Most posts here are part of a series, so if one is useful, the one before it probably is too. The SQL for Python Developers series is the place to start if you came for SQL; I Vibe Coded and Lived to Tell if you came for the AI stories.
An AI writes instructions for itself, backs up its own memory, and builds a tool to read articles on your behalf. It considers this progress.
Two sessions, two takeaways, and why you should not skip the training day at PyTexas.
Conferences are a fun part of participating in the technical community. In this T-SQL Tuesday post, let's explore the impact they have had on my career
The terminal window is a powerful tool that lets you quickly verify what LLMs tell you that they have done
NULL means unknown, not empty. Why NULL = NULL isn't true, three-valued logic, and how NULL behaves in WHERE, GROUP BY, JOINs and subqueries.
Six Python projects, four duplicated files, one shared library. The code behind the extraction, what moved, and the surprise that made it worth it.
How to run a local LLM from a Python script without an API key, a virtual environment, or Docker. You need two tools and one file.
You have been taking notes for a month. You cannot find anything. Here is how frontmatter fixes that and prepares your wiki for an LLM.
WITH clauses let you name your subqueries and read top-to-bottom instead of inside-out. Transform nested spaghetti into clean steps.
Karpathy called LLM-based knowledge bases "very useful." Why the architecture works and how to start building one in practice.