Here is the GitHub repo with 1400+ free-to-use APIs: https://t.co/HVBqBcpKDu

Is MongoDB hacked fr!!!

Am about to start working on my project sometimes discipline is tough but we go again regardless I have no choice than to embrace pigheaded discipline

If you ever want to build something valuable: - Capture attention - Keep users engaged - Monetize indirectly

I've been working on some projects of late that's why I haven't been posting for a while now Expect more educational content from me now onwards

You need not to learn SYNTAX!!!! AI eats it for breakfast Learn Design Patterns Today

999 today, Nice count. Appreciating the small things. Goal: 15K by year-end. Let’s build together 🤝

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GM FELLOW DEVS!!

What are you building, share screenshots

GM devs!!!

The people who get this early move calmly, the rest stay stuck chasing tools And now the line between them should be clear

The Takeaway Most People Miss AI isn’t hard Skipping the basics makes it hard, understand the problem Define the input. Define the output. Decide what a good guess looks like then let the machine do the boring work That’s it

That’s the real goal Not to sound smart Not to collect buzzwords but to build systems that works

The Shift That Changes Everything Once the basics are clear, learning speeds up fast Suddenly models feel interchangeable Tools feel optional Documentation becomes readable Debugging becomes logical AI stops being impressive and starts being usable

But elite engineers don’t start with code They start with boxes and arrows, IYKYK This goes in That comes out This rule connects them Only after that does code appear That’s the secret rhythm

Why This Feels Hard When It Shouldn’t Beginners are taught tools before thinking Frameworks before logic. Libraries before reasoning. Results before understanding. So AI feels like a black box, something only geniuses touch...

The work isn’t in the model It’s in deciding what question to ask Not “can AI do this?” But “what exact decision is being automated?” That question alone filters out 90% of bad projects

If the problem is poorly defined, the AI looks smart but fails in real life. This is why many AI demos collapse outside tutorials.

The Hidden Layer Most People Never See Here’s the part that separates surface learners from real builders AI doesn’t learn the world, It learns the data If the data is bad, the AI is bad. If the labels are wrong, the AI is wrong...