It has been a while since I last wrote for my archive or posted on CoderLegion.
Recently, I have been busy with several projects, and this might be the first time in a while that I am sitting down again to write properly. But instead of writing a polished conclusion, I wanted to open a discussion.
There is one word I keep coming back to.
Verify.
That is also the direction I want my site, Dechive, to follow.
These days, when I look at SNS, Threads, Instagram, or other online communities, I often see similar stories.
Someone says they made money with an automated trading program.
Someone says they earned revenue through Google AdSense.
Someone says AI can help anyone build a profitable side project.
Someone says Coursera is useless, that online certificates have no value, or that those platforms simply give certificates to anyone who pays.
When I see these claims, I do not immediately think they are all fake.
But I also do not want to believe them too quickly.
Maybe some of those stories are real.
Maybe some are exaggerated.
Maybe some people are dismissing things they have never actually tried.
Maybe others are following success stories without checking the conditions behind them.
So the question I keep asking myself is simple:
How do we know?
Do we believe a success story because it sounds exciting?
Do we reject it because it sounds too good to be true?
Do we laugh at online certificates without trying the courses ourselves?
Do we assume monetization stories are scams before checking what actually happened?
I am not sure the answer is simple.
That is why I have been trying to test things myself.
I started a project to see whether Google AdSense is actually possible for the kind of content and site I am building.
I am building my own trading-related program to understand what can really be verified and what cannot.
I paid for Coursera and started taking courses myself, not because I believe every certificate is valuable, but because I wanted to know what the learning experience actually feels like.
Maybe some of these attempts will fail.
Maybe I will find out that some claims were overhyped.
Maybe I will discover that some things are more useful than people say.
Maybe the real answer will depend on context, effort, timing, and the person using it.
But I would rather reach that conclusion after testing something than after simply believing or dismissing it.
In the AI era, creating things has become faster.
We can create articles faster.
We can create images faster.
We can build prototypes faster.
We can generate business ideas faster.
We can even create convincing stories faster.
But does faster creation mean faster judgment?
I am not sure.
Maybe the faster information moves, the more carefully we need to verify it.
When you see someone’s AI workflow, monetization result, certificate, trading bot, or side project story, what do you usually do?
Do you think, “That looks interesting”?
Do you think, “That must be fake”?
Do you think, “Maybe I should try it too”?
Or do you stop and ask, “What would it take to verify this?”
This is the question I want to ask here.
In the AI era, should we believe less?
Should we doubt more?
Or should we build a stronger habit of testing things ourselves?
Right now, I am leaning toward the third option.
Not believing immediately.
Not dismissing immediately.
But verifying first.
That is the direction I want to explore through Dechive.
Not a place for fast conclusions, but a place for questions, experiments, and records of what was actually tested.
I would love to hear how others think about this.
When you see AI success stories online, do you try to verify them?
And if you do, how?