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TILs

Fueling Curiosity, One Insight at a Time

At Codemancers, we believe every day is an opportunity to grow. This section is where our team shares bite-sized discoveries, technical breakthroughs and fascinating nuggets of wisdom we've stumbled upon in our work.

  1. Codemancers
    cat k8s.yaml | kubectl apply -f-
  2. Codemancers
    cat k8s.yaml | kubectl apply -f-
  3. Codemancers
    cat k8s.yaml | kubectl apply -f-
  4. Codemancers
    revive stuck terminals : eg - In case you loose your ssh connection and your terminal is stuck, but would like to continue on the same terminal without closing it.

    Code

    press "(esc) (enter) (shift + `) (.)" ignore brackets :

  5. Codemancers
    In ActiveRecord when using default scope filters, be careful in left_joins queries. As the scope would show up the join on clause.
  6. Codemancers
    Protocol buffers are a lightweight alternative to JSON format to share data between systems. You get the advantage of not having to write out serializers and deserializers by making use of a schema like contract file .proto. This file can be shared and used by protobuf compilers that de/serialize data into language of our choice.
  7. Codemancers
    Protocol buffers are a lightweight alternative to JSON format to share data between systems. You get the advantage of not having to write out serializers and deserializers by making use of a schema like contract file .proto. This file can be shared and used by protobuf compilers that de/serialize data into language of our choice.
  8. Codemancers
    privacy.firstparty.isolate. This feature restricts cookies, cache and other site data so it can only be accessed by the first party domain name.
  9. Codemancers
    adb shell input text "RR" to reload react native app from laptop instead of shaking the devise.
  10. Codemancers
    adb shell input text "RR" to reload app from laptop instead of shaking the devise.

Showing page 27 of 42

Your competitors are already using AI. The question is how fast you want to unlock the value.

  • Don't know where to start?

    AI is everywhere but it's unclear which investments will actually move your metrics and which are expensive experiments.

  • Your data isn't ready

    Most AI projects fail at the data layer. Pipelines, quality, access all need work before LLMs can deliver value.

  • Internal teams are stretched

    Your engineers are shipping product. They don't have capacity to also become AI specialists with production-grade experience.

  • Legacy systems block everything

    Aging, undocumented codebases make AI integration slow, risky, and expensive. They need to move first.

Don't worry. We've got you covered.

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