This is the third post in my Google Cloud Next '26 (Las Vegas) recap series. You can find the previous posts here 👇 Part 1: [Google Cloud Next '26 Recap #1] Hands-On with the Agentic Hack Zone Part 2: [Google Cloud Next '26 Recap #2] Three Unique Booths I Tried at the EXPO In Parts 1 and 2, I covered my experiences on the EXPO floor. This time, I'd like to switch gears and share one of the se
An opinionated list of Python frameworks, libraries, tools, and resources
In my previous article about treating architecture documentation as a first-class asset, I had a great discussion in the comments about enforcing architectural rules. I promised to share materials from my recent Google Developer Groups workshop. The workshop is now finished! Here is the story of how I built an AI Quality Gate, how it helped me solve the internal "CEO, CTO, CFO, CISO" conflict, and
I shipped gni-compression to npm two days ago. One of the first questions I got (from myself, running benchmarks at midnight): does it work on anything other than chat data? Short answer: not yet. Long answer: I found out exactly why, and it led me somewhere more interesting than I expected. After the npm launch I ran GN against Silesia — the standard general text compression benchmark suite. Dick
Introduction Picture two doctors updating the same patient record at the same time - one in São Paulo, the other in London. Both are offline. When connectivity returns, whose changes prevail? This is not a hypothetical. It is the everyday reality of distributed systems: multiple nodes, no shared clock, no guaranteed network. The conventional answer has long been locking - one node waits while an
I keep seeing the same argument about AI making us dumber. It's the same argument people had about search engines, and before that books. The usual response is to point at history and say "every generation panics, every generation was wrong, relax." I think that response is half right, and the wrong half is what bothers me. Tools change what we bother to remember. The people who'd trained their wh
A few years ago I solved 200 LeetCode problems and still froze on Mediums I hadn't seen. The breakthrough wasn't another hundred problems. It was a different loop. A problem asks for the longest substring with at most K distinct characters. You've solved sliding window before. Maximum sum subarray of size K, done. Longest substring without repeating characters, done. This third one stalls you. Twe
Introduction Some code works. Some code lasts. The difference rarely comes down to typing speed, syntax mastery, or how many nights you're willing to push through. It comes down to how you think about a problem before you write a single line. Big-O notation is a mathematical framework that describes how an algorithm performs as its input grows. In plain terms, it answers one question: