Most indie hackers think the hard part is building.
It’s not.
The hard part is understanding the exact moment something breaks.
I’ve been deep in home health workflows lately, and it’s honestly one of the clearest examples of this. On the surface, everyone talks about billing delays and documentation issues. Sounds straightforward. Fix the forms, speed up charting, automate a few steps.
But when you actually sit in it, the problem feels different.
A nurse can finish a visit. Documentation gets completed. Everything looks done. And then… nothing moves. Billing can’t use it yet. The system hasn’t caught up. People start checking, refreshing, asking each other what’s missing. But nothing is technically wrong.
That’s the kind of problem you don’t notice unless you’ve lived it.
And it shows up in products.
There are a lot of tools in AI home health software right now trying to “fix efficiency.” Better notes, faster inputs, cleaner dashboards. But the ones that actually feel useful are solving that weird in-between moment where work is finished but still not usable.
That’s not something you find in a market research doc.
That comes from being the person sitting there thinking, why is this not moving.
If you’re building something right now and it’s hard to explain why it matters, it’s usually because you’re a few steps removed from that moment. You’re describing the category of the problem instead of the experience of it.
And users can feel that immediately.
The builders who get traction aren’t always the most technical. They’re the ones who can point to one very specific situation and say, this right here is what I’m fixing.
If you want a breakdown of what this actually looks like inside a real workflow, I put it together here: https://pointofcarepicks.blogspot.com/2026/03/how-data-latency-in-home-health.html