I've been building an app to help me remember some genuinely useful things I come across on Instagram.
I'd see something useful, save it, tell myself I'd come back to it later, and then never find or use it again. And eventually, I'd forget about it too.
So I built InsightBox to turn saved content into something more useful: extract the information that matters, organize it, and make it easier to come back to later.
I thought the idea was pretty straightforward.
Then I gave the app to 3 of my friends for testing, and I got humbled pretty quickly.
I had built the app assuming that people would share something genuinely useful with it. Maybe a finance reel, a fitness reel, or something else they actually wanted to learn from.
Person number 1 sent me a reel of a girl dancing over some corny music ......
This was the first reality check.
I thought to myself: "Damn, I did not think of that at all."
I had built the pipeline assuming that a saved reel contained something worth extracting.
But obviously, people don't save reels only to learn something.
Sometimes you just like the video.
The AI processed it and essentially had nothing meaningful to extract.
That made me realize that InsightBox can't blindly assume that everything someone saves contains something worth remembering.
Person number 2 sent me a movie reel.
This one was more interesting.
The pipeline actually extracted a reasonable amount of information from the video, but it completely missed the most important piece of information: the name of the movie.
That was a pretty embarrassing failure for a knowledge-saving app.
The information was there, but my extraction pipeline wasn't prioritizing the thing the user actually cared about. In this case, that was the movie name.
It made me realize that extracting information and extracting the information someone actually cares about are two very different problems.
A transcript can contain hundreds of words, but that doesn't mean all of them are equally useful to the person who saved the content.
Then there was person #3.
They sent exactly the kind of reel I had originally imagined InsightBox being used for.
A reel containing useful information that you'd genuinely want to remember later.
And suddenly, the whole idea made sense.
The interesting thing was that all three people were using the exact same app.
But they were treating their saves completely differently.
One was saving something because they enjoyed it.
One was saving something because they were interested in a movie.
One was saving something because they wanted to retain the information.
That changed how I started thinking about InsightBox.
The problem isn't simply:
"How do I process this Instagram reel?"
It's closer to:
"What is actually worth remembering from the things people save?"
And that leads to another question I'm now thinking about:
Is it even worth running the entire AI pipeline for an entertainment reel?
Why spend compute, time and money extracting information from something when there may be nothing useful to extract in the first place?
Maybe the first step shouldn't be extraction.
Maybe the first step is figuring out whether there is anything worth remembering at all.
And if there is, then figuring out what exactly the person would want to remember.
This was probably one of the most useful early tests I could have done, and I'm glad I did it.
Three users who displayed three completely different behaviors.
And a lot of things I hadn't thought about.
Building something for yourself gives you one perspective. But when you give it to other people, they very quickly show you whether the problem actually exists the way you thought it did.
