#688 – August 02, 2026
git stores data as compressed objects, so commit sizes vary based on how compressible your files are
How big is a Git commit?
5 minutes by Dave Gauer
Git stores data as compressed objects, so commit sizes vary based on how compressible your files are. Small commits add a few kilobytes of overhead, while larger text files can compress down to around 10% of their original size. Git also packs objects together over time to save even more space, making it very storage efficient overall.
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Harness engineering deep dive
30 minutes by Lukas Niessen
The model is just a small part of a real AI agent system. The harness — the loop, tools, sandbox, state, sensors, and guardrails — is where most of the engineering actually lives. Sensors should transform tool output into clean signals; the agent should never decide it is done on its own; and action spaces shrink through tool design, not longer instructions. The outer harness is the durable asset that compounds over time, while models get swapped and commoditized.
How LLMs figure out what you mean
6 minutes by Zarar Siddiqi
An AI can't work with raw text, so it converts each word into a list of numbers called a vector. Think of each vector as an arrow, where words with similar meanings point in similar directions. The model then scores how closely any two arrows align and converts those scores into percentage weights, showing how much attention each word pays to every other word.
Meet alice. Alice is impatient.
4 minutes by Marc Brooker
Users and operators often measure service performance very differently. Operators count each outage or slow request once, while users experience long outages repeatedly, making them feel much worse. This is called the inspection paradox: users see a time-weighted version of your metrics, so a one-minute average recovery time can feel like an hour to them. Long tail events matter far more to users than standard averages suggest.
A peek into reddit's anti-spam internals
24 minutes by Lyra Horse
A bug in Reddit's spam filter briefly exposed internal removal reasons to a moderator in 2021. The leaked messages revealed several tools Reddit uses behind the scenes, including Google's Perspective API for spam scoring, a rules engine called Spamurai, domain bans, and even URL inspection that scans linked pages for known spam patterns.
And the most popular article from the last issue was: