Notes on cloud, infrastructure, and shipping things that don't fall over.

Why Gemini Couldn't Change My App's Logo (And What It Reveals About LLM Training)

Summary LLMs loop endlessly on simple tasks instead of admitting failure — a result of training incentives that reward guessing over honesty.

LLMs trained on their own generated data suffer “model collapse,” quietly eroding performance on rare, real-world tasks.

The Pain Point

I asked Gemini Pro, connected to Android Studio via the Gemini API, to add a logo to my app. It should have been simple: the image files were already in the resource folder. Instead, the model kept iterating on the idea without ever executing it.

I Replaced My Budget App With an LLM — Here's What It Actually Costs

The Problem: Categories That Never Fit

I struggled to track my expenses for months. Every budget app I tried made me pick a category, set a budget, and log each purchase — and it always broke down the same way: I’d spend the same amount on the same type of item, but at a different store, and suddenly my neat categories didn’t fit anymore.

A simple example: I used to buy milk and curd from my local kirana store, so I made a dedicated category for it. Recently I switched to a higher-quality (and higher-priced) dairy for the same items. Now my old category is technically wrong, and I have to decide whether to edit it, split it, or just let it drift into inaccuracy.

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Scaling Eks Clusters

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