break.
    3. GraphQL does not support versioning out of the box, but is designed in a way that minimises the need for it
    1. The risk is that when you build a new thing for the second time, you'll feel less cautious and more experienced, and end up over designing the whole thing.
    2. Avoid implementing things that you might need in the future in favor of things that you definitely need today.
    3. When building queries, focus on the underlying data, rather than how it's represented in your application.
    4. Describe the data, not the view. Make sure that your API isn't linked too closely with the demands of your initial interface.
    5. Your objective with GraphQL should be to create a unified, cohesive graph that allows users of your API to create subsets of that graph in order to build new product experiences.
    1. it is much better to nest the output types. This way we can call everything with one single request, and also perform caching and batching with the data loader.
    2. Whenever you fetch lists, I suggest you use paginated if it makes sense. You will avoid breaking changes of the schema in the future, and it is almost always a much more scalable solution.
    3. Returning affected objects as a result of mutations
    4. Using the input object type for mutations
    5. Use consistent naming in your schema

      camelCase for fields, PascalCase for type names

  3. Jan 2022
    1. MAGA
    2. Indeed, there have been 57 hyperinflations in the world that we know about. However, they all took place amid political and social chaos;

      As of now, official inflation in US is 7% which is a lot and already big another to think about hedging. No need to over-dramatize here mentioning hyperinflation.

    3. Are banks that untrustworthy?

      There is a conflict of interests. Take an inflation for example. You are not in control of it, yet you carry the burden of it (the buying power of your money diminishes). You don't want it. Banks profiting from it (they usually the first to spend newly printed fiat money)

    4. many people accept the scientific consensus on, say, vaccine effectiveness not because they value peer-reviewed research but because they are impressed by people in lab coats who use big words
    5. the fact that many Bitcoin enthusiasts say bizarre things does not, in itself, mean that cryptocurrencies are a bad idea

      Is this some kind of attribution bias?