u/Relevant-Trad

After a few hours of coding, TapAnimals is about to go live on the App Store.
The concept is embarrassingly simple: tap an animal card, hear the sound and name. But the journey to ship taught me a ton.
Technical decisions worth sharing:
Audio: I went with AVAudioPlayer with all sounds bundled in the app rather than streaming. Adds ~8MB to the bundle but means zero latency and zero network dependency — critical when a 1-year-old is waiting for the elephant sound.
SwiftUI animations: Used scaleEffect + spring() for the tap feedback. Toddlers love the bounce. This single interaction detail got the best reaction during testing (my kid).
No backend: The app makes zero network requests. No analytics SDK, no crash reporter, no feature flags. Surprisingly liberating. The privacy policy is one paragraph.
App Store review: Taking about 24 hours. The iPad screenshot requirement caught me — you need 2064×2752 for 13" iPad even if your app is iPhone-first.

Biggest lesson: Shipping beats perfecting. Version 1 doesn't have half the features I planned. But it's in the store and real kids are tapping elephants.
App Store: [link when live]
Repo/stack: SwiftUI, AVFoundation, no third-party dependencies.

What would you add to v2?

Hey r/SideProject — I just launched VectorVaultAI and wanted to share it here for feedback.

**The problem:** Every time I built an AI agent, I kept solving the same problem — giving it persistent memory that survives across sessions. Existing solutions (Pinecone, Weaviate) work great but get expensive fast, and they charge you per query on top of storage.

**What I built:** VectorVaultAI is a semantic vector memory layer for AI apps. You store knowledge with `vault.remember()`, retrieve it by meaning with `vault.recall()`, and inject it into your LLM's context. Three primitives, one API.

**Pricing:** $0 free tier (1M vectors), $39/mo Pro (10M vectors, unlimited recalls). No per-query fees ever.

**Stack:** pgvector + semantic embeddings, Python + TypeScript SDKs, sub-10ms recall.

Would love brutal feedback — especially from anyone who's dealt with the memory problem in their own AI projects. What's missing? What would make you actually use this?

👉 vectorvaultai.com

vectorvaultai.com