u/Fit-Common-5148 — reddlx

A parent once told me:
“Doctor, I didn’t know something was wrong. My kid seemed fine.”

That stayed with me.

In my experience, developmental delays aren’t caught late because parents don’t care — it’s because no one tells them what to look for, or gives them a simple way to track it.

So I built something small with a friend.

It’s called Grow Baby Grow — a free app designed for Indian parents:

Month-by-month milestones in simple language
Red flag alerts for early intervention
Full vaccination tracker (NIS + IAP)
Reminders for upcoming vaccines
Works completely offline (data stays on your phone)

It’s based on AIIMS + IAP guidelines and covers multiple developmental domains.

Not trying to sell anything — just hoping it reaches people who might need it.

If you’re a parent, I’d genuinely love feedback.
If you know someone who is, feel free to share.

https://play.google.com/store/apps/details?id=com.growbabygrow.app

https://github.com/Xdev200/Grow-Baby-Grow

Has anyone systematically looked at how RAG / agent memory quality changes the longer a session runs?

I've been noticing agents get noticeably less accurate after 15-20+ steps — not because the model degrades, but because retrieved context seems to get noisier over time. Old tool outputs, stale decisions, stuff that's no longer relevant all competing with actually useful memory.

My instinct is this is a retrieval problem more than a storage problem. But I haven't seen much written about it.

A few things I'm genuinely uncertain about:

— Is this a known, documented pattern or am I pattern-matching on noise?
— How are people handling it today? Pruning manually? Ignoring it?
— Is the fix actually just better chunking / embedding strategy upstream?

Not pitching anything. Just found myself going in circles on this and figured someone here has thought about it more carefully.