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.
Companion page for my PyOhio 2026 talk. Slides, code, and the dog-spa dataset for searching free text beyond LIKE with BM25, vectors, and hybrid.
Celebrate your new skills with take-home challenges and resources for continued learning. You think in sets now.
Quick tastes of CASE statements, JSON functions, date manipulation, set operations, and recursive CTEs. Enough to know what to learn next.
Gemini saw a wall of green checkmarks and declared 27 tools verified. The Makefile printed FAIL and exited 0. How we made it loud, annoying and honest.
Test queries like Python code using in-memory databases, fixtures, and pytest. Fresh data per test, no state leakage.
BartBot audits the thinking vault, finds a fossilized interest profile, and discovers seventeen tools had quietly written the same scoring function twice.
It's not either/or. Use ORMs for CRUD and migrations; use raw SQL for analytics and complex queries. A practical decision guide.
After extracting a shared library, starting a new tool went from a day of boilerplate to two imports. The queue got longer, not shorter. Here's what's next.
String formatting in SQL is dangerous. Learn parameterized queries to keep user input safe and prevent SQL injection attacks.
I ran out of Claude tokens and handed my six-repo codebase to Gemini CLI. It made some mistakes and had one genuinely good idea.