Insights on Building Better Software

Not every mobile app needs AI. Priya Gaudani shares a practical framework for deciding when it improves the user experience—and when traditional engineering is the better choice.

There is no single “best” database. The right choice depends on your workload. Ajay Kumar Maurya explores where MySQL, PostgreSQL and ClickHouse each make sense.

Audit history grows quickly, but most searches focus on recent events. Explore a hybrid architecture that keeps recent logs in PostgreSQL and queries older records in Amazon S3 through Athena—all through one API.

The React Native choices that quietly determine how your team builds, releases, and recovers for years — and where EAS actually helps.

How early choices in building software quietly turn into expensive constraints later — and what smart teams do differently.

You've heard it said with total confidence, trusted like it was evidence. It isn't. Here's how a green test suite on one laptop becomes a failed checkout in production — and what reproducibility actually takes.

Modern AI can answer questions, write code, and take actions — but it can't see inside your private database. The Model Context Protocol is the open standard that fixes this, giving AI a safe, consistent way to connect to the systems where your data actually lives.

An AI agent that works in a demo and an AI agent that works in production are different systems. This guide covers what actually breaks — compounding step failure, tool design, silent partial success, unbounded loops, context growth — and the evaluation and guardrail work that separates the two.

A traditional FDA clearance freezes your AI device in place — every retrain or improvement risks a new submission. A Predetermined Change Control Plan is how you get cleared to keep updating. This guide covers what a PCCP is, its three required components, and what it demands of your engineering.