English

Argues that effective AI-assisted programming shifts focus from data structures and algorithms to writing detailed comments and DocStrings. Draws parallels between managing AI and managing human teams, emphasizing delegation, context provision, and quality checks.

Compares three approaches to writing a course introduction—fully AI, AI-assisted, and fully human. Reveals that human writing conveys tension and engagement that AI's diplomatic, detached style lacks, and choosing not to use AI can itself show respect to users.

A practical guide to prompt engineering: matching tasks to LLM capabilities, managing context windows, using web search for reliability, and leveraging agents for domains like math and robotics.

Observes that AI elevates programming from last resort to first-class problem-solving method and enables personalized, hands-on learning. Argues AI's impact on IT is democratization of programming and transformation of how we acquire technical skills.

Documents an experiment connecting AI to astrophotography robotics. Explores the security-flexibility tradeoff, using Python with class encapsulation, AST parsing, and sandboxing to safely let AI control telescope equipment while preventing malicious code execution.

A two-week deep dive into Apple Vision Pro reveals it's fundamentally a VR device, not AR. Excels at hands-free scenarios like lying down, exercising, or multitasking with multiple windows, but falls short for office work and VR viewing due to limitations in text density and format support.

A real-world case study of building a complete astronomical observatory notification system in 8 hours using AI assistance. Explores how GPT-4 and Copilot can dramatically boost software engineering productivity across monitoring, server, iOS, and design tasks.

Third iteration: wrap GPT voice tools into Apple Shortcuts, creating a flexible "points and lines" execution platform that integrates deeply with mobile workflows.

GPT-4 and Copilot reduced a week-long NLP task to 10 minutes—building a natural language text editor with JSON output. Even prompt engineering can be automated by AI.

Evolving a voice transcription tool into an idea iteration system: GPT not just transcribes but asks insightful questions, challenges assumptions, and helps refine thoughts before output.