Not proved scientifically tho. I just shared it so u guys think about.
Sometimes let's brainstorm ideas outside coding guys.

morocco energy 🔥

docker is really complex than I tot.

I was playing around with this concept called background jobs (or multi-process apps).

Normally we have one HTTP server handling requests. But what if the request includes heavy work like video processing, image processing, generating files, or even sending emails? Keeping those tasks inside the request-response cycle can make users wait for seconds or even minutes.

The idea is simple: let the server respond quickly and move the heavy work into its own process (a worker).

For example, when a user signs up, they don't need to wait for the welcome email to be sent. The server can immediately say "Registration successful", save the email job in Redis, and a separate worker process will pick it up and send the email a few seconds later.

Same with YouTube. The uploader doesn't wait for the entire video processing to finish. The upload is accepted, and the heavy processing happens later in the background.

So basically, background jobs are about separating slow, heavy work from the normal request-response flow and letting another process handle it. Since we now have a server process and a worker process running independently, we've built a simple multi-process application.

The old generation struggled with a lack of information. The new generation struggles with too much information. Yesterday's problem was access; today's problem is focus.

5 goals in 2 consecutive matches!

JavaScript DSA implemented in JavaScript, with detailed explanations and complexity analysis.

https://t.co/13bf1VEuKS

Traditional AI coding vs Loop Engineering

Traditional AI coding:
You manually prompt the AI step by step.
You -> prompt -> Ai -> read -> prompt again - > repeat

Loop engineering:
You build a system that runs the AI automatically in a cycle.
System ->AI -> check result -> retry/fix -> continue ->finish

Loop engineering is building software that continuously manages AI agents through an automatic cycle of execution, verification, and retry until the task is completed.

This repo shows how to build software that Orchestrates AI agents using loop engineering instead of manual prompting.

[link]

Damnnn he baited Elon into replying and farmed millions of impressions... Now he earned more😂... Genius

I successfully pushed it..... the env file🤯

Wtf with the African teams😭

It's strange how everything that felt urgent becomes meaningless when you're sick.

Health is a silent blessing until it's gone. Take care of it before life reminds you to.

Especially, protect yourself from chronic diseases. The habits you build today shape your health tomorrow. Your future self will thank you for starting now.

If someone is good at agent harness , context engineering, orchestration but doesn't have much actual technical skill, how far can they go with a project in terms of complexity, scalability issues, and things like that... do u think someone take it to really actual project that worth and scale¿

am sorry France 💔

Argentinaaa 🫡