u/MomentInfinite2940

Comments are the king when you are small, like under 10k-20k

Linked In likes comments much more and when you comment more -> you are engaging with others and spend more time on the platform -> algorithm remembers that and pushes your posts more.

Of all of features Linked in likes comments the most.

But not any comment, Ai slop comments destroy reputation.
Good comments are gold.
If you comment often to someone's profile you get free visibility out of his audience.

Then you get views to your profile, cause people click and want to connect with someone smart and like-minded.

Then they see your page - what you do, what you offer, your prospect, if its interesting they will connect or reach out with DM so you can help them with something and sell your services.

Its pretty simple actually, the whole process.

For decades, technical interviews for engineers tested memory and logic under pressure. Everyone knew it was broken.
Now AI has made it irrelevant, and has to evolve or change.
Only the companies that can do these properly, can grow.

The famous three-phase interview (The Quiz, Coding Task, Critical Thinking) isn't totally dead, in my opinion, they just should be evolved...

Evolved it in actually tests that matters.

1. The Quiz → Can become something like "Questions of the Strategic Choice"

Generation of code is free now, code is a commodity.
Everything is about how you can control the code now and your knowledge to change and extend it, and decisions with it.

Can you decide when an LLM hallucination costs you?
When caching a response becomes a liability?
When you need determinism over convenience?
That should be like the interview question.

The engineer who says "I'll use Claude for boilerplate but this permission logic is mine" just proved they can think.
The one who says "I'll just generate the whole thing" proved they can't. Simple, its all about control.

2. The Coding Task → "Verification Phase"

The engineering moves into the code-reviewing of the AI outputs.
They now write the least code that survives contact with reality.

They build feedback loops.
Permission systems.
Validation layers that don't depend on a model's next token being correct. They write tests that target the constraint, not the happy path.

If you can't explain why you built something around the AI's output, you don't understand what you've built.

3. Critical Thinking → "The Systems Thinking Phase"

Can you articulate WHY your system works?

Not what it does.
Why it's safe.
Why it degrades gracefully.
Why a user and your team should trust it.
How it could evolve?
What happens in situation with X variables what happens with Y?
That explanation is the interview.

If your interview still measures typing speed and you are giving an for loop to reverse strings, to prove how the engineer is thinking, you're testing the wrong era.

P.S: What do you think?