Following Google’s lead many companies have instituted “20% time” for their employees. This is one day per week in which employees can work on projects of their own choosing. The practice keeps developers motivated and sharp, produces tools to solve company problems, and in the best case creates open source which builds prestige and helps recruitment.
Doing nothing at work
Many engineers should be doing less work. I don’t necessarily mean producing less code or fewer changes, but literally working fewer hours in the day. When they do work, they should be working at a slower pace. I like to aim to be running at 80% utilization by default: unless I have a high-pressure project going on, I spend 20% of my workday away from the computer.
The new 20% time, minus the time
Attention is replacing hours. But is it 120% time all over again?
Running A Software Business On 5 Hours A Week | Kalzumeus Software
This Dumb Industry: In Defense of Crunch - Twenty Sided
Last week I derided permacrunch – the policy of working an entire creative team 70 hours a week all the time – as “the policy of simpletons and sociopaths”. This led to some people asking, “Why is crunch even a thing?” Can’t management just plan the schedule so that the project is done on time using only 40 hour work weeks?
The developer’s dilemma
When it comes to making money, software developers are an odd bunch. Developers produce code, and code is in high demand. At a glance, it…
Building what customers need, not just what they ask for - Linear
Notes from our product team on building the tools we use every day.
How I estimate work as a staff software engineer
There’s a kind of polite fiction at the heart of the software industry. It goes something like this:
Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
We conduct a randomized controlled trial to understand how early-2025 AI tools affect the productivity of experienced open-source developers working on their own repositories. Surprisingly, we find that when developers use AI tools, they take 19% longer than without—AI makes them slower.
How I Went from Burn-out Entrepreneur to Automating my $4M Company and 10x my Productivity.
Building a business is hard enough. On its official website, the U.S. Small Business Administration purports that “roughly 50 percent of…
2026 State of the Workplace
Get the latest insights from state of the workplace report spanning more than 443 million hours of work activity across 1,111 organizations and 163,638 employees over three years.
I'm begging you to manage your time
Stack Overflow Developer Survey 2026
More than 30K technologists from 169 countries have shared their thoughts with us, and now it’s time to share everything we’ve learned with you. So let’s dive into this year’s Annual Developer Survey.
Super Productivity – Open-Source Deep Work Task Manager
The open-source deep work task manager for developers. Plan tasks, track time & notes in a privacy-first workspace for Windows, macOS, Linux, Android & iOS.
Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity
Despite widespread adoption, the impact of AI tools on software development in the wild remains understudied. We conduct a randomized controlled trial (RCT) to understand how AI tools at the February-June 2025 frontier affect the productivity of experienced open-source developers. 16 developers with moderate AI experience complete 246 tasks in mature projects on which they have an average of 5 years of prior experience. Each task is randomly assigned to allow or disallow usage of early 2025 AI tools. When AI tools are allowed, developers primarily use Cursor Pro, a popular code editor, and Claude 3.5/3.7 Sonnet. Before starting tasks, developers forecast that allowing AI will reduce completion time by 24%. After completing the study, developers estimate that allowing AI reduced completion time by 20%. Surprisingly, we find that allowing AI actually increases completion time by 19%--AI tooling slowed developers down. This slowdown also contradicts predictions from experts in economics (39% shorter) and ML (38% shorter). To understand this result, we collect and evaluate evidence for 20 properties of our setting that a priori could contribute to the observed slowdown effect--for example, the size and quality standards of projects, or prior developer experience with AI tooling. Although the influence of experimental artifacts cannot be entirely ruled out, the robustness of the slowdown effect across our analyses suggests it is unlikely to primarily be a function of our experimental design.
Measuring developer productivity? A response to McKinsey
The consulting firm came up with a methodology they claim can measure software developer productivity. But that measurement comes at a high price – and we offer a more sensible approach.
21 Productivity Hacks I’ve Picked Up Over the Years
A thorough list of practical productivity methods I've used and refined over the last 16 years.
