The Day the Scanner Found Nothing

The first wall I hit with MyTradePilot did not look like a disaster.

The site was up. The pages loaded. Buttons existed. The scanner looked like it was doing something.

Then it returned 0 candidates.

That number bothered me more than an error message would have. An error message is at least honest. It says, "I am broken." But 0 candidates felt sneaky. It made me wonder if the app was actually evaluating the market or just going through the motions.

I asked what was wrong. Lovable found one problem with the sample market data. The scanner was using made-up stock information at that stage, and the way it created that information was flawed. It was producing results in a way that kept the opportunity list empty.

Okay. Fixable.

But the deeper issue was emotional, not mechanical.

I typed what I was really feeling: "Something isn't right. This feels like purely a thin demo page. What criteria is the system using to determine opportunities? What makes an opportunity actionable? Why isn't the system making recommendations that can be immediately executed?"

That was the moment I stopped being impressed by the screen and started demanding substance.

Lovable gave me a more honest answer. The scoring idea was there. It was looking at five broad areas: company strength, price movement, possible news or events, market mood, and risk. It even had grades like A, B, and C.

But the data was still mock data.

That means the app was not yet looking at real current market information. It was more like a flight simulator than an airplane. Useful for testing controls, maybe, but not something you would fly across the country.

That was hard to hear because part of me wanted to believe I was already close. I wanted to believe the app was ready to find trades, make recommendations, and maybe even place them.

Instead, I had to accept that I had a good-looking shell with some early logic inside it, but not a real trading system yet.

For someone with no coding background, this is where AI building gets tricky. The app can look polished. It can use impressive words. It can have charts and buttons and dashboards. But unless you ask, "Where is this information coming from?" you might be fooling yourself.

That question became one of my most important tools.

Where is the data coming from?

Is this live or sample?

What rule caused this recommendation?

Can this action actually happen, or is it just displayed on the page?

Around that same time, I learned there was no true automation yet. The scanner only ran when I manually clicked it. There was no scheduled task running on its own in the background. No behind-the-scenes worker waking up before the market opened. No real routine.

So I told Lovable to do all four automation pieces in the best order.

That became the next push: scheduled scans, settings for automatic scanning, settings for automatic trading, and limits on how many trades could happen in one run.

The wall was frustrating, but it was useful.

It forced me to stop admiring the app and start inspecting it.

That is a big difference.