Obsidian + Claude Code is everywhere right now. But pointing an AI at a folder of markdown files and hoping for the best doesn’t work. What matters is how you structure the knowledge base. Get that right, and Claude becomes genuinely useful. Get it wrong, and you get confident garbage. There’s been a wave of posts about this combo lately: James Bedford’s full walkthrough, Greg Isenberg’s “personal OS” approach, kepano (Obsidian’s CEO) sharing Claude Skills. They’re all worth reading.
Boris Cherny created Claude Code. When he shared how he actually uses it day-to-day, the setup was surprisingly simple. I went through every tip, tried most of them, and have opinions about all of them. The original thread is on Boris’s X account. A good companion site is howborisusesclaudecode.com which compiles everything in one place.
I spent five years on the AWS Billing team. The hardest problem I tackled was detecting when customers used AWS services but weren’t charged correctly. This post walks through how I designed a system that reduced charge discrepancies by 300x and eliminated 230 million monthly false positives. The Problem # AWS billing is trickier than it looks. When a customer launches an EC2 instance, writes to S3, or queries DynamoDB, each action generates a usage record. These records flow through a pipeline that calculates charges based on the customer’s pricing plan, region, and service tier.
At Twitter, I was responsible for kernel updates across 5,000+ production servers. Updating a kernel is risky on one machine. Doing it across a fleet, without downtime, without data loss, and without breaking the services that millions of people depend on, is a different problem entirely. The Problem # Twitter’s production infrastructure ran on thousands of bare-metal servers across multiple data centers. Each server ran a Linux kernel that needed regular updates for security patches, performance improvements, and hardware compatibility.
Your development environment should feel like one cohesive tool, not a collection of unrelated windows with clashing colors. I theme everything with the same palette — Catppuccin Mocha
Imagine you’re blindfolded on a mountain and you need to find the lowest valley. You can’t see anything, but you can feel the ground under your feet. What would you do? You’d feel which direction slopes downward, take a small step that way, and repeat. Congratulations — you just invented gradient descent, the algorithm behind nearly every modern AI system. Why Should You Care? # Optimization is everywhere. When your GPS finds the fastest route, when Netflix recommends a movie, when your phone recognizes your face — behind all of these is an algorithm trying to find the best possible answer from a sea of possibilities. Gradient descent is the workhorse algorithm that makes this happen.
