Using linked-list insertion and binary-tree traversal as examples, this post argues that algorithm learning works better when you draw the structure, simulate the steps, explain the invariant, and only then write code.

Auto-scroll in an AI chat is not just scrollTop. It needs intent signals, a follow/free state machine, handling for programmatic scroll events, virtualization, and mobile edge cases.

Based on hands-on use of Copilot, Cursor, and Claude Code, this post separates where AI assistants help most, such as search, boilerplate, and error diagnosis, from where they still struggle, such as architecture and edge cases.

A short note on completing BlueDot Impact AI Safety Fundamentals, receiving the certificate, and sharpening my direction toward agent safety evals, tool-use safety, and reliable AI infrastructure.