Computing Life

After weeks of severe insomnia, I used AI to build an iOS app that exported HealthKit data and ran multivariate regression to find the root cause—late-night AI-assisted intense multitasking. This post explores how AI provided end-to-end execution support and why certain things still require human judgment.

Querying layout results takes one line of code on iOS, Android, Qt, and Flutter. On the web, it requires triggering a full-page reflow. This isn't because browser engineers are incompetent. CSS made a deliberate architectural choice in 1994 toward declarative layout, which has a higher ceiling but hides intermediate state. Facebook paid hundreds of millions of dollars in 2012 for not understanding this trade-off. SwiftUI and Jetpack Compose prove that declarative and observable can coexist through proper layering. The lesson applies to all system design: good abstractions let you choose which layer to work at; bad abstractions glue all layers together and leave you no choice.

An LLM's default output is consensus: correct but mediocre. Deep Research is really Wide Research. We found a systematic way to pull LLMs out of consensus using personal cognitive context. One year of experimentation, with controlled evidence.

The gap between using AI and using AI well is 10x. That gap comes from how you work, not which model you use. This post walks through a complete workflow example and a Three Tiers framework to explain why you should switch from ChatGPT to agentic tools like Cursor.

A real-world case study of directing AI to add SEO summaries to 300 articles in two minutes, breaking down five key decisions: choosing the right execution environment, building tests before work, letting agents handle corner cases, divide and conquer, and outcome-oriented prompt writing.