Top posts

These are some blog posts which have gotten a disproportionate amount of traffic (10,000+ page views):

2024

• It's hard to write code for computers, but it's even harder to write code for humans

2023

• Simple sabotage for software

2022

• We are still early with the cloud: why software development is overdue for a change

2021

• Storm in the stratosphere: how the cloud will be reshuffled
• Building a data team at a mid-stage startup: a short story
• Software infrastructure 2.0: a wishlist

2020

• How to hire smarter than the market: a toy model
• Never attribute to stupidity that which is adequately explained by opportunity cost

2019

• Why software projects take longer than you think: a statistical model
• Buffet lines are terrible, but let's try to improve them using computer simulations
• Miscellaneous unsolicited (and possibly biased) career advice
• Headcount goals, feature factories, and when to hire those mythical 10x people

2018

• I don't want to learn your garbage query language
• The hacker's guide to uncertainty estimates
• Interviewing is a noisy prediction problem

2017

• The eigenvector of “Why we moved from language X to language Y”
• Language pitch
• Conversion rates – you are (most likely) computing them wrong

2016

• Analyzing 50k fonts using deep neural networks
• NYC subway math
• The half-life of code & the ship of Theseus
• Exploding offers are bullshit
• I believe in the 10x engineer, but…

2014

• Deep learning for chess

…Bonus

The post When machine learning matters didn't get a lot of web traffic, but it was mentioned in the 2017 book Machine, Wisdom Crowd by Andrew McAfee and Erik Brynjolfsson.