I was unsatisfied with my health and fitness level as I started to hit middle age. Over time, I’ve picked up some bad habits and lost a lot of the discipline that I once possessed when I was an infantryman. I decided it was time to take drastic steps to get back in shape, and I heard about a challenge called 75 HARD that seemed to be a good fit.
Sometimes things happen that we just can’t let go of unless we address them. Deep Inhale.
I’m an AI skeptic who still uses LLMs daily for development work. Here’s the workflow I’ve developed to get real value from these tools without falling into the trap of letting them do my thinking for me.
Getting data out of your Postgres database and into a different data store, like BigQuery or Redshift, is easy with logical replication. This guide shows you how.
When applications reach a certain scale, the database quickly becomes a non-negotiable consideration. Strange issues start to appear when storing millions of records and processing thousands of transactions per second. This post offers a few quick pointers for addressing issues as they arise.
While a rake task or background job works fine for most data imports, they become prohibitively slow when dealing with millions of rows. PostgreSQL’s \copy command can handle these large datasets orders of magnitude faster than application-level approaches.
Iterate faster by using vim, tmux, and vim-slime to write and debug your code in a Read, Eval, Print Loop (REPL).
I read the book Shape Up by Ryan Singer, taking extensive notes about the methodology and assessing its viability for adoption by product teams.
A personal reflection on how I stopped caring about traditional metrics like grades and started prioritizing personal growth through challenging experiences.
Discover how polymorphic relationships in ActiveRecord can elegantly separate billing accounts from collaborative groups - a practical guide based on real-world implementation.