If you guys have wondered where you could find open source alternatives for Amazon S3, here is one I have tried:
https://min.io

It allows you to store objects, get download urls with a custom expiration time and to top it all of, it has a web UI where you can see the uploaded objects. It also has a docker image available on the docker hub. Check it out.

We also got 100🔥

Coding is not Enough

For someone to be successful as a Software Engineer, the current market demands other things in addition to coding. Most people focus on their coding skills when they try to grow in their career as a Software Engineer. Although coding is a great skill to have, in today's market, it is not the most important one. The AI models that exist today can write good code as long as they are properly guided in the right direction. The following skills are great to focus on moving forward.

1. Architecture

Architecting systems for performance, scalability, security, and user experience is a very important skill to develop. Anytime we think of building a project, we should first think of the architecture. Planning should take most of our time rather than coding. We should not start coding unless we know exactly what we are going to do, at least at a high level.

2. Tools and Technologies

There are many tools and technologies out there that make our lives easier as Software Engineers. We should read about these tools and understand them. Understanding the tools and technologies we use would help us make decisions about which tool or technology aligns more with our goals whenever we plan our projects.

3. Communication and Collaboration

As Software Engineers, we have to communicate and collaborate with clients, managers, designers, and cross-functional team members. For this communication to be effective, we have to improve our skills of speaking and writing clearly in a way that is unambiguous. We should learn to explain technical things to non-technical people in a way they can understand. We should learn to write clear documentation that is very easy for our team members to understand. We should also learn to ask questions whenever we don't understand something. We should avoid assumptions and communicate clearly.

I would love to hear your thoughts on whether there is anything I missed or if there is anything you want to add.

came across this service which provides thousands of models just for free with unified single API just like the vercel ai-sdk. downside: only 1 concurrent request, but no restriction on usage, and tbh fast inference given that you got unlimited requests. you can access 141k models (including gpt 4.1 and many multimodals) on the free tier. they got both python and js sdk. cool stuff to experiment with

models: https://bytez.com/models
docs: https://docs.bytez.com/model-api/docs/welcome
#resources

https://www.linkedin.com/posts/a2sv_a2sv-education-generation7-activity-7388960222482079744-6DrE?utm_source=share&utm_medium=member_desktop&rcm=ACoAAD7wiqoB3AP7D1_JY_SDhbFUN4lWRrmeKDI

For anyone who is interested A2SV has opened the G7 applications phase

If you want a simple LLM framework that allows you to build AI workflows and agents, here is one I recently found:
https://github.com/The-Pocket/PocketFlow

The framework itself is literally just 100 lines of code. And the repo contains links to a great tutorial video and a link to their docs.

It even has a .cursor_rules directory which explains the framework and how to use it to your coding AI agent. I hope you'll find it useful.

So basically, let’s start from what authentication is…

Authentication simply means verifying or proving the identity of a user before giving them access to a resource.

In the real world, it’s like showing your ID card when entering a restricted place like a university. The gatekeeper checks two things:

If the ID is valid and issued by the university.

If it’s not expired meaning it’s still active.

If both are true, you’re allowed to enter.

Now, in the digital world, this same idea applies but digitally. There are many ways to authenticate users, and the two most common ones are Session-based authentication and JWT (JSON Web Token) authentication.

Let’s talk about JWT, since it’s one of the easiest to implement.

In any digital product, there are two main sides:

- The Client (the browser or app that users interact with).

- The Server (where we store all our data — posts, images, user info, etc.).

Let’s imagine a social media website.
When someone wants to post, like, or edit something, we need to know who the user is so others can’t edit or delete someone else’s posts. That’s where authentication comes in.

So, how do we verify a user’s identity?
👉 We use JWT Authentication.

JWT stands for JSON Web Token it’s basically a digital ID in the form of a long string that holds user information (like ID, username, and expiration time).

Here’s how it works step by step:

When a user signs up, they enter an email and password.
We save those details in our database on the server.

When they log in, we check if the email exists and if the password matches.

If it’s valid, we generate a JWT token containing the user’s info (like ID and username).

We then encrypt this token using a secret key and send it to the client.

This makes sure only we (the server) can read and verify it later.

Whenever the client makes a request (like fetching their posts), they send this token along with it.

The server decrypts the token using the secret key and:

- Checks if it’s valid.

- Checks if it’s expired.

If all is good, it uses the user’s ID from the token to fetch and return their specific data.

And that’s the basic idea of JWT Authentication a safe and efficient way to verify users and control access in modern web apps

@sifendev

Through: bot

Whenever you are doubting whether to use pointers or values in Go, default to values. Using values is simpler, and it is easier to switch to pointers in the future. It is also easier to reason about. However, there are some clear signs to indicate when to use one or the other.

Use values when
1. You are working with primitive data types and small structs that do not require modification
2. If you want to prevent data manipulation during compile time

Use pointers when
1. You are working with big structs
2. Your struct requires modification
3. If one of your methods accepts a pointer, use pointers for all others for consistency.

My Upwork Stats for 2025

I am switching my main backend language from Python to Go. Since it has been a while since I touched Go, I decided to refresh my memory of its syntax by building a wc clone from John Crickett's https://codingchallenges.fyi/.

I built the line, word, byte, and character count functionalities and wrote unittests using testify. I have also included the architecture documentation and an easy-to-follow Readme.

Here is my repo: https://github.com/abeni-al7/aben-wc

I would appreciate any feedback on my code and suggestions for improvement.



LinkedIn
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I just solved today's Advent of Code challenge. The second part took me a lot of time. Been staring and writing out the pattern on excalidraw for so long. My solutions are in my repo:

https://github.com/abeni-al7/advent_of_code

This is just a meme but eventhough programmers in rich countries get paid more than average salaries, they are usually in the middle class - upper middle class range in their countries. The cost of living is also very high in places where big tech companies are located making them spend more than people living in areas where the cost of living is lower. Meanwhile programmers in poor countries usually earn an amount of money small - medium sized business owners earn in their countries when they are employed at companies located in the rich countries remotely, which places them among the highest earners in their countries. Wealth is just relative and whenever salaries are considered, cost of living in the area should also be considered. When saying this, I'm not denying the fact that there are benefits that come with residing in the developed countries such as reliable electricity, reliable internet access and better systems and infrastructures. I'm just saying that everything is a tradeoff and there is no perfect scenario

In my current job, I am mostly refactoring previously written code to follow DDD (Domain Driven Design) principles. If any of you are experienced with DDD or Clean Architecture, you would know how much Interfaces are used for dependency inversion. This can usually be implemented in languages that support interfaces very easily. You define the interface you want in the domain layer, and you extend that interface and implement it in any of the layers that the domain should never depend on. But in Python, you don't have access to interfaces. So what I found out recently is the concept of Protocols in Python. Protocols allow you to define contracts that can be implicitly implemented by your layers. It works exactly like interfaces in Go. You don't have to explicitly inherit from or extend the protocol. As long as you implement all the methods defined in it, it just works. I hope this will be useful for anyone who is working on DDD with Python.

Real

The slide says this, but the school still choose to give us the course 😑

@cyber_Guardian5

😂 Explanation of Human in neal.fun