Rethinking the Knowledge Base: Maybe Just Start with an LLM Wiki?
I looked into GraphRAG and LLM Wiki and found that both "distill" raw data with an LLM. Here is my understanding of how each developed, the problems they share, and which one to pick.
A digital version of my messy desk. Half-finished projects, random thoughts, and life logs.
I looked into GraphRAG and LLM Wiki and found that both "distill" raw data with an LLM. Here is my understanding of how each developed, the problems they share, and which one to pick.
I wanted to make an unfamiliar codebase visible, so I looked into static analysis tools. How I use ripgrep, ast-grep, Serena and CodeQL, and what I learned from a small trial.
REA, Adobe clones, GTA and Halo in the browser. A week of "Software is over / done / dead" takes, sorted out by a software engineer: what actually ends, and what stays.
Organizing everything I learned about AI/ML during my holiday crash course. Part 1 covers general principles and an overview of classic, non-NN machine learning models.
House hunting saga in Japan. From spec-driven logic to realizing the importance of intuition.
The reality of AI development is a bit different from the magic shown on TikTok. A story about the struggle and fun of managing a digital Sheldon Cooper.
Rakuten, Moving to the US, Meta, Google, Returning to Japan, Kyndryl. Reflecting on my engineering journey so far.
From Yamaguchi, Texas-influenced, living in Tokyo.